기계 번역으로 제공되는 번역입니다. 제공된 번역과 원본 영어의 내용이 상충하는 경우에는 영어 버전이 우선합니다.

# Docker 레지스트리 경로 및 예제 코드
<a name="sagemaker-algo-docker-registry-paths"></a>

다음 항목에는 Docker 레지스트리 경로와 Amazon SageMaker AI에서 제공하는 각 알고리즘 및 딥 러닝 컨테이너(DLC)에 대한 기타 파라미터가 나열되어 있습니다. 추가 정보는 [사전 빌드된 SageMaker 도커 이미지 사용](https://docs.aws.amazon.com/sagemaker/latest/dg/docker-containers-prebuilt.html)을 참조하세요.

경로를 다음과 같이 사용하세요.
+ 훈련 작업([훈련\$1작업\$1생성](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_training_job))을 생성하려면 Docker 레지스트리 경로(`TrainingImage`) 및 훈련 이미지에 대한 훈련 입력 모드(`TrainingInputMode`)를 지정합니다. 특정 데이터 세트를 사용하여 훈련할 훈련 작업을 생성합니다.
+ 모델 ([모델\$1생성](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/sagemaker.html#SageMaker.Client.create_model))을 생성하려면 추론 이미지(`PrimaryContainer Image`)에 대한 Docker 레지스트리 경로(`Image`)를 지정합니다. SageMaker AI에서는 엔드포인트 구성을 기반으로 하는 기계 학습 컴퓨팅 인스턴스를 시작하고 아티팩트(모델 훈련의 결과)가 포함된 모델을 배포합니다.
+ 모델 모니터를 생성하려면 AWS 리전을 선택한 다음 **모델 모니터(알고리즘)**를 선택합니다. 자세한 내용은 [Amazon SageMaker AI Model Monitor 사전 구축 컨테이너](https://docs.aws.amazon.com/sagemaker/latest/dg/model-monitor-pre-built-container.html)를 참조하세요.

**참고**  
사전 구축된 컨테이너 이미지는 SageMaker AI 서비스에서 관리하며 경우에 따라 독점 코드를 포함합니다. 훈련 및 처리 작업, 배치 변환, 실시간 추론과 같은 기능은 서비스 소유 자격 증명을 사용하여 관리형 SageMaker AI 인스턴스에서 이미지를 가져오고 실행합니다. 고객 자격 증명은 사용되지 않으므로 Amazon ECR 권한을 거부하는 모든 AWS IAM 정책(서비스 제어 정책 및 리소스 제어 정책 포함)은 사전 빌드된 이미지 사용을 금지하지 않습니다.

**참고**  
레지스트리 경로에서 `:1` 버전 태그를 사용하여 안정적인 버전의 알고리즘/DLC을 사용 중인지 확인합니다. `:1` 태그를 보유한 추론 이미지에 있는 `:1` 태그가 포함된 이미지를 사용하여 훈련된 모델을 안정적으로 호스팅할 수 있습니다. 레지스트리 경로에서 `:latest` 태그를 사용하면 최신 버전의 알고리즘/DLC가 제공되지만 하위 버전 호환성 문제가 발생할 수 있습니다. 생산 목적의 경우 `:latest` 태그 사용을 피하세요.

**중요**  
SageMaker AI XGBoost 이미지 URI를 검색할 때 이미지 URI 태그에는 `:latest` 또는 `:1`을 사용하지 마세요. 사용하려는 네이티브 XGBoost 패키지 버전이 포함된 SageMaker AI 관리 XGBoost 컨테이너를 선택하려면 [지원 버전](https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost.html#xgboost-supported-versions) 중 하나를 지정해야 합니다. SageMaker AI XGBoost 컨테이너로 마이그레이션된 패키지 버전을 찾으려면 AWS 리전 을 선택한 다음 **XGBoost(알고리즘)** 섹션으로 이동하세요.

레지스트리 경로를 찾으려면 AWS 리전을 선택한 다음 알고리즘 또는 DLC를 선택합니다.

**Topics**
+ [미국 동부(버지니아 북부)](ecr-us-east-1.md)
+ [미국 동부(오하이오)](ecr-us-east-2.md)
+ [미국 서부(캘리포니아 북부)](ecr-us-west-1.md)
+ [미국 서부(오리건)](ecr-us-west-2.md)
+ [아프리카(케이프타운)](ecr-af-south-1.md)
+ [아시아 태평양(홍콩)](ecr-ap-east-1.md)
+ [(ap-east-2)용 Docker 레지스트리 경로 및 예시 코드](ecr-ap-east-2.md)
+ [아시아 태평양(하이데라바드)](ecr-ap-south-2.md)
+ [아시아 태평양(자카르타)](ecr-ap-southeast-3.md)
+ [아시아 태평양(말레이시아)](ecr-ap-southeast-5.md)
+ [아시아 태평양(멜버른)](ecr-ap-southeast-4.md)
+ [아시아 태평양(뭄바이)](ecr-ap-south-1.md)
+ [아시아 태평양(오사카)](ecr-ap-northeast-3.md)
+ [아시아 태평양(서울)](ecr-ap-northeast-2.md)
+ [아시아 태평양(싱가포르)](ecr-ap-southeast-1.md)
+ [아시아 태평양(시드니)](ecr-ap-southeast-2.md)
+ [아시아 태평양(태국)](ecr-ap-southeast-7.md)
+ [아시아 태평양(도쿄)](ecr-ap-northeast-1.md)
+ [캐나다(중부)](ecr-ca-central-1.md)
+ [캐나다 서부(캘거리)](ecr-ca-west-1.md)
+ [중국(베이징)](ecr-cn-north-1.md)
+ [중국(닝샤)](ecr-cn-northwest-1.md)
+ [유럽(프랑크푸르트)](ecr-eu-central-1.md)
+ [유럽(아일랜드)](ecr-eu-west-1.md)
+ [유럽(런던)](ecr-eu-west-2.md)
+ [유럽(밀라노)](ecr-eu-south-1.md)
+ [유럽(파리)](ecr-eu-west-3.md)
+ [유럽(스페인)](ecr-eu-south-2.md)
+ [유럽(스톡홀름)](ecr-eu-north-1.md)
+ [유럽(취리히)](ecr-eu-central-2.md)
+ [이스라엘(텔아비브)](ecr-il-central-1.md)
+ [멕시코(중부)](ecr-mx-central-1.md)
+ [중동(바레인)](ecr-me-south-1.md)
+ [중동(UAE)](ecr-me-central-1.md)
+ [남아메리카(상파울루)](ecr-sa-east-1.md)
+ [AWS GovCloud(미국 동부)](ecr-us-gov-east-1.md)
+ [AWS GovCloud(미국 서부)](ecr-us-gov-west-1.md)

# 미국 동부(버지니아 북부)(us-east-1) Docker 레지스트리 경로 및 예시 코드
<a name="ecr-us-east-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-us-east-1)
+ [BlazingText(알고리즘)](#blazingtext-us-east-1)
+ [Chainer(DLC)](#chainer-us-east-1)
+ [Clarify(알고리즘)](#clarify-us-east-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-us-east-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-us-east-1)
+ [Debugger(알고리즘)](#debugger-us-east-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-us-east-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-us-east-1)
+ [Hugging Face(알고리즘)](#huggingface-us-east-1)
+ [IP Insights(알고리즘)](#ipinsights-us-east-1)
+ [이미지 분류(알고리즘)](#image-classification-us-east-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-us-east-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-us-east-1)
+ [K-Means(알고리즘)](#kmeans-us-east-1)
+ [KNN(알고리즘)](#knn-us-east-1)
+ [LDA(알고리즘)](#lda-us-east-1)
+ [Linear Learner(알고리즘)](#linear-learner-us-east-1)
+ [MXNet(DLC)](#mxnet-us-east-1)
+ [MXNet Coach(DLC)](#coach-mxnet-us-east-1)
+ [모델 모니터(알고리즘)](#model-monitor-us-east-1)
+ [NTM(알고리즘)](#ntm-us-east-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-us-east-1)
+ [Neo MXNet(DLC)](#neo-mxnet-us-east-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-us-east-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-us-east-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-us-east-1)
+ [객체 감지(알고리즘)](#object-detection-us-east-1)
+ [Object2Vec(알고리즘)](#object2vec-us-east-1)
+ [PCA(알고리즘)](#pca-us-east-1)
+ [PyTorch(DLC)](#pytorch-us-east-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-us-east-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-us-east-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-us-east-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-us-east-1)
+ [Scikit-learn(알고리즘)](#sklearn-us-east-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-us-east-1)
+ [Seq2Seq(알고리즘)](#seq2seq-us-east-1)
+ [Spark(알고리즘)](#spark-us-east-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-us-east-1)
+ [Tensorflow(DLC)](#tensorflow-us-east-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-us-east-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-us-east-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-us-east-1)
+ [VW(알고리즘)](#vw-us-east-1)
+ [XGBoost(알고리즘)](#xgboost-us-east-1)

## AutoGluon(알고리즘)
<a name="autogluon-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='us-east-1',image_scope='inference',version='0.4')

# Output path
'763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:0.4-cpu-py38'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='us-east-1')

# Output path
'811284229777.dkr.ecr.us-east-1.amazonaws.com/blazingtext:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='us-east-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')

# Output path
'520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-chainer:5.0.0-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='us-east-1',version='1.0',image_scope='processing')

# Output path
'205585389593.dkr.ecr.us-east-1.amazonaws.com/sagemaker-clarify-processing:1.0'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 205585389593.dkr.ecr.us-east-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')

# Output path
'763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='us-east-1')

# Output path
'663277389841.dkr.ecr.us-east-1.amazonaws.com/sagemaker-data-wrangler-container:1.x'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 663277389841.dkr.ecr.us-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 663277389841.dkr.ecr.us-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 663277389841.dkr.ecr.us-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='us-east-1')

# Output path
'503895931360.dkr.ecr.us-east-1.amazonaws.com/sagemaker-debugger-rules:latest'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 503895931360.dkr.ecr.us-east-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='us-east-1')

# Output path
'522234722520.dkr.ecr.us-east-1.amazonaws.com/forecasting-deepar:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 522234722520.dkr.ecr.us-east-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/factorization-machines:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='us-east-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')

# Output path
'763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.4.2-gpu-py37'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/ipinsights:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='us-east-1')

# Output path
'811284229777.dkr.ecr.us-east-1.amazonaws.com/image-classification:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='us-east-1',version='1.5.1',instance_type='ml.inf1.6xlarge')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-mxnet:1.5.1-inf-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='us-east-1',version='1.9',py_version='py3')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-pytorch:1.9-inf-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/kmeans:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/knn:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='us-east-1')

# Output path
'766337827248.dkr.ecr.us-east-1.amazonaws.com/lda:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 766337827248.dkr.ecr.us-east-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/linear-learner:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='us-east-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')

# Output path
'763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference:1.4.1-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='us-east-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')

# Output path
'520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='us-east-1')

# Output path
'156813124566.dkr.ecr.us-east-1.amazonaws.com/sagemaker-model-monitor-analyzer'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 156813124566.dkr.ecr.us-east-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/ntm:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='us-east-1')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/image-classification-neo:latest'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='us-east-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-mxnet:1.8-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='us-east-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:1.6-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='us-east-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-tensorflow:1.15.3-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='us-east-1')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/xgboost-neo:latest'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='us-east-1')

# Output path
'811284229777.dkr.ecr.us-east-1.amazonaws.com/object-detection:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/object2vec:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/pca:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-us-east-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='us-east-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')

# Output path
'763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:1.8.0-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')

# Output path
'763104351884.dkr.ecr.us-west-2.amazon.aws.com/pytorch-neuron:1.10.2-neuron-py37-sdk1.19.0-ubuntu18.04'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')

# Output path
'763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-trcomp-training:1.12.0-gpu-py38-cu113-ubuntu20.04-sagemaker'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='us-east-1')

# Output path
'382416733822.dkr.ecr.us-east-1.amazonaws.com/randomcutforest:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 382416733822.dkr.ecr.us-east-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='us-east-1',version='0.8.5',instance_type='ml.c5.4xlarge')

# Output path
'462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-cpu-py36'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='us-east-1',version='0.23-1',image_scope='inference')

# Output path
'683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:0.23-1-cpu-py3'
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='us-east-1')

# Output path
'811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='us-east-1')

# Output path
'811284229777.dkr.ecr.us-east-1.amazonaws.com/seq2seq:1'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='us-east-1',version='3.0',image_scope='processing')

# Output path
'173754725891.dkr.ecr.us-east-1.amazonaws.com/sagemaker-spark-processing:3.0-cpu'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 173754725891.dkr.ecr.us-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 173754725891.dkr.ecr.us-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 173754725891.dkr.ecr.us-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 173754725891.dkr.ecr.us-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 173754725891.dkr.ecr.us-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='us-east-1',version='2.4')

# Output path
'683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-sparkml-serving:2.4'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-us-east-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='us-east-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')

# Output path
'520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-serving:1.12.0-cpu'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='us-east-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')

# Output path
'462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-cpu-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='us-east-1',version='1.15.0',instance_type='ml.inf1.6xlarge')

# Output path
'785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-tensorflow:1.15.0-inf-py3'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 785573368785.dkr.ecr.us-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='us-east-1',version='0.8.5',instance_type='ml.c5.4xlarge')

# Output path
'462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-cpu-py36'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='us-east-1',version='8.7.0',image_scope='training')

# Output path
'462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-cpu'
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-us-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='us-east-1',version='1.5-1')

# Output path
'683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:1.5-1'
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 811284229777.dkr.ecr.us-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 683313688378.dkr.ecr.us-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 미국 동부(오하이오)(us-east-2) Docker 레지스트리 경로 및 예시 코드
<a name="ecr-us-east-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-us-east-2)
+ [BlazingText(알고리즘)](#blazingtext-us-east-2)
+ [Chainer(DLC)](#chainer-us-east-2)
+ [Clarify(알고리즘)](#clarify-us-east-2)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-us-east-2)
+ [Data Wrangler(알고리즘)](#data-wrangler-us-east-2)
+ [Debugger(알고리즘)](#debugger-us-east-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-us-east-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-us-east-2)
+ [Hugging Face(알고리즘)](#huggingface-us-east-2)
+ [IP Insights(알고리즘)](#ipinsights-us-east-2)
+ [이미지 분류(알고리즘)](#image-classification-us-east-2)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-us-east-2)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-us-east-2)
+ [K-Means(알고리즘)](#kmeans-us-east-2)
+ [KNN(알고리즘)](#knn-us-east-2)
+ [LDA(알고리즘)](#lda-us-east-2)
+ [Linear Learner(알고리즘)](#linear-learner-us-east-2)
+ [MXNet(DLC)](#mxnet-us-east-2)
+ [MXNet Coach(DLC)](#coach-mxnet-us-east-2)
+ [모델 모니터(알고리즘)](#model-monitor-us-east-2)
+ [NTM(알고리즘)](#ntm-us-east-2)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-us-east-2)
+ [Neo MXNet(DLC)](#neo-mxnet-us-east-2)
+ [Neo PyTorch(DLC)](#neo-pytorch-us-east-2)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-us-east-2)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-us-east-2)
+ [객체 감지(알고리즘)](#object-detection-us-east-2)
+ [Object2Vec(알고리즘)](#object2vec-us-east-2)
+ [PCA(알고리즘)](#pca-us-east-2)
+ [PyTorch(DLC)](#pytorch-us-east-2)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-us-east-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-us-east-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-us-east-2)
+ [Ray PyTorch(DLC)](#ray-pytorch-us-east-2)
+ [Scikit-learn(알고리즘)](#sklearn-us-east-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-us-east-2)
+ [Seq2Seq(알고리즘)](#seq2seq-us-east-2)
+ [Spark(알고리즘)](#spark-us-east-2)
+ [SparkML Serving(알고리즘)](#sparkml-serving-us-east-2)
+ [Tensorflow(DLC)](#tensorflow-us-east-2)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-us-east-2)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-us-east-2)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-us-east-2)
+ [VW(알고리즘)](#vw-us-east-2)
+ [XGBoost(알고리즘)](#xgboost-us-east-2)

