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Modelos probados
Las siguientes secciones plegables proporcionan información sobre los modelos de machine learning 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 y Operadores compatibles con SageMaker AI Neo
Modelos |
ARM V8 |
ARM Mali |
Ambarella CV22 |
Nvidia |
Panorama |
A TDA4VM |
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 |
Modelos |
ARM V8 |
ARM Mali |
Ambarella CV22 |
Nvidia |
Panorama |
A TDA4VM |
Qualcomm QCS603 |
X86_Linux |
X86_Windows |
|---|---|---|---|---|---|---|---|---|---|
AlexNet |
X |
||||||||
Densenet 121 |
X |
||||||||
Densenet 201 |
X |
X |
X |
X |
X |
X |
X |
X |
|
Google Net |
X |
X |
X |
X |
X |
X |
X |
||
Inception v3 |
X |
X |
X |
X |
X |
||||
MobileNet 0.75 |
X |
X |
X |
X |
X |
X |
|||
MobileNet 1.0 |
X |
X |
X |
X |
X |
X |
X |
||
MobileNet V2_0.5 |
X |
X |
X |
X |
X |
X |
|||
MobileNet V2_1.0 |
X |
X |
X |
X |
X |
X |
X |
X |
X |
MobileNet V3_Large |
X |
X | X |
X |
X |
X |
X |
X |
X |
MobileNetV3_Small |
X |
X |
X |
X |
X |
X |
X |
X |
X |
Resest 50 |
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 |
|
Resnext 101_32x4D |
|||||||||
Resnext50_32x4D |
X |
X |
X |
X |
X |
X |
|||
Senet_154 |
X |
X |
X |
X |
X |
||||
SE_Resnext50_32x4D |
X |
X |
X |
X |
X | X |
X |
||
SqueezeNet 1.0 |
X |
X |
X |
X |
X |
X |
X |
||
SqueezeNet 1.1 |
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 |
Modelos |
ARM V8 |
ARM Mali |
Ambarella CV22 |
Nvidia |
Panorama |
A TDA4VM |
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 |
Modelos |
ARM V8 |
ARM Mali |
Ambarella CV22 |
Nvidia |
Panorama |
A TDA4VM |
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 |
Modelos |
ARM V8 |
ARM Mali |
Ambarella CV22 |
Ambarella CV25 |
Nvidia |
Panorama |
A TDA4VM |
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 |