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# Modèles testés
<a name="neo-supported-edge-tested-models"></a>

Les sections démontables suivantes fournissent des informations sur les modèles d'apprentissage automatique testés par l'équipe Amazon SageMaker Neo. Développez la section réductible en fonction de votre cadre pour vérifier si un modèle a été testé.

**Note**  
Ceci n’est pas une liste complète de modèles qui peuvent être compilés avec Neo.

Consultez [Cadres pris en charge](neo-supported-devices-edge-frameworks.md) et [SageMaker AI Neo Supported Operators](https://aws.amazon.com/releasenotes/sagemaker-neo-supported-frameworks-and-operators/) pour savoir si vous pouvez compiler votre modèle avec SageMaker Neo.

## DarkNet
<a name="collapsible-section-01"></a>


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| AlexNet |  |  |  |  |  |  |  |  |  | 
| Resnet50 | X | X |  | X | X | X |  | X | X | 
| YOLOv2 |  |  |  | X | X | X |  | X | X | 
| YOLOv2\_tiny | X | X |  | X | X | X |  | X | X | 
| YOLOv3\_416 |  |  |  | X | X | X |  | X | X | 
| YOLOv3\_tiny | X | X |  | X | X | X |  | X | X | 

## MXNet
<a name="collapsible-section-02"></a>


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| AlexNet |  |  | X |  |  |  |  |  |  | 
| Densenet121 |  |  | X |  |  |  |  |  |  | 
| DenseNet201 | X | X | X | X | X | X |  | X | X | 
| GoogLeNet | X | X |  | X | X | X |  | X | X | 
| Inceptionv3 |  |  |  | X | X | X |  | X | X | 
| MobileNet0.75 | X | X |  | X | X | X |  |  | X | 
| MobileNet1.0 | X | X | X | X | X | X |  |  | X | 
| MobileNetV2\_0,5 | X | X |  | X | X | X |  |  | X | 
| MobileNetV2\_1.0 | X | X | X | X | X | X | X | X | X | 
| MobileNetV3\_Large | X | X | X | X | X | X | X | X | X | 
| MobileNetV3\_Petit | X | X | X | X | X | X | X | X | X | 
| ResNeSt50 |  |  |  | X | X |  |  | X | X | 
| ResNet18\_v1 | X | X | X | X | X | X |  |  | X | 
| ResNet18\_v2 | X | X |  | X | X | X |  |  | X | 
| ResNet50\_v1 | X | X | X | X | X | X |  | X | X | 
| ResNet50\_v2 | X | X | X | X | X | X |  | X | X | 
| ResNext101\_32x4d |  |  |  |  |  |  |  |  |  | 
| ResNext50 x 32 x 4 | X |  | X | X | X |  |  | X | X | 
| SENet\_154 |  |  |  | X | X | X |  | X | X | 
| SE\_ 50 x 32 x 4 ResNext | X | X |  | X | X | X |  | X | X | 
| SqueezeNet1.0 | X | X | X | X | X | X |  |  | X | 
| SqueezeNet1.1 | X | X | X | X | X | X |  | X | X | 
| VGG11 | X | X | X | X | X |  |  | X | X | 
| Xception | X | X | X | X | X | X |  | X | X | 
| darknet53 | X | X |  | X | X | X |  | X | X | 
| resnet18\_v1b\_0.89 | X | X |  | X | X | X |  |  | X | 
| resnet50\_v1d\_0.11 | X | X |  | X | X | X |  |  | X | 
| resnet50\_v1d\_0.86 | X | X | X | X | X | X |  | X | X | 
| ssd\_512\_mobilenet1.0\_coco | X |  | X | X | X | X |  | X | X | 
| ssd\_512\_mobilenet1.0\_voc | X |  | X | X | X | X |  | X | X | 
| ssd\_resnet50\_v1 | X |  | X | X | X |  |  | X | X | 
| yolo3\_darknet53\_coco | X |  |  | X | X |  |  | X | X | 
| yolo3\_mobilenet1.0\_coco | X | X |  | X | X | X |  | X | X | 
| deeplab\_resnet50 |  |  | X |  |  |  |  |  |  | 