## AutoGluon(알고리즘)
<a name="autogluon-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='us-east-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='us-east-2',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='us-east-2',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 211330385671.dkr.ecr.us-east-2.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 415577184552.dkr.ecr.us-east-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 415577184552.dkr.ecr.us-east-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 415577184552.dkr.ecr.us-east-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 915447279597.dkr.ecr.us-east-2.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 566113047672.dkr.ecr.us-east-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='us-east-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='us-east-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='us-east-2',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 999911452149.dkr.ecr.us-east-2.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='us-east-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='us-east-2',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 777275614652.dkr.ecr.us-east-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='us-east-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='us-east-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='us-east-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-us-east-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='us-east-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 404615174143.dkr.ecr.us-east-2.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='us-east-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='us-east-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='us-east-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='us-east-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 314815235551.dkr.ecr.us-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 314815235551.dkr.ecr.us-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 314815235551.dkr.ecr.us-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 314815235551.dkr.ecr.us-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 314815235551.dkr.ecr.us-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='us-east-2',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-us-east-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='us-east-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='us-east-2',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='us-east-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 007439368137.dkr.ecr.us-east-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='us-east-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='us-east-2',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.us-east-2.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-us-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='us-east-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 825641698319.dkr.ecr.us-east-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 257758044811.dkr.ecr.us-east-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 미국 서부(캘리포니아 북부)용 Docker 레지스트리 경로 및 예시 코드 (us-west-1)
<a name="ecr-us-west-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-us-west-1)
+ [BlazingText(알고리즘)](#blazingtext-us-west-1)
+ [Chainer(DLC)](#chainer-us-west-1)
+ [Clarify(알고리즘)](#clarify-us-west-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-us-west-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-us-west-1)
+ [Debugger(알고리즘)](#debugger-us-west-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-us-west-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-us-west-1)
+ [Hugging Face(알고리즘)](#huggingface-us-west-1)
+ [IP Insights(알고리즘)](#ipinsights-us-west-1)
+ [이미지 분류(알고리즘)](#image-classification-us-west-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-us-west-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-us-west-1)
+ [K-Means(알고리즘)](#kmeans-us-west-1)
+ [KNN(알고리즘)](#knn-us-west-1)
+ [LDA(알고리즘)](#lda-us-west-1)
+ [Linear Learner(알고리즘)](#linear-learner-us-west-1)
+ [MXNet(DLC)](#mxnet-us-west-1)
+ [MXNet Coach(DLC)](#coach-mxnet-us-west-1)
+ [모델 모니터(알고리즘)](#model-monitor-us-west-1)
+ [NTM(알고리즘)](#ntm-us-west-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-us-west-1)
+ [Neo MXNet(DLC)](#neo-mxnet-us-west-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-us-west-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-us-west-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-us-west-1)
+ [객체 감지(알고리즘)](#object-detection-us-west-1)
+ [Object2Vec(알고리즘)](#object2vec-us-west-1)
+ [PCA(알고리즘)](#pca-us-west-1)
+ [PyTorch(DLC)](#pytorch-us-west-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-us-west-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-us-west-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-us-west-1)
+ [Scikit-learn(알고리즘)](#sklearn-us-west-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-us-west-1)
+ [Seq2Seq(알고리즘)](#seq2seq-us-west-1)
+ [Spark(알고리즘)](#spark-us-west-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-us-west-1)
+ [Tensorflow(DLC)](#tensorflow-us-west-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-us-west-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-us-west-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-us-west-1)
+ [VW(알고리즘)](#vw-us-west-1)
+ [XGBoost(알고리즘)](#xgboost-us-west-1)

## AutoGluon(알고리즘)
<a name="autogluon-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='us-west-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='us-west-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='us-west-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 740489534195.dkr.ecr.us-west-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 926135532090.dkr.ecr.us-west-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 926135532090.dkr.ecr.us-west-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 926135532090.dkr.ecr.us-west-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 685455198987.dkr.ecr.us-west-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='us-west-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='us-west-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='us-west-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='us-west-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='us-west-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 890145073186.dkr.ecr.us-west-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='us-west-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='us-west-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='us-west-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-us-west-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='us-west-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='us-west-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='us-west-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='us-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='us-west-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 667973535471.dkr.ecr.us-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 667973535471.dkr.ecr.us-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 667973535471.dkr.ecr.us-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 667973535471.dkr.ecr.us-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 667973535471.dkr.ecr.us-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='us-west-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-us-west-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='us-west-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='us-west-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='us-west-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 710691900526.dkr.ecr.us-west-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='us-west-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='us-west-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-us-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='us-west-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 632365934929.dkr.ecr.us-west-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 746614075791.dkr.ecr.us-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 미국 서부(오레곤)(us-west-2) Docker 레지스트리 경로 및 예시 코드
<a name="ecr-us-west-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-us-west-2)
+ [BlazingText(알고리즘)](#blazingtext-us-west-2)
+ [Chainer(DLC)](#chainer-us-west-2)
+ [Clarify(알고리즘)](#clarify-us-west-2)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-us-west-2)
+ [Data Wrangler(알고리즘)](#data-wrangler-us-west-2)
+ [Debugger(알고리즘)](#debugger-us-west-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-us-west-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-us-west-2)
+ [Hugging Face(알고리즘)](#huggingface-us-west-2)
+ [IP Insights(알고리즘)](#ipinsights-us-west-2)
+ [이미지 분류(알고리즘)](#image-classification-us-west-2)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-us-west-2)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-us-west-2)
+ [K-Means(알고리즘)](#kmeans-us-west-2)
+ [KNN(알고리즘)](#knn-us-west-2)
+ [LDA(알고리즘)](#lda-us-west-2)
+ [Linear Learner(알고리즘)](#linear-learner-us-west-2)
+ [MXNet(DLC)](#mxnet-us-west-2)
+ [MXNet Coach(DLC)](#coach-mxnet-us-west-2)
+ [모델 모니터(알고리즘)](#model-monitor-us-west-2)
+ [NTM(알고리즘)](#ntm-us-west-2)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-us-west-2)
+ [Neo MXNet(DLC)](#neo-mxnet-us-west-2)
+ [Neo PyTorch(DLC)](#neo-pytorch-us-west-2)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-us-west-2)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-us-west-2)
+ [객체 감지(알고리즘)](#object-detection-us-west-2)
+ [Object2Vec(알고리즘)](#object2vec-us-west-2)
+ [PCA(알고리즘)](#pca-us-west-2)
+ [PyTorch(DLC)](#pytorch-us-west-2)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-us-west-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-us-west-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-us-west-2)
+ [Ray PyTorch(DLC)](#ray-pytorch-us-west-2)
+ [Scikit-learn(알고리즘)](#sklearn-us-west-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-us-west-2)
+ [Seq2Seq(알고리즘)](#seq2seq-us-west-2)
+ [Spark(알고리즘)](#spark-us-west-2)
+ [SparkML Serving(알고리즘)](#sparkml-serving-us-west-2)
+ [Tensorflow(DLC)](#tensorflow-us-west-2)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-us-west-2)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-us-west-2)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-us-west-2)
+ [VW(알고리즘)](#vw-us-west-2)
+ [XGBoost(알고리즘)](#xgboost-us-west-2)

## AutoGluon(알고리즘)
<a name="autogluon-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='us-west-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='us-west-2',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='us-west-2',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 306415355426.dkr.ecr.us-west-2.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174368400705.dkr.ecr.us-west-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 174368400705.dkr.ecr.us-west-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 174368400705.dkr.ecr.us-west-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 895741380848.dkr.ecr.us-west-2.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 156387875391.dkr.ecr.us-west-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='us-west-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='us-west-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='us-west-2',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 266724342769.dkr.ecr.us-west-2.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='us-west-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='us-west-2',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 159807026194.dkr.ecr.us-west-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='us-west-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='us-west-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='us-west-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-us-west-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='us-west-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 174872318107.dkr.ecr.us-west-2.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='us-west-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='us-west-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='us-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='us-west-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 153931337802.dkr.ecr.us-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 153931337802.dkr.ecr.us-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 153931337802.dkr.ecr.us-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 153931337802.dkr.ecr.us-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 153931337802.dkr.ecr.us-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='us-west-2',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-us-west-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='us-west-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.us-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='us-west-2',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='us-west-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 301217895009.dkr.ecr.us-west-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='us-west-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='us-west-2',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.us-west-2.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-us-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='us-west-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 433757028032.dkr.ecr.us-west-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 246618743249.dkr.ecr.us-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아프리카(케이프타운)용 Docker 레지스트리 경로 및 예시 코드 (af-south-1)
<a name="ecr-af-south-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-af-south-1)
+ [BlazingText(알고리즘)](#blazingtext-af-south-1)
+ [Chainer(DLC)](#chainer-af-south-1)
+ [Clarify(알고리즘)](#clarify-af-south-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-af-south-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-af-south-1)
+ [Debugger(알고리즘)](#debugger-af-south-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-af-south-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-af-south-1)
+ [Hugging Face(알고리즘)](#huggingface-af-south-1)
+ [IP Insights(알고리즘)](#ipinsights-af-south-1)
+ [이미지 분류(알고리즘)](#image-classification-af-south-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-af-south-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-af-south-1)
+ [K-Means(알고리즘)](#kmeans-af-south-1)
+ [KNN(알고리즘)](#knn-af-south-1)
+ [Linear Learner(알고리즘)](#linear-learner-af-south-1)
+ [MXNet(DLC)](#mxnet-af-south-1)
+ [MXNet Coach(DLC)](#coach-mxnet-af-south-1)
+ [모델 모니터(알고리즘)](#model-monitor-af-south-1)
+ [NTM(알고리즘)](#ntm-af-south-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-af-south-1)
+ [Neo MXNet(DLC)](#neo-mxnet-af-south-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-af-south-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-af-south-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-af-south-1)
+ [객체 감지(알고리즘)](#object-detection-af-south-1)
+ [Object2Vec(알고리즘)](#object2vec-af-south-1)
+ [PCA(알고리즘)](#pca-af-south-1)
+ [PyTorch(DLC)](#pytorch-af-south-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-af-south-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-af-south-1)
+ [Scikit-learn(알고리즘)](#sklearn-af-south-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-af-south-1)
+ [Seq2Seq(알고리즘)](#seq2seq-af-south-1)
+ [Spark(알고리즘)](#spark-af-south-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-af-south-1)
+ [Tensorflow(DLC)](#tensorflow-af-south-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-af-south-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-af-south-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-af-south-1)
+ [XGBoost(알고리즘)](#xgboost-af-south-1)

## AutoGluon(알고리즘)
<a name="autogluon-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='af-south-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='af-south-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='af-south-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 811711786498.dkr.ecr.af-south-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 143210264188.dkr.ecr.af-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 143210264188.dkr.ecr.af-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 143210264188.dkr.ecr.af-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 314341159256.dkr.ecr.af-south-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='af-south-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='af-south-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='af-south-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='af-south-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='af-south-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 875698925577.dkr.ecr.af-south-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='af-south-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='af-south-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='af-south-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-af-south-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='af-south-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='af-south-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='af-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='af-south-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 309385258863.dkr.ecr.af-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='af-south-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-af-south-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='af-south-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 626614931356.dkr.ecr.af-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='af-south-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='af-south-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 774647643957.dkr.ecr.af-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='af-south-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 313743910680.dkr.ecr.af-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-af-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='af-south-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 455444449433.dkr.ecr.af-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 510948584623.dkr.ecr.af-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(홍콩)용 Docker 레지스트리 경로 및 예시 코드 (ap-east-1)
<a name="ecr-ap-east-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-east-1)
+ [BlazingText(알고리즘)](#blazingtext-ap-east-1)
+ [Chainer(DLC)](#chainer-ap-east-1)
+ [Clarify(알고리즘)](#clarify-ap-east-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-east-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-east-1)
+ [Debugger(알고리즘)](#debugger-ap-east-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-east-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-east-1)
+ [Hugging Face(알고리즘)](#huggingface-ap-east-1)
+ [IP Insights(알고리즘)](#ipinsights-ap-east-1)
+ [이미지 분류(알고리즘)](#image-classification-ap-east-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-east-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-east-1)
+ [K-Means(알고리즘)](#kmeans-ap-east-1)
+ [KNN(알고리즘)](#knn-ap-east-1)
+ [Linear Learner(알고리즘)](#linear-learner-ap-east-1)
+ [MXNet(DLC)](#mxnet-ap-east-1)
+ [MXNet Coach(DLC)](#coach-mxnet-ap-east-1)
+ [모델 모니터(알고리즘)](#model-monitor-ap-east-1)
+ [NTM(알고리즘)](#ntm-ap-east-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-east-1)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-east-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-east-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-east-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-east-1)
+ [객체 감지(알고리즘)](#object-detection-ap-east-1)
+ [Object2Vec(알고리즘)](#object2vec-ap-east-1)
+ [PCA(알고리즘)](#pca-ap-east-1)
+ [PyTorch(DLC)](#pytorch-ap-east-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-east-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-east-1)
+ [Scikit-learn(알고리즘)](#sklearn-ap-east-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-east-1)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-east-1)
+ [Spark(알고리즘)](#spark-ap-east-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-east-1)
+ [Tensorflow(DLC)](#tensorflow-ap-east-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ap-east-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-east-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ap-east-1)
+ [XGBoost(알고리즘)](#xgboost-ap-east-1)

## AutoGluon(알고리즘)
<a name="autogluon-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-east-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ap-east-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-east-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 098760798382.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 707077482487.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 707077482487.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 707077482487.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 199566480951.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-east-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-east-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-east-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-east-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ap-east-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 001633400207.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-east-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-east-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-east-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-east-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-east-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-east-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-east-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 732049463269.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-east-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-east-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-east-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 871362719292.dkr.ecr.ap-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ap-east-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-east-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 110948597952.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ap-east-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 057415533634.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-east-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 286214385809.dkr.ecr.ap-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 651117190479.dkr.ecr.ap-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# (ap-east-2)용 Docker 레지스트리 경로 및 예시 코드
<a name="ecr-ap-east-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [PyTorch(DLC)](#pytorch-ap-east-2)
+ [Spark(알고리즘)](#spark-ap-east-2)
+ [Tensorflow(DLC)](#tensorflow-ap-east-2)

## PyTorch(DLC)
<a name="pytorch-ap-east-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-east-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Spark(알고리즘)
<a name="spark-ap-east-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-east-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 533267296287.dkr.ecr.ap-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 533267296287.dkr.ecr.ap-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 533267296287.dkr.ecr.ap-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 533267296287.dkr.ecr.ap-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 533267296287.dkr.ecr.ap-east-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-east-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-east-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 975050140332.dkr.ecr.ap-east-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

# 아시아 태평양 (하이데라바드)의 Docker 레지스트리 경로 및 예제 코드 (ap-south-2)
<a name="ecr-ap-south-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-south-2)
+ [BlazingText(알고리즘)](#blazingtext-ap-south-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-south-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-south-2)
+ [Hugging Face(알고리즘)](#huggingface-ap-south-2)
+ [IP Insights(알고리즘)](#ipinsights-ap-south-2)
+ [이미지 분류(알고리즘)](#image-classification-ap-south-2)
+ [K-Means(알고리즘)](#kmeans-ap-south-2)
+ [KNN(알고리즘)](#knn-ap-south-2)
+ [Linear Learner(알고리즘)](#linear-learner-ap-south-2)
+ [MXNet(DLC)](#mxnet-ap-south-2)
+ [NTM(알고리즘)](#ntm-ap-south-2)
+ [Object Detection(알고리즘)](#object-detection-ap-south-2)
+ [Object2Vec(알고리즘)](#object2vec-ap-south-2)
+ [PCA(알고리즘)](#pca-ap-south-2)
+ [PyTorch(DLC)](#pytorch-ap-south-2)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ap-south-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-south-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-south-2)
+ [Scikit-learn(알고리즘)](#sklearn-ap-south-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-south-2)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-south-2)
+ [Spark(알고리즘)](#spark-ap-south-2)
+ [Tensorflow(DLC)](#tensorflow-ap-south-2)
+ [XGBoost(알고리즘)](#xgboost-ap-south-2)

