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# Modelos probados
<a name="neo-supported-edge-tested-models"></a>

Las siguientes secciones plegables proporcionan información sobre los modelos de aprendizaje automático que probó el equipo de Amazon SageMaker Neo. Amplíe la sección plegable en función de su estructura para comprobar si se ha probado un modelo.

**nota**  
Esta no es una lista exhaustiva de los modelos que se pueden compilar con Neo.

Consulte [Marcos admitidos](neo-supported-devices-edge-frameworks.md) a [los operadores compatibles con SageMaker AI Neo](https://aws.amazon.com/releasenotes/sagemaker-neo-supported-frameworks-and-operators/) para averiguar si puede compilar su modelo con SageMaker Neo.

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


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| AlexNet |  |  |  |  |  |  |  |  |  | 
| Resnet 50 | 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>


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| AlexNet |  |  | X |  |  |  |  |  |  | 
| Densenet 121 |  |  | X |  |  |  |  |  |  | 
| DenseNet201 | X | X | X | X | X | X |  | X | X | 
| GoogLeNet | X | X |  | X | X | X |  | X | X | 
| Inception v3 |  |  |  | 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\_Small | 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\_32x4d | X |  | X | X | X |  |  | X | X | 
| SENet\_154 |  |  |  | X | X | X |  | X | X | 
| SE\_ 50\_32x4d 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>


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| densenet 121 | X | X | X | X | X | X |  | X | X | 
| densenet 201 | 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>


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| AlexNet |  |  | X |  |  |  |  |  |  | 
| mobilenetv2-1.0 | X | X | X | X | X | X |  | X | X | 
| resnet 18 contra 1 | X |  |  | X | X |  |  |  | X | 
| resnet18 v2 | X |  |  | X | X |  |  |  | X | 
| resnet50 v1 | X |  | X | X | X |  |  | X | X | 
| resnet50 v2 | X |  | X | X | X |  |  | X | X | 
| resnet 152 v1 |  |  |  | X | X | X |  |  | X | 
| resnet 152 v2 |  |  |  | X | X | X |  |  | X | 
| squeezenet 1.1 | X |  | X | X | X | X |  | X | X | 
| vgg19 |  |  | X |  |  |  |  |  | X | 

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


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Ambarella CV25 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| densenet 121 | 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 | 
| squeezenet 1.0 | X | X |  |  | X | X | X |  |  | X | 
| squeezenet 1.1 | 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 ]


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Ambarella CV25 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| densenet 201 | 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 | 
| mobilenet 130\_v2 | X | X |  |  | X | X | X |  |  | X | 
| mobilenet 140\_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 ]


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | Qualcomm QCS603 | X86\_Linux | X86\_Windows | 
| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | 
| DenseNet121 | X | X |  | X | X | X |  | X | X | 
| DenseNet201 | X | X |  | X | X | X |  |  | X | 
| Inception v3 | X | X |  | X | X | X |  | X | X | 
| MobileNet | X | X |  | X | X | X |  | X | X | 
| MobileNetv2. | X | X |  | X | X | X |  | X | X | 
| NASNetGrande |  |  |  | X | X |  |  | X | X | 
| NASNetMóvil | X | X |  | X | X | X |  | X | X | 
| ResNet101 |  |  |  | X | X | X |  |  | X | 
| ResNet101 V2 |  |  |  | X | X | X |  |  | X | 
| ResNet152 |  |  |  | X | X |  |  |  | X | 
| ResNet152 contra 2 |  |  |  | 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) ]


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | 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) ]


| Modelos | ARM V8 | ARM Mali | Ambarella CV22 | Nvidia | Panorama | A VM TDA4 | 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 |  |  |  | 

------