## Keras
<a name="collapsible-section-03"></a>


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| denseet121 | X | X | X | X | X | X |  | X | X | 
| densenet201 | X | X | X | X | X | X |  |  | X | 
| inception\_v3 | X | X |  | X | X | X |  | X | X | 
| mobilenet\_v1 | X | X | X | X | X | X |  | X | X | 
| mobilenet\_v2 | X | X | X | X | X | X |  | X | X | 
| resnet152\_v1 |  |  |  | X | X |  |  |  | X | 
| resnet152\_v2 |  |  |  | X | X |  |  |  | X | 
| resnet50\_v1 | X | X | X | X | X |  |  | X | X | 
| resnet50\_v2 | X | X | X | X | X | X |  | X | X | 
| vgg16 |  |  | X | X | X |  |  | X | X | 

## ONNX
<a name="collapsible-section-04"></a>


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| AlexNet |  |  | X |  |  |  |  |  |  | 
| mobilenetv2-1.0 | X | X | X | X | X | X |  | X | X | 
| resnet18v1 | X |  |  | X | X |  |  |  | X | 
| resnet18v2 | X |  |  | X | X |  |  |  | X | 
| resnet50v1 | X |  | X | X | X |  |  | X | X | 
| resnet50v2 | X |  | X | X | X |  |  | X | X | 
| resnet152v1 |  |  |  | X | X | X |  |  | X | 
| resnet152v2 |  |  |  | X | X | X |  |  | X | 
| squeezenet1.1 | X |  | X | X | X | X |  | X | X | 
| vgg19 |  |  | X |  |  |  |  |  | X | 

## PyTorch (FP32)
<a name="collapsible-section-05"></a>


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Ambarella CV25 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| denseet121 | X | X | X | X | X | X | X |  | X | X | 
| inception\_v3 |  | X |  |  | X | X | X |  | X | X | 
| resnet152 |  |  |  |  | X | X | X |  |  | X | 
| resnet18 | X | X |  |  | X | X | X |  |  | X | 
| resnet50 | X | X | X | X | X | X |  |  | X | X | 
| squeezenet1.0 | X | X |  |  | X | X | X |  |  | X | 
| squeezenet1.1 | X | X | X | X | X | X | X |  | X | X | 
| yolov4 |  |  |  |  | X | X |  |  |  |  | 
| yolov5 |  |  |  | X | X | X |  |  |  |  | 
| fasterrcnn\_resnet50\_fpn |  |  |  |  | X | X |  |  |  |  | 
| maskrcnn\_resnet50\_fpn |  |  |  |  | X | X |  |  |  |  | 

## TensorFlow
<a name="collapsible-section-06"></a>

------
#### [ TensorFlow ]


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Ambarella CV25 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| densenet201 | X | X | X | X | X | X | X |  | X | X | 
| inception\_v3 | X | X | X |  | X | X | X |  | X | X | 
| mobilenet100\_v1 | X | X | X |  | X | X | X |  |  | X | 
| mobilenet100\_v2.0 | X | X | X |  | X | X | X |  | X | X | 
| mobilenet130\_v2 | X | X |  |  | X | X | X |  |  | X | 
| mobilenet140\_v2 | X | X | X |  | X | X | X |  | X | X | 
| resnet50\_v1.5 | X | X |  |  | X | X | X |  | X | X | 
| resnet50\_v2 | X | X | X | X | X | X | X |  | X | X | 
| squeezenet | X | X | X | X | X | X | X |  | X | X | 
| mask\_rcnn\_inception\_resnet\_v2 |  |  |  |  | X |  |  |  |  |  | 
| ssd\_mobilenet\_v2 |  |  |  |  | X | X |  |  |  |  | 
| faster\_rcnn\_resnet50\_lowproposals |  |  |  |  | X |  |  |  |  |  | 
| rfcn\_resnet101 |  |  |  |  | X |  |  |  |  |  | 

------
#### [ TensorFlow.Keras ]