## AutoGluon(알고리즘)
<a name="autogluon-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-south-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-south-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## K-Means(알고리즘)
<a name="kmeans-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-south-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## NTM(알고리즘)
<a name="ntm-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## Object Detection(알고리즘)
<a name="object-detection-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-south-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-south-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-south-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-south-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 873151114052.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 873151114052.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 873151114052.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 873151114052.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 873151114052.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-south-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-south-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 772153158452.dkr.ecr.ap-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## XGBoost(알고리즘)
<a name="xgboost-ap-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-south-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 628508329040.dkr.ecr.ap-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(자카르타)의 Docker 레지스트리 경로 및 예제 코드 (ap-southeast-3)
<a name="ecr-ap-southeast-3"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-southeast-3)
+ [BlazingText(알고리즘)](#blazingtext-ap-southeast-3)
+ [Clarify(알고리즘)](#clarify-ap-southeast-3)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-southeast-3)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-southeast-3)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-southeast-3)
+ [Hugging Face(알고리즘)](#huggingface-ap-southeast-3)
+ [IP Insights(알고리즘)](#ipinsights-ap-southeast-3)
+ [이미지 분류(알고리즘)](#image-classification-ap-southeast-3)
+ [K-Means(알고리즘)](#kmeans-ap-southeast-3)
+ [KNN(알고리즘)](#knn-ap-southeast-3)
+ [Linear Learner(알고리즘)](#linear-learner-ap-southeast-3)
+ [MXNet(DLC)](#mxnet-ap-southeast-3)
+ [모델 모니터(알고리즘)](#model-monitor-ap-southeast-3)
+ [NTM(알고리즘)](#ntm-ap-southeast-3)
+ [Object Detection(알고리즘)](#object-detection-ap-southeast-3)
+ [Object2Vec(알고리즘)](#object2vec-ap-southeast-3)
+ [PCA(알고리즘)](#pca-ap-southeast-3)
+ [PyTorch(DLC)](#pytorch-ap-southeast-3)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-southeast-3)
+ [Scikit-learn(알고리즘)](#sklearn-ap-southeast-3)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-southeast-3)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-southeast-3)
+ [Spark(알고리즘)](#spark-ap-southeast-3)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-southeast-3)
+ [Tensorflow(DLC)](#tensorflow-ap-southeast-3)
+ [XGBoost(알고리즘)](#xgboost-ap-southeast-3)

## AutoGluon(알고리즘)
<a name="autogluon-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-southeast-3',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/blazingtext:<태그> | 1 | 추론, 훈련 | 

## Clarify(알고리즘)
<a name="clarify-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-southeast-3',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 705930551576.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-southeast-3',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## K-Means(알고리즘)
<a name="kmeans-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-southeast-3',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669540362728.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## Object Detection(알고리즘)
<a name="object-detection-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-southeast-3"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-southeast-3',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-southeast-3',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-southeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-southeast-3',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 800295151634.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 800295151634.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 800295151634.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 800295151634.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 800295151634.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-southeast-3',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-southeast-3"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-southeast-3',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 907027046896.dkr.ecr.ap-southeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## XGBoost(알고리즘)
<a name="xgboost-ap-southeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-southeast-3',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 951798379941.dkr.ecr.ap-southeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(말레이시아)(ap-southeast-5)용 Docker 레지스트리 경로 및 예시 코드
<a name="ecr-ap-southeast-5"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [PyTorch(DLC)](#pytorch-ap-southeast-5)
+ [Spark(알고리즘)](#spark-ap-southeast-5)
+ [Tensorflow(DLC)](#tensorflow-ap-southeast-5)

## PyTorch(DLC)
<a name="pytorch-ap-southeast-5"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-southeast-5',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Spark(알고리즘)
<a name="spark-ap-southeast-5"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-southeast-5',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 841784149062.dkr.ecr.ap-southeast-5.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 841784149062.dkr.ecr.ap-southeast-5.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 841784149062.dkr.ecr.ap-southeast-5.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 841784149062.dkr.ecr.ap-southeast-5.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 841784149062.dkr.ecr.ap-southeast-5.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-southeast-5"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-southeast-5',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 550225433462.dkr.ecr.ap-southeast-5.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

# 아시아 태평양 (멜버른)의 Docker 레지스트리 경로 및 예제 코드 (ap-southeast-4)
<a name="ecr-ap-southeast-4"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-southeast-4)
+ [BlazingText(알고리즘)](#blazingtext-ap-southeast-4)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-southeast-4)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-southeast-4)
+ [Hugging Face(알고리즘)](#huggingface-ap-southeast-4)
+ [IP Insights(알고리즘)](#ipinsights-ap-southeast-4)
+ [이미지 분류(알고리즘)](#image-classification-ap-southeast-4)
+ [K-Means(알고리즘)](#kmeans-ap-southeast-4)
+ [KNN(알고리즘)](#knn-ap-southeast-4)
+ [Linear Learner(알고리즘)](#linear-learner-ap-southeast-4)
+ [MXNet(DLC)](#mxnet-ap-southeast-4)
+ [NTM(알고리즘)](#ntm-ap-southeast-4)
+ [Object Detection(알고리즘)](#object-detection-ap-southeast-4)
+ [Object2Vec(알고리즘)](#object2vec-ap-southeast-4)
+ [PCA(알고리즘)](#pca-ap-southeast-4)
+ [PyTorch(DLC)](#pytorch-ap-southeast-4)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ap-southeast-4)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-southeast-4)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-southeast-4)
+ [Scikit-learn(알고리즘)](#sklearn-ap-southeast-4)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-southeast-4)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-southeast-4)
+ [Spark(알고리즘)](#spark-ap-southeast-4)
+ [Tensorflow(DLC)](#tensorflow-ap-southeast-4)
+ [XGBoost(알고리즘)](#xgboost-ap-southeast-4)

## AutoGluon(알고리즘)
<a name="autogluon-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-southeast-4',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-southeast-4',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## K-Means(알고리즘)
<a name="kmeans-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-southeast-4',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## NTM(알고리즘)
<a name="ntm-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## Object Detection(알고리즘)
<a name="object-detection-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-southeast-4"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-southeast-4',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-southeast-4',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-southeast-4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-southeast-4',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 819679513684.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 819679513684.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 819679513684.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 819679513684.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 819679513684.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-southeast-4"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-southeast-4',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 457447274322.dkr.ecr.ap-southeast-4.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## XGBoost(알고리즘)
<a name="xgboost-ap-southeast-4"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-southeast-4',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 106583098589.dkr.ecr.ap-southeast-4.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(뭄바이)용 Docker 레지스트리 경로 및 예제 코드 (ap-south-1)
<a name="ecr-ap-south-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-south-1)
+ [BlazingText(알고리즘)](#blazingtext-ap-south-1)
+ [Chainer(DLC)](#chainer-ap-south-1)
+ [Clarify(알고리즘)](#clarify-ap-south-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-south-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-south-1)
+ [Debugger(알고리즘)](#debugger-ap-south-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-south-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-south-1)
+ [Hugging Face(알고리즘)](#huggingface-ap-south-1)
+ [IP Insights(알고리즘)](#ipinsights-ap-south-1)
+ [이미지 분류(알고리즘)](#image-classification-ap-south-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-south-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-south-1)
+ [K-Means(알고리즘)](#kmeans-ap-south-1)
+ [KNN(알고리즘)](#knn-ap-south-1)
+ [LDA(알고리즘)](#lda-ap-south-1)
+ [Linear Learner(알고리즘)](#linear-learner-ap-south-1)
+ [MXNet(DLC)](#mxnet-ap-south-1)
+ [MXNet Coach(DLC)](#coach-mxnet-ap-south-1)
+ [모델 모니터(알고리즘)](#model-monitor-ap-south-1)
+ [NTM(알고리즘)](#ntm-ap-south-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-south-1)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-south-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-south-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-south-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-south-1)
+ [객체 감지(알고리즘)](#object-detection-ap-south-1)
+ [Object2Vec(알고리즘)](#object2vec-ap-south-1)
+ [PCA(알고리즘)](#pca-ap-south-1)
+ [PyTorch(DLC)](#pytorch-ap-south-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ap-south-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-south-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-south-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-ap-south-1)
+ [Scikit-learn(알고리즘)](#sklearn-ap-south-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-south-1)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-south-1)
+ [Spark(알고리즘)](#spark-ap-south-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-south-1)
+ [Tensorflow(DLC)](#tensorflow-ap-south-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ap-south-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-south-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ap-south-1)
+ [VW(알고리즘)](#vw-ap-south-1)
+ [XGBoost(알고리즘)](#xgboost-ap-south-1)

## AutoGluon(알고리즘)
<a name="autogluon-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-south-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ap-south-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-south-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 452307495513.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 089933028263.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 089933028263.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 089933028263.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 904829902805.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-south-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-south-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-south-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-south-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ap-south-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 126357580389.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-south-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-south-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-south-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-south-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-south-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='ap-south-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-south-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-south-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 105495057255.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 105495057255.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 105495057255.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 105495057255.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 105495057255.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-south-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-south-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-south-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ap-south-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-south-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 763008648453.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ap-south-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='ap-south-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-south-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 991648021394.dkr.ecr.ap-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 720646828776.dkr.ecr.ap-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(오사카)용 Docker 레지스트리 경로 및 예시 코드 (ap-northeast-3)
<a name="ecr-ap-northeast-3"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-northeast-3)
+ [BlazingText(알고리즘)](#blazingtext-ap-northeast-3)
+ [Clarify(알고리즘)](#clarify-ap-northeast-3)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-northeast-3)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-northeast-3)
+ [Debugger(알고리즘)](#debugger-ap-northeast-3)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-northeast-3)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-northeast-3)
+ [Hugging Face(알고리즘)](#huggingface-ap-northeast-3)
+ [IP Insights(알고리즘)](#ipinsights-ap-northeast-3)
+ [이미지 분류(알고리즘)](#image-classification-ap-northeast-3)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-northeast-3)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-northeast-3)
+ [K-Means(알고리즘)](#kmeans-ap-northeast-3)
+ [KNN(알고리즘)](#knn-ap-northeast-3)
+ [Linear Learner(알고리즘)](#linear-learner-ap-northeast-3)
+ [MXNet(DLC)](#mxnet-ap-northeast-3)
+ [모델 모니터(알고리즘)](#model-monitor-ap-northeast-3)
+ [NTM(알고리즘)](#ntm-ap-northeast-3)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-northeast-3)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-northeast-3)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-northeast-3)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-northeast-3)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-northeast-3)
+ [객체 감지(알고리즘)](#object-detection-ap-northeast-3)
+ [Object2Vec(알고리즘)](#object2vec-ap-northeast-3)
+ [PCA(알고리즘)](#pca-ap-northeast-3)
+ [PyTorch(DLC)](#pytorch-ap-northeast-3)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-northeast-3)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-northeast-3)
+ [Scikit-learn(알고리즘)](#sklearn-ap-northeast-3)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-northeast-3)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-northeast-3)
+ [Spark(알고리즘)](#spark-ap-northeast-3)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-northeast-3)
+ [Tensorflow(DLC)](#tensorflow-ap-northeast-3)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-northeast-3)
+ [XGBoost(알고리즘)](#xgboost-ap-northeast-3)

## AutoGluon(알고리즘)
<a name="autogluon-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-northeast-3',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/blazingtext:<태그> | 1 | 추론, 훈련 | 

## Clarify(알고리즘)
<a name="clarify-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-northeast-3',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 912233562940.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 913387583493.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 913387583493.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 913387583493.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 479947661362.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-northeast-3',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-northeast-3',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-northeast-3',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-northeast-3',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 990339680094.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-northeast-3',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-northeast-3',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-northeast-3',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-northeast-3"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-northeast-3',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-northeast-3',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-northeast-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-northeast-3',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 102471314380.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 102471314380.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 102471314380.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 102471314380.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 102471314380.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-northeast-3',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-northeast-3"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-northeast-3',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 364406365360.dkr.ecr.ap-northeast-3.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-northeast-3',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 925152966179.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-northeast-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-northeast-3',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 867004704886.dkr.ecr.ap-northeast-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(서울)(ap-northeast-2) Docker 레지스트리 경로 및 예시 코드
<a name="ecr-ap-northeast-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-northeast-2)
+ [BlazingText(알고리즘)](#blazingtext-ap-northeast-2)
+ [Chainer(DLC)](#chainer-ap-northeast-2)
+ [Clarify(알고리즘)](#clarify-ap-northeast-2)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-northeast-2)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-northeast-2)
+ [Debugger(알고리즘)](#debugger-ap-northeast-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-northeast-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-northeast-2)
+ [Hugging Face(알고리즘)](#huggingface-ap-northeast-2)
+ [IP Insights(알고리즘)](#ipinsights-ap-northeast-2)
+ [이미지 분류(알고리즘)](#image-classification-ap-northeast-2)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-northeast-2)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-northeast-2)
+ [K-Means(알고리즘)](#kmeans-ap-northeast-2)
+ [KNN(알고리즘)](#knn-ap-northeast-2)
+ [LDA(알고리즘)](#lda-ap-northeast-2)
+ [Linear Learner(알고리즘)](#linear-learner-ap-northeast-2)
+ [MXNet(DLC)](#mxnet-ap-northeast-2)
+ [MXNet Coach(DLC)](#coach-mxnet-ap-northeast-2)
+ [모델 모니터(알고리즘)](#model-monitor-ap-northeast-2)
+ [NTM(알고리즘)](#ntm-ap-northeast-2)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-northeast-2)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-northeast-2)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-northeast-2)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-northeast-2)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-northeast-2)
+ [객체 감지(알고리즘)](#object-detection-ap-northeast-2)
+ [Object2Vec(알고리즘)](#object2vec-ap-northeast-2)
+ [PCA(알고리즘)](#pca-ap-northeast-2)
+ [PyTorch(DLC)](#pytorch-ap-northeast-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-northeast-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-northeast-2)
+ [Ray PyTorch(DLC)](#ray-pytorch-ap-northeast-2)
+ [Scikit-learn(알고리즘)](#sklearn-ap-northeast-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-northeast-2)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-northeast-2)
+ [Spark(알고리즘)](#spark-ap-northeast-2)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-northeast-2)
+ [Tensorflow(DLC)](#tensorflow-ap-northeast-2)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ap-northeast-2)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-northeast-2)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ap-northeast-2)
+ [VW(알고리즘)](#vw-ap-northeast-2)
+ [XGBoost(알고리즘)](#xgboost-ap-northeast-2)

