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

# 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 |