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| DenseNet121 | X | X |  | X | X | X |  | X | X | 
| DenseNet201 | X | X |  | X | X | X |  |  | X | 
| Inceptionv3 | X | X |  | X | X | X |  | X | X | 
| MobileNet | X | X |  | X | X | X |  | X | X | 
| MobileNetv2 | X | X |  | X | X | X |  | X | X | 
| NASNetLarge |  |  |  | X | X |  |  | X | X | 
| NASNetMobile | X | X |  | X | X | X |  | X | X | 
| ResNet101 |  |  |  | X | X | X |  |  | X | 
| ResNet101V2 |  |  |  | X | X | X |  |  | X | 
| ResNet152 |  |  |  | X | X |  |  |  | X | 
| ResNet152 v2 |  |  |  | X | X |  |  |  | X | 
| ResNet50 | X | X |  | X | X |  |  | X | X | 
| ResNet50 V2 | X | X |  | X | X | X |  | X | X | 
| VGG16 |  |  |  | X | X |  |  | X | X | 
| Xception | X | X |  | X | X | X |  | X | X | 

------

## TensorFlow-Lite
<a name="collapsible-section-07"></a>

------
#### [ TensorFlow-Lite (FP32) ]


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | i.MX 8M Plus | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| densenet\_2018\_04\_27 | X |  |  | X | X | X |  |  | X |  | 
| inception\_resnet\_v2\_2018\_04\_27 |  |  |  | X | X | X |  |  | X |  | 
| inception\_v3\_2018\_04\_27 |  |  |  | X | X | X |  |  | X | X | 
| inception\_v4\_2018\_04\_27 |  |  |  | X | X | X |  |  | X | X | 
| mnasnet\_0.5\_224\_09\_07\_2018 | X |  |  | X | X | X |  |  | X |  | 
| mnasnet\_1.0\_224\_09\_07\_2018 | X |  |  | X | X | X |  |  | X |  | 
| mnasnet\_1.3\_224\_09\_07\_2018 | X |  |  | X | X | X |  |  | X |  | 
| mobilenet\_v1\_0.25\_128 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_0.25\_224 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_0.5\_128 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_0.5\_224 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_0.75\_128 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_0.75\_224 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_1.0\_128 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v1\_1.0\_192 | X |  |  | X | X | X |  |  | X | X | 
| mobilenet\_v2\_1.0\_224 | X |  |  | X | X | X |  |  | X | X | 
| resnet\_v2\_101 |  |  |  | X | X | X |  |  | X |  | 
| squeezenet\_2018\_04\_27 | X |  |  | X | X | X |  |  | X |  | 

------
#### [ TensorFlow-Lite (INT8) ]


| Modèles   | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | TI TDA4VM | Qualcomm QCS603 | X86\_Linux | X86\_Windows | i.MX 8M Plus | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| inception\_v1 |  |  |  |  |  |  | X |  |  | X | 
| inception\_v2 |  |  |  |  |  |  | X |  |  | X | 
| inception\_v3 | X |  |  |  |  | X | X |  | X | X | 
| inception\_v4\_299 | X |  |  |  |  | X | X |  | X | X | 
| mobilenet\_v1\_0.25\_128 | X |  |  |  |  | X |  |  | X | X | 
| mobilenet\_v1\_0.25\_224 | X |  |  |  |  | X |  |  | X | X | 
| mobilenet\_v1\_0.5\_128 | X |  |  |  |  | X |  |  | X | X | 
| mobilenet\_v1\_0.5\_224 | X |  |  |  |  | X |  |  | X | X | 
| mobilenet\_v1\_0.75\_128 | X |  |  |  |  | X |  |  | X | X | 
| mobilenet\_v1\_0.75\_224 | X |  |  |  |  | X | X |  | X | X | 
| mobilenet\_v1\_1.0\_128 | X |  |  |  |  | X |  |  | X | X | 
| mobilenet\_v1\_1.0\_224 | X |  |  |  |  | X | X |  | X | X | 
| mobilenet\_v2\_1.0\_224 | X |  |  |  |  | X | X |  | X | X | 
| deeplab-v3\_513 |  |  |  |  |  |  | X |  |  |  | 

------