## AutoGluon(알고리즘)
<a name="autogluon-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-northeast-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ap-northeast-2',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-northeast-2',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 263625296855.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 131546521161.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 131546521161.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 131546521161.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 578805364391.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 204372634319.dkr.ecr.ap-northeast-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-northeast-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-northeast-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-northeast-2',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 293181348795.dkr.ecr.ap-northeast-2.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-northeast-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ap-northeast-2',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 709848358524.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-northeast-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-northeast-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-northeast-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-northeast-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-northeast-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835164637446.dkr.ecr.ap-northeast-2.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='ap-northeast-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-northeast-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-northeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-northeast-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 860869212795.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 860869212795.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 860869212795.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 860869212795.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 860869212795.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-northeast-2',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-northeast-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-northeast-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ap-northeast-2',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-northeast-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 151534178276.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ap-northeast-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='ap-northeast-2',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-northeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-northeast-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 306986355934.dkr.ecr.ap-northeast-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 366743142698.dkr.ecr.ap-northeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양 (싱가포르)의 Docker 레지스트리 경로 및 예제 코드 (ap-southeast-1)
<a name="ecr-ap-southeast-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-southeast-1)
+ [BlazingText(알고리즘)](#blazingtext-ap-southeast-1)
+ [Chainer(DLC)](#chainer-ap-southeast-1)
+ [Clarify(알고리즘)](#clarify-ap-southeast-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-southeast-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-southeast-1)
+ [Debugger(알고리즘)](#debugger-ap-southeast-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-southeast-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-southeast-1)
+ [Hugging Face(알고리즘)](#huggingface-ap-southeast-1)
+ [IP Insights(알고리즘)](#ipinsights-ap-southeast-1)
+ [이미지 분류(알고리즘)](#image-classification-ap-southeast-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-southeast-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-southeast-1)
+ [K-Means(알고리즘)](#kmeans-ap-southeast-1)
+ [KNN(알고리즘)](#knn-ap-southeast-1)
+ [LDA(알고리즘)](#lda-ap-southeast-1)
+ [Linear Learner(알고리즘)](#linear-learner-ap-southeast-1)
+ [MXNet(DLC)](#mxnet-ap-southeast-1)
+ [MXNet Coach(DLC)](#coach-mxnet-ap-southeast-1)
+ [모델 모니터(알고리즘)](#model-monitor-ap-southeast-1)
+ [NTM(알고리즘)](#ntm-ap-southeast-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-southeast-1)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-southeast-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-southeast-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-southeast-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-southeast-1)
+ [객체 감지(알고리즘)](#object-detection-ap-southeast-1)
+ [Object2Vec(알고리즘)](#object2vec-ap-southeast-1)
+ [PCA(알고리즘)](#pca-ap-southeast-1)
+ [PyTorch(DLC)](#pytorch-ap-southeast-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ap-southeast-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-southeast-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-southeast-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-ap-southeast-1)
+ [Scikit-learn(알고리즘)](#sklearn-ap-southeast-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-southeast-1)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-southeast-1)
+ [Spark(알고리즘)](#spark-ap-southeast-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-southeast-1)
+ [Tensorflow(DLC)](#tensorflow-ap-southeast-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ap-southeast-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-southeast-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ap-southeast-1)
+ [VW(알고리즘)](#vw-ap-southeast-1)
+ [XGBoost(알고리즘)](#xgboost-ap-southeast-1)

## AutoGluon(알고리즘)
<a name="autogluon-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-southeast-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ap-southeast-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-southeast-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 834264404009.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 119527597002.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 119527597002.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 119527597002.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 972752614525.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-southeast-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-southeast-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-southeast-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-southeast-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ap-southeast-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 245545462676.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-southeast-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-southeast-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-southeast-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-southeast-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-southeast-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='ap-southeast-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-southeast-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-southeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-southeast-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 759080221371.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 759080221371.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 759080221371.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 759080221371.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 759080221371.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-southeast-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-southeast-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-southeast-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ap-southeast-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-southeast-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 324986816169.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ap-southeast-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='ap-southeast-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-southeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-southeast-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 475088953585.dkr.ecr.ap-southeast-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 121021644041.dkr.ecr.ap-southeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(시드니)용 Docker 레지스트리 경로 및 예제 코드 (ap-southeast-2)
<a name="ecr-ap-southeast-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-southeast-2)
+ [BlazingText(알고리즘)](#blazingtext-ap-southeast-2)
+ [Chainer(DLC)](#chainer-ap-southeast-2)
+ [Clarify(알고리즘)](#clarify-ap-southeast-2)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-southeast-2)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-southeast-2)
+ [Debugger(알고리즘)](#debugger-ap-southeast-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-southeast-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-southeast-2)
+ [Hugging Face(알고리즘)](#huggingface-ap-southeast-2)
+ [IP Insights(알고리즘)](#ipinsights-ap-southeast-2)
+ [이미지 분류(알고리즘)](#image-classification-ap-southeast-2)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-southeast-2)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-southeast-2)
+ [K-Means(알고리즘)](#kmeans-ap-southeast-2)
+ [KNN(알고리즘)](#knn-ap-southeast-2)
+ [LDA(알고리즘)](#lda-ap-southeast-2)
+ [Linear Learner(알고리즘)](#linear-learner-ap-southeast-2)
+ [MXNet(DLC)](#mxnet-ap-southeast-2)
+ [MXNet Coach(DLC)](#coach-mxnet-ap-southeast-2)
+ [모델 모니터(알고리즘)](#model-monitor-ap-southeast-2)
+ [NTM(알고리즘)](#ntm-ap-southeast-2)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-southeast-2)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-southeast-2)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-southeast-2)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-southeast-2)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-southeast-2)
+ [객체 감지(알고리즘)](#object-detection-ap-southeast-2)
+ [Object2Vec(알고리즘)](#object2vec-ap-southeast-2)
+ [PCA(알고리즘)](#pca-ap-southeast-2)
+ [PyTorch(DLC)](#pytorch-ap-southeast-2)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ap-southeast-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-southeast-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-southeast-2)
+ [Ray PyTorch(DLC)](#ray-pytorch-ap-southeast-2)
+ [Scikit-learn(알고리즘)](#sklearn-ap-southeast-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-southeast-2)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-southeast-2)
+ [Spark(알고리즘)](#spark-ap-southeast-2)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-southeast-2)
+ [Tensorflow(DLC)](#tensorflow-ap-southeast-2)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ap-southeast-2)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-southeast-2)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ap-southeast-2)
+ [VW(알고리즘)](#vw-ap-southeast-2)
+ [XGBoost(알고리즘)](#xgboost-ap-southeast-2)

## AutoGluon(알고리즘)
<a name="autogluon-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-southeast-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ap-southeast-2',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-southeast-2',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 007051062584.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 422173101802.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 422173101802.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 422173101802.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 184798709955.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 514117268639.dkr.ecr.ap-southeast-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-southeast-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-southeast-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-southeast-2',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 297031611018.dkr.ecr.ap-southeast-2.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-southeast-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ap-southeast-2',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 563025443158.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-southeast-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-southeast-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-southeast-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-southeast-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-southeast-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 712309505854.dkr.ecr.ap-southeast-2.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='ap-southeast-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-southeast-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-southeast-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-southeast-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 440695851116.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-southeast-2',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-southeast-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-southeast-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-southeast-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ap-southeast-2',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-southeast-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 355873309152.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ap-southeast-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='ap-southeast-2',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-southeast-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-southeast-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 544295431143.dkr.ecr.ap-southeast-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 783357654285.dkr.ecr.ap-southeast-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 아시아 태평양(태국)(ap-southeast-7)용 Docker 레지스트리 경로 및 예시 코드
<a name="ecr-ap-southeast-7"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [PyTorch(DLC)](#pytorch-ap-southeast-7)
+ [Spark(알고리즘)](#spark-ap-southeast-7)
+ [Tensorflow(DLC)](#tensorflow-ap-southeast-7)

## PyTorch(DLC)
<a name="pytorch-ap-southeast-7"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-southeast-7',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Spark(알고리즘)
<a name="spark-ap-southeast-7"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-southeast-7',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 471112967968.dkr.ecr.ap-southeast-7.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 471112967968.dkr.ecr.ap-southeast-7.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 471112967968.dkr.ecr.ap-southeast-7.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 471112967968.dkr.ecr.ap-southeast-7.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 471112967968.dkr.ecr.ap-southeast-7.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-southeast-7"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-southeast-7',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 590183813437.dkr.ecr.ap-southeast-7.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

# 아시아 태평양(도쿄)(ap-northeast-1) Docker 레지스트리 경로 및 예시 코드
<a name="ecr-ap-northeast-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ap-northeast-1)
+ [BlazingText(알고리즘)](#blazingtext-ap-northeast-1)
+ [Chainer(DLC)](#chainer-ap-northeast-1)
+ [Clarify(알고리즘)](#clarify-ap-northeast-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ap-northeast-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-ap-northeast-1)
+ [Debugger(알고리즘)](#debugger-ap-northeast-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ap-northeast-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-ap-northeast-1)
+ [Hugging Face(알고리즘)](#huggingface-ap-northeast-1)
+ [IP Insights(알고리즘)](#ipinsights-ap-northeast-1)
+ [이미지 분류(알고리즘)](#image-classification-ap-northeast-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ap-northeast-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ap-northeast-1)
+ [K-Means(알고리즘)](#kmeans-ap-northeast-1)
+ [KNN(알고리즘)](#knn-ap-northeast-1)
+ [LDA(알고리즘)](#lda-ap-northeast-1)
+ [Linear Learner(알고리즘)](#linear-learner-ap-northeast-1)
+ [MXNet(DLC)](#mxnet-ap-northeast-1)
+ [MXNet Coach(DLC)](#coach-mxnet-ap-northeast-1)
+ [모델 모니터(알고리즘)](#model-monitor-ap-northeast-1)
+ [NTM(알고리즘)](#ntm-ap-northeast-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ap-northeast-1)
+ [Neo MXNet(DLC)](#neo-mxnet-ap-northeast-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-ap-northeast-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ap-northeast-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ap-northeast-1)
+ [객체 감지(알고리즘)](#object-detection-ap-northeast-1)
+ [Object2Vec(알고리즘)](#object2vec-ap-northeast-1)
+ [PCA(알고리즘)](#pca-ap-northeast-1)
+ [PyTorch(DLC)](#pytorch-ap-northeast-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ap-northeast-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ap-northeast-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ap-northeast-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-ap-northeast-1)
+ [Scikit-learn(알고리즘)](#sklearn-ap-northeast-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ap-northeast-1)
+ [Seq2Seq(알고리즘)](#seq2seq-ap-northeast-1)
+ [Spark(알고리즘)](#spark-ap-northeast-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ap-northeast-1)
+ [Tensorflow(DLC)](#tensorflow-ap-northeast-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ap-northeast-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ap-northeast-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ap-northeast-1)
+ [VW(알고리즘)](#vw-ap-northeast-1)
+ [XGBoost(알고리즘)](#xgboost-ap-northeast-1)

## AutoGluon(알고리즘)
<a name="autogluon-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ap-northeast-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ap-northeast-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ap-northeast-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 377024640650.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 649008135260.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 649008135260.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 649008135260.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 430734990657.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 633353088612.dkr.ecr.ap-northeast-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ap-northeast-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ap-northeast-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ap-northeast-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 258307448986.dkr.ecr.ap-northeast-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ap-northeast-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ap-northeast-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 574779866223.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ap-northeast-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ap-northeast-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ap-northeast-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ap-northeast-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ap-northeast-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 351501993468.dkr.ecr.ap-northeast-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='ap-northeast-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ap-northeast-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ap-northeast-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ap-northeast-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 411782140378.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 411782140378.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 411782140378.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 411782140378.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 411782140378.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ap-northeast-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ap-northeast-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ap-northeast-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ap-northeast-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ap-northeast-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ap-northeast-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 941853720454.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ap-northeast-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='ap-northeast-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-ap-northeast-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ap-northeast-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 501404015308.dkr.ecr.ap-northeast-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 354813040037.dkr.ecr.ap-northeast-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 캐나다(중부)의 Docker 레지스트리 경로 및 예제 코드 (ca-central-1)
<a name="ecr-ca-central-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ca-central-1)
+ [BlazingText(알고리즘)](#blazingtext-ca-central-1)
+ [Chainer(DLC)](#chainer-ca-central-1)
+ [Clarify(알고리즘)](#clarify-ca-central-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ca-central-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-ca-central-1)
+ [Debugger(알고리즘)](#debugger-ca-central-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ca-central-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-ca-central-1)
+ [Hugging Face(알고리즘)](#huggingface-ca-central-1)
+ [IP Insights(알고리즘)](#ipinsights-ca-central-1)
+ [이미지 분류(알고리즘)](#image-classification-ca-central-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-ca-central-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-ca-central-1)
+ [K-Means(알고리즘)](#kmeans-ca-central-1)
+ [KNN(알고리즘)](#knn-ca-central-1)
+ [LDA(알고리즘)](#lda-ca-central-1)
+ [Linear Learner(알고리즘)](#linear-learner-ca-central-1)
+ [MXNet(DLC)](#mxnet-ca-central-1)
+ [MXNet Coach(DLC)](#coach-mxnet-ca-central-1)
+ [모델 모니터(알고리즘)](#model-monitor-ca-central-1)
+ [NTM(알고리즘)](#ntm-ca-central-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-ca-central-1)
+ [Neo MXNet(DLC)](#neo-mxnet-ca-central-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-ca-central-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-ca-central-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-ca-central-1)
+ [객체 감지(알고리즘)](#object-detection-ca-central-1)
+ [Object2Vec(알고리즘)](#object2vec-ca-central-1)
+ [PCA(알고리즘)](#pca-ca-central-1)
+ [PyTorch(DLC)](#pytorch-ca-central-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ca-central-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ca-central-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-ca-central-1)
+ [Scikit-learn(알고리즘)](#sklearn-ca-central-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ca-central-1)
+ [Seq2Seq(알고리즘)](#seq2seq-ca-central-1)
+ [Spark(알고리즘)](#spark-ca-central-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-ca-central-1)
+ [Tensorflow(DLC)](#tensorflow-ca-central-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-ca-central-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-ca-central-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-ca-central-1)
+ [VW(알고리즘)](#vw-ca-central-1)
+ [XGBoost(알고리즘)](#xgboost-ca-central-1)

## AutoGluon(알고리즘)
<a name="autogluon-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ca-central-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='ca-central-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='ca-central-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 675030665977.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 557239378090.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 557239378090.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 557239378090.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 519511493484.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ca-central-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='ca-central-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='ca-central-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ca-central-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='ca-central-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 536280801234.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='ca-central-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='ca-central-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='ca-central-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ca-central-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ca-central-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='ca-central-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ca-central-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ca-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ca-central-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 446299261295.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 446299261295.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 446299261295.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 446299261295.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 446299261295.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='ca-central-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-ca-central-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ca-central-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.ca-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='ca-central-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='ca-central-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 464438896020.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='ca-central-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='ca-central-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-ca-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ca-central-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 469771592824.dkr.ecr.ca-central-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 341280168497.dkr.ecr.ca-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 캐나다 서부(캘거리)(ca-west-1)용 Docker 레지스트리 경로 및 예시 코드
<a name="ecr-ca-west-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-ca-west-1)
+ [BlazingText(알고리즘)](#blazingtext-ca-west-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-ca-west-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-ca-west-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-ca-west-1)
+ [Hugging Face(알고리즘)](#huggingface-ca-west-1)
+ [IP Insights(알고리즘)](#ipinsights-ca-west-1)
+ [이미지 분류(알고리즘)](#image-classification-ca-west-1)
+ [K-Means(알고리즘)](#kmeans-ca-west-1)
+ [KNN(알고리즘)](#knn-ca-west-1)
+ [Linear Learner(알고리즘)](#linear-learner-ca-west-1)
+ [MXNet(DLC)](#mxnet-ca-west-1)
+ [NTM(알고리즘)](#ntm-ca-west-1)
+ [Object Detection(알고리즘)](#object-detection-ca-west-1)
+ [Object2Vec(알고리즘)](#object2vec-ca-west-1)
+ [PCA(알고리즘)](#pca-ca-west-1)
+ [PyTorch(DLC)](#pytorch-ca-west-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-ca-west-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-ca-west-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-ca-west-1)
+ [Scikit-learn(알고리즘)](#sklearn-ca-west-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-ca-west-1)
+ [Seq2Seq(알고리즘)](#seq2seq-ca-west-1)
+ [Spark(알고리즘)](#spark-ca-west-1)
+ [Tensorflow(DLC)](#tensorflow-ca-west-1)
+ [XGBoost(알고리즘)](#xgboost-ca-west-1)

## AutoGluon(알고리즘)
<a name="autogluon-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='ca-west-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='ca-west-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## K-Means(알고리즘)
<a name="kmeans-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='ca-west-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## NTM(알고리즘)
<a name="ntm-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## Object Detection(알고리즘)
<a name="object-detection-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-ca-west-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='ca-west-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='ca-west-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='ca-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='ca-west-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 000907499111.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 000907499111.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 000907499111.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 000907499111.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 000907499111.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-ca-west-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='ca-west-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 204538143572.dkr.ecr.ca-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## XGBoost(알고리즘)
<a name="xgboost-ca-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='ca-west-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 190319476487.dkr.ecr.ca-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 중국(베이징)의 Docker 레지스트리 경로 및 예제 코드 (cn-north-1)
<a name="ecr-cn-north-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-cn-north-1)
+ [BlazingText(알고리즘)](#blazingtext-cn-north-1)
+ [Chainer(DLC)](#chainer-cn-north-1)
+ [Clarify(알고리즘)](#clarify-cn-north-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-cn-north-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-cn-north-1)
+ [Debugger(알고리즘)](#debugger-cn-north-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-cn-north-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-cn-north-1)
+ [Hugging Face(알고리즘)](#huggingface-cn-north-1)
+ [IP Insights(알고리즘)](#ipinsights-cn-north-1)
+ [이미지 분류(알고리즘)](#image-classification-cn-north-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-cn-north-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-cn-north-1)
+ [K-Means(알고리즘)](#kmeans-cn-north-1)
+ [KNN(알고리즘)](#knn-cn-north-1)
+ [Linear Learner(알고리즘)](#linear-learner-cn-north-1)
+ [MXNet(DLC)](#mxnet-cn-north-1)
+ [MXNet Coach(DLC)](#coach-mxnet-cn-north-1)
+ [모델 모니터(알고리즘)](#model-monitor-cn-north-1)
+ [NTM(알고리즘)](#ntm-cn-north-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-cn-north-1)
+ [Neo MXNet(DLC)](#neo-mxnet-cn-north-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-cn-north-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-cn-north-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-cn-north-1)
+ [객체 감지(알고리즘)](#object-detection-cn-north-1)
+ [Object2Vec(알고리즘)](#object2vec-cn-north-1)
+ [PCA(알고리즘)](#pca-cn-north-1)
+ [PyTorch(DLC)](#pytorch-cn-north-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-cn-north-1)
+ [Scikit-learn(알고리즘)](#sklearn-cn-north-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-cn-north-1)
+ [Seq2Seq(알고리즘)](#seq2seq-cn-north-1)
+ [Spark(알고리즘)](#spark-cn-north-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-cn-north-1)
+ [Tensorflow(DLC)](#tensorflow-cn-north-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-cn-north-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-cn-north-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-cn-north-1)
+ [XGBoost(알고리즘)](#xgboost-cn-north-1)

## AutoGluon(알고리즘)
<a name="autogluon-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='cn-north-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='cn-north-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='cn-north-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 122526803553---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 245909111842---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 245909111842---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 245909111842---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 618459771430---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='cn-north-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='cn-north-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='cn-north-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='cn-north-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='cn-north-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 453000072557---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='cn-north-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='cn-north-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='cn-north-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-cn-north-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='cn-north-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='cn-north-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='cn-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='cn-north-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 671472414489---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 671472414489---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 671472414489---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 671472414489---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 671472414489---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='cn-north-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-cn-north-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='cn-north-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='cn-north-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='cn-north-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 472730292857---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='cn-north-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 422961961927---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-cn-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='cn-north-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 390948362332---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 450853457545---dkr---ecr---cn-north-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 중국(닝샤)용 Docker 레지스트리 경로 및 예제 코드 (cn-northwest-1)
<a name="ecr-cn-northwest-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-cn-northwest-1)
+ [BlazingText(알고리즘)](#blazingtext-cn-northwest-1)
+ [Chainer(DLC)](#chainer-cn-northwest-1)
+ [Clarify(알고리즘)](#clarify-cn-northwest-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-cn-northwest-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-cn-northwest-1)
+ [Debugger(알고리즘)](#debugger-cn-northwest-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-cn-northwest-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-cn-northwest-1)
+ [Hugging Face(알고리즘)](#huggingface-cn-northwest-1)
+ [IP Insights(알고리즘)](#ipinsights-cn-northwest-1)
+ [이미지 분류(알고리즘)](#image-classification-cn-northwest-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-cn-northwest-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-cn-northwest-1)
+ [K-Means(알고리즘)](#kmeans-cn-northwest-1)
+ [KNN(알고리즘)](#knn-cn-northwest-1)
+ [Linear Learner(알고리즘)](#linear-learner-cn-northwest-1)
+ [MXNet(DLC)](#mxnet-cn-northwest-1)
+ [MXNet Coach(DLC)](#coach-mxnet-cn-northwest-1)
+ [모델 모니터(알고리즘)](#model-monitor-cn-northwest-1)
+ [NTM(알고리즘)](#ntm-cn-northwest-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-cn-northwest-1)
+ [Neo MXNet(DLC)](#neo-mxnet-cn-northwest-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-cn-northwest-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-cn-northwest-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-cn-northwest-1)
+ [객체 감지(알고리즘)](#object-detection-cn-northwest-1)
+ [Object2Vec(알고리즘)](#object2vec-cn-northwest-1)
+ [PCA(알고리즘)](#pca-cn-northwest-1)
+ [PyTorch(DLC)](#pytorch-cn-northwest-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-cn-northwest-1)
+ [Scikit-learn(알고리즘)](#sklearn-cn-northwest-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-cn-northwest-1)
+ [Seq2Seq(알고리즘)](#seq2seq-cn-northwest-1)
+ [Spark(알고리즘)](#spark-cn-northwest-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-cn-northwest-1)
+ [Tensorflow(DLC)](#tensorflow-cn-northwest-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-cn-northwest-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-cn-northwest-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-cn-northwest-1)
+ [XGBoost(알고리즘)](#xgboost-cn-northwest-1)

## AutoGluon(알고리즘)
<a name="autogluon-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='cn-northwest-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='cn-northwest-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='cn-northwest-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 122578899357---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249157047649---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 249157047649---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 249157047649---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 658757709296---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='cn-northwest-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='cn-northwest-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='cn-northwest-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='cn-northwest-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='cn-northwest-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 453252182341---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='cn-northwest-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='cn-northwest-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='cn-northwest-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-cn-northwest-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='cn-northwest-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='cn-northwest-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='cn-northwest-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='cn-northwest-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 844356804704---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 844356804704---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 844356804704---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 844356804704---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 844356804704---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='cn-northwest-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-cn-northwest-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='cn-northwest-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 727897471807---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='cn-northwest-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='cn-northwest-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 474822919863---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='cn-northwest-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 423003514399---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-cn-northwest-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='cn-northwest-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 387376663083---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 451049120500---dkr---ecr---cn-northwest-1.amazonaws.com.rproxy.govskope.us.cn/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 유럽(프랑크푸르트)의 Docker 레지스트리 경로 및 예제 코드 (eu-central-1)
<a name="ecr-eu-central-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-central-1)
+ [BlazingText(알고리즘)](#blazingtext-eu-central-1)
+ [Chainer(DLC)](#chainer-eu-central-1)
+ [Clarify(알고리즘)](#clarify-eu-central-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-eu-central-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-eu-central-1)
+ [Debugger(알고리즘)](#debugger-eu-central-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-central-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-central-1)
+ [Hugging Face(알고리즘)](#huggingface-eu-central-1)
+ [IP Insights(알고리즘)](#ipinsights-eu-central-1)
+ [이미지 분류(알고리즘)](#image-classification-eu-central-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-central-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-central-1)
+ [K-Means(알고리즘)](#kmeans-eu-central-1)
+ [KNN(알고리즘)](#knn-eu-central-1)
+ [LDA(알고리즘)](#lda-eu-central-1)
+ [Linear Learner(알고리즘)](#linear-learner-eu-central-1)
+ [MXNet(DLC)](#mxnet-eu-central-1)
+ [MXNet Coach(DLC)](#coach-mxnet-eu-central-1)
+ [모델 모니터(알고리즘)](#model-monitor-eu-central-1)
+ [NTM(알고리즘)](#ntm-eu-central-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-central-1)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-central-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-central-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-central-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-central-1)
+ [객체 감지(알고리즘)](#object-detection-eu-central-1)
+ [Object2Vec(알고리즘)](#object2vec-eu-central-1)
+ [PCA(알고리즘)](#pca-eu-central-1)
+ [PyTorch(DLC)](#pytorch-eu-central-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-eu-central-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-central-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-central-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-eu-central-1)
+ [Scikit-learn(알고리즘)](#sklearn-eu-central-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-central-1)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-central-1)
+ [Spark(알고리즘)](#spark-eu-central-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-eu-central-1)
+ [Tensorflow(DLC)](#tensorflow-eu-central-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-eu-central-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-central-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-eu-central-1)
+ [VW(알고리즘)](#vw-eu-central-1)
+ [XGBoost(알고리즘)](#xgboost-eu-central-1)

## AutoGluon(알고리즘)
<a name="autogluon-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-central-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='eu-central-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-central-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 017069133835.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 024640144536.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 024640144536.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 024640144536.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 482524230118.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 495149712605.dkr.ecr.eu-central-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-central-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-central-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-central-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 353608530281.dkr.ecr.eu-central-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-central-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='eu-central-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 048819808253.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-central-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-central-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-central-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-central-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-central-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 664544806723.dkr.ecr.eu-central-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='eu-central-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-central-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-central-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 906073651304.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 906073651304.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 906073651304.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 906073651304.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 906073651304.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='eu-central-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-central-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-central-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='eu-central-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-central-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 746233611703.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='eu-central-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='eu-central-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-central-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 813361260812.dkr.ecr.eu-central-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 492215442770.dkr.ecr.eu-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 유럽(아일랜드)용 Docker 레지스트리 경로 및 예제 코드 (eu-west-1)
<a name="ecr-eu-west-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-west-1)
+ [BlazingText(알고리즘)](#blazingtext-eu-west-1)
+ [Chainer(DLC)](#chainer-eu-west-1)
+ [Clarify(알고리즘)](#clarify-eu-west-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-eu-west-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-eu-west-1)
+ [Debugger(알고리즘)](#debugger-eu-west-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-west-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-west-1)
+ [Hugging Face(알고리즘)](#huggingface-eu-west-1)
+ [IP Insights(알고리즘)](#ipinsights-eu-west-1)
+ [이미지 분류(알고리즘)](#image-classification-eu-west-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-west-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-west-1)
+ [K-Means(알고리즘)](#kmeans-eu-west-1)
+ [KNN(알고리즘)](#knn-eu-west-1)
+ [LDA(알고리즘)](#lda-eu-west-1)
+ [Linear Learner(알고리즘)](#linear-learner-eu-west-1)
+ [MXNet(DLC)](#mxnet-eu-west-1)
+ [MXNet Coach(DLC)](#coach-mxnet-eu-west-1)
+ [모델 모니터(알고리즘)](#model-monitor-eu-west-1)
+ [NTM(알고리즘)](#ntm-eu-west-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-west-1)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-west-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-west-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-west-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-west-1)
+ [객체 감지(알고리즘)](#object-detection-eu-west-1)
+ [Object2Vec(알고리즘)](#object2vec-eu-west-1)
+ [PCA(알고리즘)](#pca-eu-west-1)
+ [PyTorch(DLC)](#pytorch-eu-west-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-eu-west-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-west-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-west-1)
+ [Ray PyTorch(DLC)](#ray-pytorch-eu-west-1)
+ [Scikit-learn(알고리즘)](#sklearn-eu-west-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-west-1)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-west-1)
+ [Spark(알고리즘)](#spark-eu-west-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-eu-west-1)
+ [Tensorflow(DLC)](#tensorflow-eu-west-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-eu-west-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-west-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-eu-west-1)
+ [VW(알고리즘)](#vw-eu-west-1)
+ [XGBoost(알고리즘)](#xgboost-eu-west-1)

## AutoGluon(알고리즘)
<a name="autogluon-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-west-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='eu-west-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-west-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 131013547314.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 245179582081.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 245179582081.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 245179582081.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 929884845733.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 224300973850.dkr.ecr.eu-west-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-west-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-west-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-west-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 999678624901.dkr.ecr.eu-west-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-west-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='eu-west-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 468650794304.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-west-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-west-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-west-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-west-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-west-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 438346466558.dkr.ecr.eu-west-1.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='eu-west-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-west-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-west-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 571004829621.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 571004829621.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 571004829621.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 571004829621.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 571004829621.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='eu-west-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-west-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-west-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='eu-west-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-west-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 802834080501.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='eu-west-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='eu-west-1',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-west-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 685385470294.dkr.ecr.eu-west-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 141502667606.dkr.ecr.eu-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 유럽(런던)용 Docker 레지스트리 경로 및 예제 코드 (eu-west-2)
<a name="ecr-eu-west-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-west-2)
+ [BlazingText(알고리즘)](#blazingtext-eu-west-2)
+ [Chainer(DLC)](#chainer-eu-west-2)
+ [Clarify(알고리즘)](#clarify-eu-west-2)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-eu-west-2)
+ [Data Wrangler(알고리즘)](#data-wrangler-eu-west-2)
+ [Debugger(알고리즘)](#debugger-eu-west-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-west-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-west-2)
+ [Hugging Face(알고리즘)](#huggingface-eu-west-2)
+ [IP Insights(알고리즘)](#ipinsights-eu-west-2)
+ [이미지 분류(알고리즘)](#image-classification-eu-west-2)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-west-2)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-west-2)
+ [K-Means(알고리즘)](#kmeans-eu-west-2)
+ [KNN(알고리즘)](#knn-eu-west-2)
+ [LDA(알고리즘)](#lda-eu-west-2)
+ [Linear Learner(알고리즘)](#linear-learner-eu-west-2)
+ [MXNet(DLC)](#mxnet-eu-west-2)
+ [MXNet Coach(DLC)](#coach-mxnet-eu-west-2)
+ [모델 모니터(알고리즘)](#model-monitor-eu-west-2)
+ [NTM(알고리즘)](#ntm-eu-west-2)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-west-2)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-west-2)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-west-2)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-west-2)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-west-2)
+ [객체 감지(알고리즘)](#object-detection-eu-west-2)
+ [Object2Vec(알고리즘)](#object2vec-eu-west-2)
+ [PCA(알고리즘)](#pca-eu-west-2)
+ [PyTorch(DLC)](#pytorch-eu-west-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-west-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-west-2)
+ [Ray PyTorch(DLC)](#ray-pytorch-eu-west-2)
+ [Scikit-learn(알고리즘)](#sklearn-eu-west-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-west-2)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-west-2)
+ [Spark(알고리즘)](#spark-eu-west-2)
+ [SparkML Serving(알고리즘)](#sparkml-serving-eu-west-2)
+ [Tensorflow(DLC)](#tensorflow-eu-west-2)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-eu-west-2)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-west-2)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-eu-west-2)
+ [VW(알고리즘)](#vw-eu-west-2)
+ [XGBoost(알고리즘)](#xgboost-eu-west-2)

## AutoGluon(알고리즘)
<a name="autogluon-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-west-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='eu-west-2',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-west-2',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 440796970383.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 894491911112.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 894491911112.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 894491911112.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 250201462417.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-west-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-west-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-west-2',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-west-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='eu-west-2',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749857270468.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-west-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-west-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-west-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-west-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-west-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/randomcutforest:<태그> | 1 | 추론, 훈련 | 

## Ray PyTorch(DLC)
<a name="ray-pytorch-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-pytorch',region='eu-west-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-torch-<태그> | 1.6.0 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-torch-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-west-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-west-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-west-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 836651553127.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 836651553127.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 836651553127.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 836651553127.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 836651553127.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='eu-west-2',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-west-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-west-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='eu-west-2',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-coach-container:coach-1.0.0-tf-<태그> | 1.0.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-west-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 205493899709.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='eu-west-2',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-1.6.0-tf-<태그> | 1.6.0 | 학습 | CPU, GPU | py37 | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.5-tf-<태그> | 0.8.5 | 학습 | CPU, GPU | py36 | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-ray-container:ray-0.8.2-tf-<태그> | 0.8.2 | 학습 | CPU, GPU | py36 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## VW(알고리즘)
<a name="vw-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='vw',region='eu-west-2',version='8.7.0',image_scope='training')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 462105765813.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-rl-vw-container:vw-8.7.0-<태그> | 8.7.0 | 학습 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-west-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-west-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 644912444149.dkr.ecr.eu-west-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 764974769150.dkr.ecr.eu-west-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 유럽(밀라노)용 Docker 레지스트리 경로 및 예제 코드 (eu-south-1)
<a name="ecr-eu-south-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-south-1)
+ [BlazingText(알고리즘)](#blazingtext-eu-south-1)
+ [Chainer(DLC)](#chainer-eu-south-1)
+ [Clarify(알고리즘)](#clarify-eu-south-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-eu-south-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-eu-south-1)
+ [Debugger(알고리즘)](#debugger-eu-south-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-south-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-south-1)
+ [Hugging Face(알고리즘)](#huggingface-eu-south-1)
+ [IP Insights(알고리즘)](#ipinsights-eu-south-1)
+ [이미지 분류(알고리즘)](#image-classification-eu-south-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-south-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-south-1)
+ [K-Means(알고리즘)](#kmeans-eu-south-1)
+ [KNN(알고리즘)](#knn-eu-south-1)
+ [Linear Learner(알고리즘)](#linear-learner-eu-south-1)
+ [MXNet(DLC)](#mxnet-eu-south-1)
+ [MXNet Coach(DLC)](#coach-mxnet-eu-south-1)
+ [모델 모니터(알고리즘)](#model-monitor-eu-south-1)
+ [NTM(알고리즘)](#ntm-eu-south-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-south-1)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-south-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-south-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-south-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-south-1)
+ [객체 감지(알고리즘)](#object-detection-eu-south-1)
+ [Object2Vec(알고리즘)](#object2vec-eu-south-1)
+ [PCA(알고리즘)](#pca-eu-south-1)
+ [PyTorch(DLC)](#pytorch-eu-south-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-south-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-south-1)
+ [Scikit-learn(알고리즘)](#sklearn-eu-south-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-south-1)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-south-1)
+ [Spark(알고리즘)](#spark-eu-south-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-eu-south-1)
+ [Tensorflow(DLC)](#tensorflow-eu-south-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-eu-south-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-south-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-eu-south-1)
+ [XGBoost(알고리즘)](#xgboost-eu-south-1)

## AutoGluon(알고리즘)
<a name="autogluon-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-south-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='eu-south-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-south-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 638885417683.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 488287956546.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 488287956546.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 488287956546.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 563282790590.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-south-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-south-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-south-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-south-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='eu-south-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 933208885752.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-south-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-south-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-south-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-south-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-south-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-south-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-south-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 753923664805.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 753923664805.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 753923664805.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 753923664805.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 753923664805.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='eu-south-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-south-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-south-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 692866216735.dkr.ecr.eu-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='eu-south-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-south-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 966458181534.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='eu-south-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 048378556238.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-south-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 257386234256.dkr.ecr.eu-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 978288397137.dkr.ecr.eu-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 유럽(파리)용 Docker 레지스트리 경로 및 예제 코드 (eu-west-3)
<a name="ecr-eu-west-3"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-west-3)
+ [BlazingText(알고리즘)](#blazingtext-eu-west-3)
+ [Chainer(DLC)](#chainer-eu-west-3)
+ [Clarify(알고리즘)](#clarify-eu-west-3)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-eu-west-3)
+ [Data Wrangler(알고리즘)](#data-wrangler-eu-west-3)
+ [Debugger(알고리즘)](#debugger-eu-west-3)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-west-3)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-west-3)
+ [Hugging Face(알고리즘)](#huggingface-eu-west-3)
+ [IP Insights(알고리즘)](#ipinsights-eu-west-3)
+ [이미지 분류(알고리즘)](#image-classification-eu-west-3)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-west-3)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-west-3)
+ [K-Means(알고리즘)](#kmeans-eu-west-3)
+ [KNN(알고리즘)](#knn-eu-west-3)
+ [Linear Learner(알고리즘)](#linear-learner-eu-west-3)
+ [MXNet(DLC)](#mxnet-eu-west-3)
+ [MXNet Coach(DLC)](#coach-mxnet-eu-west-3)
+ [모델 모니터(알고리즘)](#model-monitor-eu-west-3)
+ [NTM(알고리즘)](#ntm-eu-west-3)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-west-3)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-west-3)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-west-3)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-west-3)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-west-3)
+ [객체 감지(알고리즘)](#object-detection-eu-west-3)
+ [Object2Vec(알고리즘)](#object2vec-eu-west-3)
+ [PCA(알고리즘)](#pca-eu-west-3)
+ [PyTorch(DLC)](#pytorch-eu-west-3)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-eu-west-3)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-west-3)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-west-3)
+ [Scikit-learn(알고리즘)](#sklearn-eu-west-3)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-west-3)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-west-3)
+ [Spark(알고리즘)](#spark-eu-west-3)
+ [SparkML Serving(알고리즘)](#sparkml-serving-eu-west-3)
+ [Tensorflow(DLC)](#tensorflow-eu-west-3)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-eu-west-3)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-west-3)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-eu-west-3)
+ [XGBoost(알고리즘)](#xgboost-eu-west-3)

## AutoGluon(알고리즘)
<a name="autogluon-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-west-3',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='eu-west-3',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-west-3',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 341593696636.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 807237891255.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 807237891255.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 807237891255.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 447278800020.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-west-3',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-west-3',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-west-3',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-west-3',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='eu-west-3',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680080141114.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-west-3',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-west-3',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-west-3',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-west-3"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-west-3',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-west-3',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-west-3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-west-3',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 136845547031.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 136845547031.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 136845547031.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 136845547031.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 136845547031.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='eu-west-3',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-west-3"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-west-3',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-west-3.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='eu-west-3',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-west-3',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 254080097072.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='eu-west-3',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-west-3"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-west-3',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 749696950732.dkr.ecr.eu-west-3.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 659782779980.dkr.ecr.eu-west-3.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# Docker 레지스트리 경로 및 유럽 (스페인) 예제 코드 (eu-south-2)
<a name="ecr-eu-south-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-south-2)
+ [BlazingText(알고리즘)](#blazingtext-eu-south-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-south-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-south-2)
+ [Hugging Face(알고리즘)](#huggingface-eu-south-2)
+ [IP Insights(알고리즘)](#ipinsights-eu-south-2)
+ [이미지 분류(알고리즘)](#image-classification-eu-south-2)
+ [K-Means(알고리즘)](#kmeans-eu-south-2)
+ [KNN(알고리즘)](#knn-eu-south-2)
+ [Linear Learner(알고리즘)](#linear-learner-eu-south-2)
+ [MXNet(DLC)](#mxnet-eu-south-2)
+ [모델 모니터(알고리즘)](#model-monitor-eu-south-2)
+ [NTM(알고리즘)](#ntm-eu-south-2)
+ [Object Detection(알고리즘)](#object-detection-eu-south-2)
+ [Object2Vec(알고리즘)](#object2vec-eu-south-2)
+ [PCA(알고리즘)](#pca-eu-south-2)
+ [PyTorch(DLC)](#pytorch-eu-south-2)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-eu-south-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-south-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-south-2)
+ [Scikit-learn(알고리즘)](#sklearn-eu-south-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-south-2)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-south-2)
+ [Spark(알고리즘)](#spark-eu-south-2)
+ [Tensorflow(DLC)](#tensorflow-eu-south-2)
+ [XGBoost(알고리즘)](#xgboost-eu-south-2)

## AutoGluon(알고리즘)
<a name="autogluon-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-south-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-south-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## K-Means(알고리즘)
<a name="kmeans-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-south-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 437450045455.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## Object Detection(알고리즘)
<a name="object-detection-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-south-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-south-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-south-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-south-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-south-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 833944533722.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-south-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-south-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 503227376785.dkr.ecr.eu-south-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## XGBoost(알고리즘)
<a name="xgboost-eu-south-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-south-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 104374241257.dkr.ecr.eu-south-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 유럽(스톡홀름)용 Docker 레지스트리 경로 및 예제 코드 (eu-north-1)
<a name="ecr-eu-north-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-north-1)
+ [BlazingText(알고리즘)](#blazingtext-eu-north-1)
+ [Chainer(DLC)](#chainer-eu-north-1)
+ [Clarify(알고리즘)](#clarify-eu-north-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-eu-north-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-eu-north-1)
+ [Debugger(알고리즘)](#debugger-eu-north-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-north-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-north-1)
+ [Hugging Face(알고리즘)](#huggingface-eu-north-1)
+ [IP Insights(알고리즘)](#ipinsights-eu-north-1)
+ [이미지 분류(알고리즘)](#image-classification-eu-north-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-north-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-north-1)
+ [K-Means(알고리즘)](#kmeans-eu-north-1)
+ [KNN(알고리즘)](#knn-eu-north-1)
+ [Linear Learner(알고리즘)](#linear-learner-eu-north-1)
+ [MXNet(DLC)](#mxnet-eu-north-1)
+ [MXNet Coach(DLC)](#coach-mxnet-eu-north-1)
+ [모델 모니터(알고리즘)](#model-monitor-eu-north-1)
+ [NTM(알고리즘)](#ntm-eu-north-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-north-1)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-north-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-north-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-north-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-north-1)
+ [객체 감지(알고리즘)](#object-detection-eu-north-1)
+ [Object2Vec(알고리즘)](#object2vec-eu-north-1)
+ [PCA(알고리즘)](#pca-eu-north-1)
+ [PyTorch(DLC)](#pytorch-eu-north-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-north-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-north-1)
+ [Scikit-learn(알고리즘)](#sklearn-eu-north-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-north-1)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-north-1)
+ [Spark(알고리즘)](#spark-eu-north-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-eu-north-1)
+ [Tensorflow(DLC)](#tensorflow-eu-north-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-eu-north-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-north-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-eu-north-1)
+ [XGBoost(알고리즘)](#xgboost-eu-north-1)

## AutoGluon(알고리즘)
<a name="autogluon-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-north-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='eu-north-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-north-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763603941244.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 054986407534.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 054986407534.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 054986407534.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 314864569078.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-north-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-north-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-north-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-north-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='eu-north-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 895015795356.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-north-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-north-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-north-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-north-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-north-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-north-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-north-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-north-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 330188676905.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 330188676905.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 330188676905.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 330188676905.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 330188676905.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='eu-north-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-north-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-north-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.eu-north-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='eu-north-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-north-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 601324751636.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='eu-north-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-north-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-north-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 669576153137.dkr.ecr.eu-north-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 662702820516.dkr.ecr.eu-north-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# Docker 레지스트리 경로 및 유럽 (취리히)의 예제 코드 (eu-central-2)
<a name="ecr-eu-central-2"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-eu-central-2)
+ [BlazingText(알고리즘)](#blazingtext-eu-central-2)
+ [Clarify(알고리즘)](#clarify-eu-central-2)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-eu-central-2)
+ [Factorization Machine(알고리즘)](#factorization-machines-eu-central-2)
+ [Hugging Face(알고리즘)](#huggingface-eu-central-2)
+ [IP Insights(알고리즘)](#ipinsights-eu-central-2)
+ [이미지 분류(알고리즘)](#image-classification-eu-central-2)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-eu-central-2)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-eu-central-2)
+ [K-Means(알고리즘)](#kmeans-eu-central-2)
+ [KNN(알고리즘)](#knn-eu-central-2)
+ [Linear Learner(알고리즘)](#linear-learner-eu-central-2)
+ [MXNet(DLC)](#mxnet-eu-central-2)
+ [모델 모니터(알고리즘)](#model-monitor-eu-central-2)
+ [NTM(알고리즘)](#ntm-eu-central-2)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-eu-central-2)
+ [Neo MXNet(DLC)](#neo-mxnet-eu-central-2)
+ [Neo PyTorch(DLC)](#neo-pytorch-eu-central-2)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-eu-central-2)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-eu-central-2)
+ [객체 감지(알고리즘)](#object-detection-eu-central-2)
+ [Object2Vec(알고리즘)](#object2vec-eu-central-2)
+ [PCA(알고리즘)](#pca-eu-central-2)
+ [PyTorch(DLC)](#pytorch-eu-central-2)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-eu-central-2)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-eu-central-2)
+ [Random Cut Forest(알고리즘)](#randomcutforest-eu-central-2)
+ [Scikit-learn(알고리즘)](#sklearn-eu-central-2)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-eu-central-2)
+ [Seq2Seq(알고리즘)](#seq2seq-eu-central-2)
+ [Spark(알고리즘)](#spark-eu-central-2)
+ [Tensorflow(DLC)](#tensorflow-eu-central-2)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-eu-central-2)
+ [XGBoost(알고리즘)](#xgboost-eu-central-2)

## AutoGluon(알고리즘)
<a name="autogluon-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='eu-central-2',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/blazingtext:<태그> | 1 | 추론, 훈련 | 

## Clarify(알고리즘)
<a name="clarify-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='eu-central-2',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 730335477804.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='eu-central-2',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='eu-central-2',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='eu-central-2',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='eu-central-2',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 590183933784.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='eu-central-2',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='eu-central-2',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='eu-central-2',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-eu-central-2"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='eu-central-2',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.5.1 | eia | CPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference-eia:<태그> | 1.3.1 | eia | CPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='eu-central-2',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='eu-central-2')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='eu-central-2',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 142351485170.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 142351485170.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 142351485170.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 142351485170.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 142351485170.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-eu-central-2"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='eu-central-2',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 380420809688.dkr.ecr.eu-central-2.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='eu-central-2',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 010526262399.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-eu-central-2"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='eu-central-2',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 680994064768.dkr.ecr.eu-central-2.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 이스라엘(텔아비브)(il-central-1)용 Docker 레지스트리 경로 및 예시 코드
<a name="ecr-il-central-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-il-central-1)
+ [BlazingText(알고리즘)](#blazingtext-il-central-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-il-central-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-il-central-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-il-central-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-il-central-1)
+ [Hugging Face(알고리즘)](#huggingface-il-central-1)
+ [IP Insights(알고리즘)](#ipinsights-il-central-1)
+ [이미지 분류(알고리즘)](#image-classification-il-central-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-il-central-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-il-central-1)
+ [K-Means(알고리즘)](#kmeans-il-central-1)
+ [KNN(알고리즘)](#knn-il-central-1)
+ [Linear Learner(알고리즘)](#linear-learner-il-central-1)
+ [MXNet(DLC)](#mxnet-il-central-1)
+ [모델 모니터(알고리즘)](#model-monitor-il-central-1)
+ [NTM(알고리즘)](#ntm-il-central-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-il-central-1)
+ [Neo MXNet(DLC)](#neo-mxnet-il-central-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-il-central-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-il-central-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-il-central-1)
+ [객체 감지(알고리즘)](#object-detection-il-central-1)
+ [Object2Vec(알고리즘)](#object2vec-il-central-1)
+ [PCA(알고리즘)](#pca-il-central-1)
+ [PyTorch(DLC)](#pytorch-il-central-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-il-central-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-il-central-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-il-central-1)
+ [Scikit-learn(알고리즘)](#sklearn-il-central-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-il-central-1)
+ [Seq2Seq(알고리즘)](#seq2seq-il-central-1)
+ [Spark(알고리즘)](#spark-il-central-1)
+ [Tensorflow(DLC)](#tensorflow-il-central-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-il-central-1)
+ [XGBoost(알고리즘)](#xgboost-il-central-1)

## AutoGluon(알고리즘)
<a name="autogluon-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='il-central-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 406833011540.dkr.ecr.il-central-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='il-central-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='il-central-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='il-central-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='il-central-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 843974653677.dkr.ecr.il-central-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='il-central-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='il-central-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='il-central-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-il-central-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='il-central-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='il-central-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='il-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='il-central-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 408426139102.dkr.ecr.il-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 408426139102.dkr.ecr.il-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 408426139102.dkr.ecr.il-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 408426139102.dkr.ecr.il-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 408426139102.dkr.ecr.il-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-il-central-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='il-central-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 780543022126.dkr.ecr.il-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='il-central-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 275950707576.dkr.ecr.il-central-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-il-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='il-central-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 898809789911.dkr.ecr.il-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 멕시코(중부)(mx-central-1)용 Docker 레지스트리 경로 및 예시 코드
<a name="ecr-mx-central-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [PyTorch(DLC)](#pytorch-mx-central-1)
+ [Spark(알고리즘)](#spark-mx-central-1)
+ [Tensorflow(DLC)](#tensorflow-mx-central-1)

## PyTorch(DLC)
<a name="pytorch-mx-central-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='mx-central-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Spark(알고리즘)
<a name="spark-mx-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='mx-central-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 211125459255.dkr.ecr.mx-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 211125459255.dkr.ecr.mx-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 211125459255.dkr.ecr.mx-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 211125459255.dkr.ecr.mx-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 211125459255.dkr.ecr.mx-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-mx-central-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='mx-central-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 637423239942.dkr.ecr.mx-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

# 중동(바레인)용 Docker 레지스트리 경로 및 예제 코드 (me-south-1)
<a name="ecr-me-south-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-me-south-1)
+ [BlazingText(알고리즘)](#blazingtext-me-south-1)
+ [Chainer(DLC)](#chainer-me-south-1)
+ [Clarify(알고리즘)](#clarify-me-south-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-me-south-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-me-south-1)
+ [Debugger(알고리즘)](#debugger-me-south-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-me-south-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-me-south-1)
+ [Hugging Face(알고리즘)](#huggingface-me-south-1)
+ [IP Insights(알고리즘)](#ipinsights-me-south-1)
+ [이미지 분류(알고리즘)](#image-classification-me-south-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-me-south-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-me-south-1)
+ [K-Means(알고리즘)](#kmeans-me-south-1)
+ [KNN(알고리즘)](#knn-me-south-1)
+ [Linear Learner(알고리즘)](#linear-learner-me-south-1)
+ [MXNet(DLC)](#mxnet-me-south-1)
+ [MXNet Coach(DLC)](#coach-mxnet-me-south-1)
+ [모델 모니터(알고리즘)](#model-monitor-me-south-1)
+ [NTM(알고리즘)](#ntm-me-south-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-me-south-1)
+ [Neo MXNet(DLC)](#neo-mxnet-me-south-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-me-south-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-me-south-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-me-south-1)
+ [객체 감지(알고리즘)](#object-detection-me-south-1)
+ [Object2Vec(알고리즘)](#object2vec-me-south-1)
+ [PCA(알고리즘)](#pca-me-south-1)
+ [PyTorch(DLC)](#pytorch-me-south-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-me-south-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-me-south-1)
+ [Scikit-learn(알고리즘)](#sklearn-me-south-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-me-south-1)
+ [Seq2Seq(알고리즘)](#seq2seq-me-south-1)
+ [Spark(알고리즘)](#spark-me-south-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-me-south-1)
+ [Tensorflow(DLC)](#tensorflow-me-south-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-me-south-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-me-south-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-me-south-1)
+ [XGBoost(알고리즘)](#xgboost-me-south-1)

## AutoGluon(알고리즘)
<a name="autogluon-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='me-south-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='me-south-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='me-south-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 835444307964.dkr.ecr.me-south-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 376037874950.dkr.ecr.me-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 376037874950.dkr.ecr.me-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 376037874950.dkr.ecr.me-south-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 986000313247.dkr.ecr.me-south-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='me-south-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='me-south-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='me-south-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='me-south-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='me-south-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 607024016150.dkr.ecr.me-south-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='me-south-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='me-south-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='me-south-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-me-south-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='me-south-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='me-south-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='me-south-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='me-south-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 750251592176.dkr.ecr.me-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 750251592176.dkr.ecr.me-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 750251592176.dkr.ecr.me-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 750251592176.dkr.ecr.me-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 750251592176.dkr.ecr.me-south-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='me-south-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-me-south-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='me-south-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 217643126080.dkr.ecr.me-south-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='me-south-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='me-south-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 836785723513.dkr.ecr.me-south-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='me-south-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 724002660598.dkr.ecr.me-south-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-me-south-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='me-south-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 249704162688.dkr.ecr.me-south-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 801668240914.dkr.ecr.me-south-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 중동(UAE) (me-central-1)의 Docker 레지스트리 경로 및 예제 코드
<a name="ecr-me-central-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-me-central-1)
+ [BlazingText(알고리즘)](#blazingtext-me-central-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-me-central-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-me-central-1)
+ [Hugging Face(알고리즘)](#huggingface-me-central-1)
+ [IP Insights(알고리즘)](#ipinsights-me-central-1)
+ [이미지 분류(알고리즘)](#image-classification-me-central-1)
+ [K-Means(알고리즘)](#kmeans-me-central-1)
+ [KNN(알고리즘)](#knn-me-central-1)
+ [Linear Learner(알고리즘)](#linear-learner-me-central-1)
+ [MXNet(DLC)](#mxnet-me-central-1)
+ [모델 모니터(알고리즘)](#model-monitor-me-central-1)
+ [NTM(알고리즘)](#ntm-me-central-1)
+ [Object Detection(알고리즘)](#object-detection-me-central-1)
+ [Object2Vec(알고리즘)](#object2vec-me-central-1)
+ [PCA(알고리즘)](#pca-me-central-1)
+ [PyTorch(DLC)](#pytorch-me-central-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-me-central-1)
+ [Scikit-learn(알고리즘)](#sklearn-me-central-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-me-central-1)
+ [Seq2Seq(알고리즘)](#seq2seq-me-central-1)
+ [Spark(알고리즘)](#spark-me-central-1)
+ [Tensorflow(DLC)](#tensorflow-me-central-1)
+ [XGBoost(알고리즘)](#xgboost-me-central-1)

## AutoGluon(알고리즘)
<a name="autogluon-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='me-central-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='me-central-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## K-Means(알고리즘)
<a name="kmeans-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='me-central-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 588750061953.dkr.ecr.me-central-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## Object Detection(알고리즘)
<a name="object-detection-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-me-central-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='me-central-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='me-central-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='me-central-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='me-central-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 395420993607.dkr.ecr.me-central-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-me-central-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='me-central-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 914824155844.dkr.ecr.me-central-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## XGBoost(알고리즘)
<a name="xgboost-me-central-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='me-central-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 272398656194.dkr.ecr.me-central-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# 남아메리카(상파울루)용 Docker 레지스트리 경로 및 예제 코드 (sa-east-1)
<a name="ecr-sa-east-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-sa-east-1)
+ [BlazingText(알고리즘)](#blazingtext-sa-east-1)
+ [Chainer(DLC)](#chainer-sa-east-1)
+ [Clarify(알고리즘)](#clarify-sa-east-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-sa-east-1)
+ [Data Wrangler(알고리즘)](#data-wrangler-sa-east-1)
+ [Debugger(알고리즘)](#debugger-sa-east-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-sa-east-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-sa-east-1)
+ [Hugging Face(알고리즘)](#huggingface-sa-east-1)
+ [IP Insights(알고리즘)](#ipinsights-sa-east-1)
+ [이미지 분류(알고리즘)](#image-classification-sa-east-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-sa-east-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-sa-east-1)
+ [K-Means(알고리즘)](#kmeans-sa-east-1)
+ [KNN(알고리즘)](#knn-sa-east-1)
+ [Linear Learner(알고리즘)](#linear-learner-sa-east-1)
+ [MXNet(DLC)](#mxnet-sa-east-1)
+ [MXNet Coach(DLC)](#coach-mxnet-sa-east-1)
+ [모델 모니터(알고리즘)](#model-monitor-sa-east-1)
+ [NTM(알고리즘)](#ntm-sa-east-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-sa-east-1)
+ [Neo MXNet(DLC)](#neo-mxnet-sa-east-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-sa-east-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-sa-east-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-sa-east-1)
+ [객체 감지(알고리즘)](#object-detection-sa-east-1)
+ [Object2Vec(알고리즘)](#object2vec-sa-east-1)
+ [PCA(알고리즘)](#pca-sa-east-1)
+ [PyTorch(DLC)](#pytorch-sa-east-1)
+ [PyTorch Neuron(DLC)](#pytorch-neuron-sa-east-1)
+ [PyTorch Training Compiler(DLC)](#pytorch-training-compiler-sa-east-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-sa-east-1)
+ [Scikit-learn(알고리즘)](#sklearn-sa-east-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-sa-east-1)
+ [Seq2Seq(알고리즘)](#seq2seq-sa-east-1)
+ [Spark(알고리즘)](#spark-sa-east-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-sa-east-1)
+ [Tensorflow(DLC)](#tensorflow-sa-east-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-sa-east-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-sa-east-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-sa-east-1)
+ [XGBoost(알고리즘)](#xgboost-sa-east-1)

## AutoGluon(알고리즘)
<a name="autogluon-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='sa-east-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='sa-east-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='sa-east-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 520018980103.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Data Wrangler(알고리즘)
<a name="data-wrangler-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='data-wrangler',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 424196993095.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 3.x | 처리 중 | 
| 424196993095.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 2.x | 처리 중 | 
| 424196993095.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-data-wrangler-container:<태그> | 1.x | 처리 중 | 

## Debugger(알고리즘)
<a name="debugger-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 818342061345.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='sa-east-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='sa-east-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='sa-east-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='sa-east-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='sa-east-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## 모델 모니터(알고리즘)
<a name="model-monitor-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='model-monitor',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 539772159869.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-model-monitor-analyzer:<태그> |  | 모니터링 | 

## NTM(알고리즘)
<a name="ntm-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='sa-east-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='sa-east-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='sa-east-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-sa-east-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='sa-east-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## PyTorch Neuron(DLC)
<a name="pytorch-neuron-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-neuron',region='us-west-2', image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-training-neuron:<태그> | 1.11.0 | 학습 | TRN | py38 | 

## PyTorch Training Compiler(DLC)
<a name="pytorch-training-compiler-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch-training-compiler',region='us-west-2', version='py38')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.13.1 | 학습 | GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/pytorch-trcomp-training:<태그> | 1.12.0 | 학습 | GPU | py38 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='sa-east-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='sa-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='sa-east-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 737130764395.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 737130764395.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 737130764395.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 737130764395.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 737130764395.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='sa-east-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-sa-east-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='sa-east-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 763104351884.dkr.ecr.sa-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='sa-east-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='sa-east-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 756306329178.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='sa-east-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 520713654638.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-sa-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='sa-east-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 855470959533.dkr.ecr.sa-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 737474898029.dkr.ecr.sa-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# AWS GovCloud용 Docker 레지스트리 경로 및 예제 코드 (미국 동부) (us-gov-east-1)
<a name="ecr-us-gov-east-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-us-gov-east-1)
+ [BlazingText(알고리즘)](#blazingtext-us-gov-east-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-us-gov-east-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-us-gov-east-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-us-gov-east-1)
+ [Hugging Face(알고리즘)](#huggingface-us-gov-east-1)
+ [IP Insights(알고리즘)](#ipinsights-us-gov-east-1)
+ [이미지 분류(알고리즘)](#image-classification-us-gov-east-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-us-gov-east-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-us-gov-east-1)
+ [K-Means(알고리즘)](#kmeans-us-gov-east-1)
+ [KNN(알고리즘)](#knn-us-gov-east-1)
+ [Linear Learner(알고리즘)](#linear-learner-us-gov-east-1)
+ [MXNet(DLC)](#mxnet-us-gov-east-1)
+ [NTM(알고리즘)](#ntm-us-gov-east-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-us-gov-east-1)
+ [Neo MXNet(DLC)](#neo-mxnet-us-gov-east-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-us-gov-east-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-us-gov-east-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-us-gov-east-1)
+ [객체 감지(알고리즘)](#object-detection-us-gov-east-1)
+ [Object2Vec(알고리즘)](#object2vec-us-gov-east-1)
+ [PCA(알고리즘)](#pca-us-gov-east-1)
+ [PyTorch(DLC)](#pytorch-us-gov-east-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-us-gov-east-1)
+ [Scikit-learn(알고리즘)](#sklearn-us-gov-east-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-us-gov-east-1)
+ [Seq2Seq(알고리즘)](#seq2seq-us-gov-east-1)
+ [Spark(알고리즘)](#spark-us-gov-east-1)
+ [Tensorflow(DLC)](#tensorflow-us-gov-east-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-us-gov-east-1)
+ [XGBoost(알고리즘)](#xgboost-us-gov-east-1)

## AutoGluon(알고리즘)
<a name="autogluon-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='us-gov-east-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='us-gov-east-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='us-gov-east-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='us-gov-east-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='us-gov-east-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 

## NTM(알고리즘)
<a name="ntm-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='us-gov-east-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='us-gov-east-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='us-gov-east-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-us-gov-east-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='us-gov-east-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='us-gov-east-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='us-gov-east-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='us-gov-east-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 260923028637.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 260923028637.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 260923028637.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 260923028637.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 260923028637.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## Tensorflow(DLC)
<a name="tensorflow-us-gov-east-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='us-gov-east-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 446045086412.dkr.ecr.us-gov-east-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='us-gov-east-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 227234621604.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-us-gov-east-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='us-gov-east-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 237065988967.dkr.ecr.us-gov-east-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 | 

# AWS GovCloud용 Docker 레지스트리 경로 및 예제 코드 (미국-서부) (us-gov-west-1)
<a name="ecr-us-gov-west-1"></a>

다음 항목에는 Amazon SageMaker AI에서 제공하는 이 AWS 리전의 각 알고리즘 및 딥 러닝 컨테이너에 대한 파라미터가 나열되어 있습니다.

**Topics**
+ [AutoGluon(알고리즘)](#autogluon-us-gov-west-1)
+ [BlazingText(알고리즘)](#blazingtext-us-gov-west-1)
+ [Chainer(DLC)](#chainer-us-gov-west-1)
+ [Clarify(알고리즘)](#clarify-us-gov-west-1)
+ [DJL DeepSpeed(알고리즘)](#djl-deepspeed-us-gov-west-1)
+ [Debugger(알고리즘)](#debugger-us-gov-west-1)
+ [DeepAR Forecasting(알고리즘)](#forecasting-deepar-us-gov-west-1)
+ [Factorization Machine(알고리즘)](#factorization-machines-us-gov-west-1)
+ [Hugging Face(알고리즘)](#huggingface-us-gov-west-1)
+ [IP Insights(알고리즘)](#ipinsights-us-gov-west-1)
+ [이미지 분류(알고리즘)](#image-classification-us-gov-west-1)
+ [Inferentia MXNet(DLC)](#inferentia-mxnet-us-gov-west-1)
+ [Inferentia PyTorch(DLC)](#inferentia-pytorch-us-gov-west-1)
+ [K-Means(알고리즘)](#kmeans-us-gov-west-1)
+ [KNN(알고리즘)](#knn-us-gov-west-1)
+ [LDA(알고리즘)](#lda-us-gov-west-1)
+ [Linear Learner(알고리즘)](#linear-learner-us-gov-west-1)
+ [MXNet(DLC)](#mxnet-us-gov-west-1)
+ [MXNet Coach(DLC)](#coach-mxnet-us-gov-west-1)
+ [NTM(알고리즘)](#ntm-us-gov-west-1)
+ [네오 이미지 분류(알고리즘)](#image-classification-neo-us-gov-west-1)
+ [Neo MXNet(DLC)](#neo-mxnet-us-gov-west-1)
+ [Neo PyTorch(DLC)](#neo-pytorch-us-gov-west-1)
+ [Neo Tensorflow(DLC)](#neo-tensorflow-us-gov-west-1)
+ [Neo XGBoost(알고리즘)](#xgboost-neo-us-gov-west-1)
+ [객체 감지(알고리즘)](#object-detection-us-gov-west-1)
+ [Object2Vec(알고리즘)](#object2vec-us-gov-west-1)
+ [PCA(알고리즘)](#pca-us-gov-west-1)
+ [PyTorch(DLC)](#pytorch-us-gov-west-1)
+ [Random Cut Forest(알고리즘)](#randomcutforest-us-gov-west-1)
+ [Scikit-learn(알고리즘)](#sklearn-us-gov-west-1)
+ [의미 체계 분할(알고리즘)](#semantic-segmentation-us-gov-west-1)
+ [Seq2Seq(알고리즘)](#seq2seq-us-gov-west-1)
+ [Spark(알고리즘)](#spark-us-gov-west-1)
+ [SparkML Serving(알고리즘)](#sparkml-serving-us-gov-west-1)
+ [Tensorflow(DLC)](#tensorflow-us-gov-west-1)
+ [Tensorflow Coach(DLC)](#coach-tensorflow-us-gov-west-1)
+ [Tensorflow Inferentia(DLC)](#inferentia-tensorflow-us-gov-west-1)
+ [Tensorflow Ray(DLC)](#ray-tensorflow-us-gov-west-1)
+ [XGBoost(알고리즘)](#xgboost-us-gov-west-1)

## AutoGluon(알고리즘)
<a name="autogluon-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='autogluon',region='us-gov-west-1',image_scope='inference',version='0.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 1.3.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 1.3.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 1.2.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 1.2.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.1 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 1.1.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 1.1.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 1.0.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 1.0.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.8.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.8.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.7.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.7.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.6.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.6.1 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.5.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.5.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.3 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.3 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.4.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.4.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-training:<태그> | 0.3.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/autogluon-inference:<태그> | 0.3.1 | 추론 | 

## BlazingText(알고리즘)
<a name="blazingtext-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='blazingtext',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/blazingtext:<태그> | 1 | 훈련, 추론 | 

## Chainer(DLC)
<a name="chainer-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='chainer',region='us-gov-west-1',version='5.0.0',py_version='py3',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-chainer:<태그> | 5.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-chainer:<태그> | 4.1.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-chainer:<태그> | 4.0.0 | 훈련, 추론 | CPU, GPU | py2, py3 | 

## Clarify(알고리즘)
<a name="clarify-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='clarify',region='us-gov-west-1',version='1.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 598674086554.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-clarify-processing:<태그> | 1.0 | 처리 중 | 

## DJL DeepSpeed(알고리즘)
<a name="djl-deepspeed-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='djl-deepspeed', region='us-west-2',py_version='py3',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.27.0-deepspeed0.12.6-cu121-<tag> | 0.27.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.26.0-deepspeed0.12.6-cu121-<tag> | 0.26.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.25.0-deepspeed0.11.0-cu118-<tag> | 0.25.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.24.0-deepspeed0.10.0-cu118-<tag> | 0.24.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.23.0-deepspeed0.9.5-cu118-<tag> | 0.23.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.22.1-deepspeed0.9.2-cu118-<tag> | 0.22.1 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.21.0-deepspeed0.8.3-cu117-<태그> | 0.21.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.20.0-deepspeed0.7.5-cu116-<태그> | 0.20.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/djl-inference:0.19.0-deepspeed0.7.3-cu113-<태그> | 0.19.0 | 추론 | 

## Debugger(알고리즘)
<a name="debugger-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='debugger',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 515509971035.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-debugger-rules:<태그> | 최신 | 디버거 | 

## DeepAR Forecasting(알고리즘)
<a name="forecasting-deepar-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='forecasting-deepar',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/forecasting-deepar:<태그> | 1 | 훈련, 추론 | 

## Factorization Machine(알고리즘)
<a name="factorization-machines-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='factorization-machines',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/factorization-machines:<태그> | 1 | 훈련, 추론 | 

## Hugging Face(알고리즘)
<a name="huggingface-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='huggingface',region='us-gov-west-1',version='4.4.2',image_scope='training',base_framework_version='tensorflow2.4.1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.49.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.49.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.48.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.48.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.46.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.37.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.36.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.28.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.28.1 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.26.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.26.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.26.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.17.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.17.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.17.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.17.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.12.3 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.12.3 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.12.3 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.12.3 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.11.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.11.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.11.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.11.0 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.10.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.10.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.10.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.10.2 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.6.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.6.1 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-inference:<태그> | 4.6.1 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-inference:<태그> | 4.6.1 | 추론 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.5.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.5.0 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-pytorch-training:<태그> | 4.4.2 | 학습 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/huggingface-tensorflow-training:<태그> | 4.4.2 | 학습 | 

## IP Insights(알고리즘)
<a name="ipinsights-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ipinsights',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/ipinsights:<태그> | 1 | 훈련, 추론 | 

## 이미지 분류(알고리즘)
<a name="image-classification-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/image-classification:<태그> | 1 | 훈련, 추론 | 

## Inferentia MXNet(DLC)
<a name="inferentia-mxnet-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-mxnet',region='us-gov-west-1',version='1.5.1',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.8 | 추론 | inf | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-mxnet:<태그> | 1.5.1 | 추론 | inf | py3 | 

## Inferentia PyTorch(DLC)
<a name="inferentia-pytorch-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-pytorch',region='us-gov-west-1',version='1.9',py_version='py3')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.9 | 추론 | inf | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.8 | 추론 | inf | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-pytorch:<태그> | 1.7 | 추론 | inf | py3 | 

## K-Means(알고리즘)
<a name="kmeans-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='kmeans',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/kmeans:<태그> | 1 | 훈련, 추론 | 

## KNN(알고리즘)
<a name="knn-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='knn',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/knn:<태그> | 1 | 훈련, 추론 | 

## LDA(알고리즘)
<a name="lda-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='lda',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/lda:<태그> | 1 | 훈련, 추론 | 

## Linear Learner(알고리즘)
<a name="linear-learner-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='linear-learner',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/linear-learner:<태그> | 1 | 훈련, 추론 | 

## MXNet(DLC)
<a name="mxnet-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='mxnet',region='us-gov-west-1',version='1.4.1',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-training:<태그> | 1.7.0 | 학습 | CPU, GPU | py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference:<태그> | 1.7.0 | 추론 | CPU, GPU | py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.7.0 | eia | CPU | py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.5.1 | eia | CPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-training:<태그> | 1.4.1 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference:<태그> | 1.4.1 | 추론 | CPU, GPU | py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/mxnet-inference-eia:<태그> | 1.4.1 | eia | CPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet-serving:<태그> | 1.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet-serving-eia:<태그> | 1.4.0 | eia | CPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.3.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet-eia:<태그> | 1.3.0 | eia | CPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.2.1 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-mxnet:<태그> | 0.12.1 | 추론 | CPU, GPU | py2, py3 | 

## MXNet Coach(DLC)
<a name="coach-mxnet-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-mxnet',region='us-gov-west-1',version='0.11',py_version='py3',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-mxnet:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 

## NTM(알고리즘)
<a name="ntm-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ntm',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/ntm:<태그> | 1 | 훈련, 추론 | 

## 네오 이미지 분류(알고리즘)
<a name="image-classification-neo-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='image-classification-neo',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/image-classification-neo:<태그> | 최신 | 추론 | 

## Neo MXNet(DLC)
<a name="neo-mxnet-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-mxnet',region='us-gov-west-1',version='1.8',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-mxnet:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 

## Neo PyTorch(DLC)
<a name="neo-pytorch-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-pytorch',region='us-gov-west-1',version='1.6',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 2.0 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.13 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.12 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.8 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.7 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.6 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.5 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-pytorch:<태그> | 1.4 | 추론 | CPU, GPU | py3 | 

## Neo Tensorflow(DLC)
<a name="neo-tensorflow-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='neo-tensorflow',region='us-gov-west-1',version='1.15.3',py_version='py3',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 2.9.2 | 추론 | CPU, GPU | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-inference-tensorflow:<태그> | 1.15.3 | 추론 | CPU, GPU | py3 | 

## Neo XGBoost(알고리즘)
<a name="xgboost-neo-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost-neo',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/xgboost-neo:<태그> | 최신 | 추론 | 

## 객체 감지(알고리즘)
<a name="object-detection-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object-detection',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/object-detection:<태그> | 1 | 훈련, 추론 | 

## Object2Vec(알고리즘)
<a name="object2vec-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='object2vec',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/object2vec:<태그> | 1 | 훈련, 추론 | 

## PCA(알고리즘)
<a name="pca-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pca',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/pca:<태그> | 1 | 훈련, 추론 | 

## PyTorch(DLC)
<a name="pytorch-us-gov-west-1"></a>

지원되는 PyTorch 버전과 지원되지 않는 PyTorch 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='pytorch',region='us-gov-west-1',version='1.8.0',py_version='py3',image_scope='inference', instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py312 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | py312 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py312 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.4.0 | 추론 | CPU, GPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.4.0 | inference\$1graviton | CPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.4.0 | 학습 | CPU, GPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.3.0 | inference\$1graviton | CPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py311 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.2.1 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.1.0 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.1 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 2.0.0 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.13.1 | 추론 | CPU, GPU | py39 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py39 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.1 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference-graviton:<태그> | 1.12.1 | inference\$1graviton | CPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.1 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.12.0 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.12.0 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.11.0 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.11.0 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.2 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.2 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.10.0 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.10.0 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.1 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.1 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.9.0 | 추론 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.9.0 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.1 | 추론 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.1 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.8.0 | 추론 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.8.0 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.7.1 | 추론 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.7.1 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.6.0 | 추론 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.6.0 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.5.0 | 추론 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.5.0 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.4.0 | 추론 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.4.0 | 학습 | CPU, GPU | py2, py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.3.1 | 추론 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.3.1 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-inference:<태그> | 1.2.0 | 추론 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/pytorch-training:<태그> | 1.2.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 1.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 추론 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-pytorch:<태그> | 0.4.0 | 학습 | CPU, GPU | py2, py3 | 

## Random Cut Forest(알고리즘)
<a name="randomcutforest-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='randomcutforest',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/randomcutforest:<태그> | 1 | 훈련, 추론 | 

## Scikit-learn(알고리즘)
<a name="sklearn-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sklearn',region='us-gov-west-1',version='0.23-1',image_scope='inference')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.2-1 | 1.2.1 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 1.0-1 | 1.0.2 | inference\$1graviton | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.23-1 | 0.23.2 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-scikit-learn:<태그> | 0.20.0 | 0.20.0 | 학습 | 

## 의미 체계 분할(알고리즘)
<a name="semantic-segmentation-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='semantic-segmentation',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/semantic-segmentation:<태그> | 1 | 훈련, 추론 | 

## Seq2Seq(알고리즘)
<a name="seq2seq-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='seq2seq',region='us-gov-west-1')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/seq2seq:<태그> | 1 | 추론, 훈련 | 

## Spark(알고리즘)
<a name="spark-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='spark',region='us-gov-west-1',version='3.0',image_scope='processing')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 271483468897.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.3 | 처리 중 | 
| 271483468897.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.2 | 처리 중 | 
| 271483468897.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.1 | 처리 중 | 
| 271483468897.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 3.0 | 처리 중 | 
| 271483468897.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-spark-processing:<태그> | 2.4 | 처리 중 | 

## SparkML Serving(알고리즘)
<a name="sparkml-serving-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='sparkml-serving',region='us-gov-west-1',version='2.4')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 3.3 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.4 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-sparkml-serving:<태그> | 2.2 | 추론 | 

## Tensorflow(DLC)
<a name="tensorflow-us-gov-west-1"></a>

지원되는 TensorFlow 버전과 지원되지 않는 TensorFlow 버전에 대한 자세한 내용은 *AWS 딥 러닝 컨테이너 개발자 안내서*의 [프레임워크 지원 정책 표](https://docs.aws.amazon.com/deep-learning-containers/latest/devguide/dlc-framework-support-policy.html)를 참조하세요.

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='tensorflow',region='us-gov-west-1',version='1.12.0',image_scope='inference',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.19.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.19.0 | 학습 | CPU, GPU | py312 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.18.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.18.0 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.16.2 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.16.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.16.1 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.14.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.14.1 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.14.1 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.13.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.13.0 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.13.0 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.12.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.12.1 | inference\$1graviton | CPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.12.0 | 학습 | CPU, GPU | py310 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.11.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.11.0 | 학습 | CPU, GPU | py39 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.10.1 | 학습 | CPU, GPU | py39 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.10.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.3 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.9.2 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.9.2 | 학습 | CPU, GPU | py39 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-graviton:<태그> | 2.9.1 | inference\$1graviton | CPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.4 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.8.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.8.0 | 학습 | CPU, GPU | py39 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.7.1 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.7.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.3 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.3 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.2 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.6.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.6.0 | 학습 | CPU, GPU | py38 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.5.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.1 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.5.0 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.3 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.3 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.4.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.4.1 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.2 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.2 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.1 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.3.0 | eia | CPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.3.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.3.0 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.2 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.2 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.1 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.2.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.2.0 | 학습 | CPU, GPU | py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.3 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.3 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.2 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.2 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.1 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.1.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.1.0 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.4 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.4 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.3 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.3 | 학습 | CPU, GPU | py3, py36 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.2 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.2 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.1 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.1 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 2.0.0 | eia | CPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 2.0.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 2.0.0 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.5 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.5 | 학습 | CPU, GPU | py3, py36, py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.4 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.4 | 학습 | CPU, GPU | py3, py36, py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.3 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.3 | 학습 | CPU, GPU | py2, py3, py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.2 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.2 | 학습 | CPU, GPU | py2, py3, py37 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.15.0 | eia | CPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.15.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.15.0 | 학습 | CPU, GPU | py2, py3 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference-eia:<태그> | 1.14.0 | eia | CPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.14.0 | 추론 | CPU, GPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.14.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.13.1 | 학습 | CPU, GPU | py2 | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-training:<태그> | 1.13.1 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.13.0 | eia | CPU | - | 
| 442386744353.dkr.ecr.us-gov-west-1.amazonaws.com/tensorflow-inference:<태그> | 1.13.0 | 추론 | CPU, GPU | - | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.12.0 | eia | CPU | - | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.12.0 | 추론 | CPU, GPU | - | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.12.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-serving-eia:<태그> | 1.11.0 | eia | CPU | - | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-serving:<태그> | 1.11.0 | 추론 | CPU, GPU | - | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-scriptmode:<태그> | 1.11.0 | 학습 | CPU, GPU | py2, py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow-eia:<태그> | 1.10.0 | eia | CPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.10.0 | 학습 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.9.0 | 학습 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.8.0 | 학습 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.7.0 | 학습 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.6.0 | 학습 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.5.0 | 학습 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 추론 | CPU, GPU | py2 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-tensorflow:<태그> | 1.4.1 | 학습 | CPU, GPU | py2 | 

## Tensorflow Coach(DLC)
<a name="coach-tensorflow-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='coach-tensorflow',region='us-gov-west-1',version='1.0.0',image_scope='training',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.1-<태그> | 0.11.1 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11.0-<태그> | 0.11.0 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.11-<태그> | 0.11 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10.1-<태그> | 0.10.1 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:coach0.10-<태그> | 0.10 | 학습 | CPU, GPU | py3 | 

## Tensorflow Inferentia(DLC)
<a name="inferentia-tensorflow-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='inferentia-tensorflow',region='us-gov-west-1',version='1.15.0',instance_type='ml.inf1.6xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 2.5.2 | 추론 | inf | py3 | 
| 263933020539.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-neo-tensorflow:<태그> | 1.15.0 | 추론 | inf | py3 | 

## Tensorflow Ray(DLC)
<a name="ray-tensorflow-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='ray-tensorflow',region='us-gov-west-1',version='0.8.5',instance_type='ml.c5.4xlarge')
```


| 레지스트리 경로 | 버전 | 작업 유형(이미지 범위) | 프로세서 유형 | Python 버전 | 
| --- | --- | --- | --- | --- | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6.5-<태그> | 0.6.5 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.6-<태그> | 0.6 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5.3-<태그> | 0.5.3 | 학습 | CPU, GPU | py3 | 
| 246785580436.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-rl-tensorflow:ray0.5-<태그> | 0.5 | 학습 | CPU, GPU | py3 | 

## XGBoost(알고리즘)
<a name="xgboost-us-gov-west-1"></a>

다음 SageMaker AI Python SDK 예시에서는 특정 레지스트리 경로를 검색하는 방법을 보여줍니다.

```
from sagemaker import image_uris
image_uris.retrieve(framework='xgboost',region='us-gov-west-1',version='1.5-1')
```


| 레지스트리 경로 | 버전 | 패키지 버전 | 작업 유형(이미지 범위) | 
| --- | --- | --- | --- | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.7-1 | 1.7.4 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.5-1 | 1.5.2 | inference\$1graviton | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.3-1 | 1.3.3 | inference\$1graviton | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-2 | 1.2.0 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.2-1 | 1.2.0 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 1.0-1 | 1.0.0 | 학습 | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 추론 | 
| 226302683700.dkr.ecr.us-gov-west-1.amazonaws.com/xgboost:<태그> | 1 | 0.72 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-2 | 0.90 | 학습 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 추론 | 
| 414596584902.dkr.ecr.us-gov-west-1.amazonaws.com/sagemaker-xgboost:<태그> | 0.90-1 | 0.90 | 학습 |