经过测试的模型 - Amazon SageMaker

本文属于机器翻译版本。若本译文内容与英语原文存在差异，则一律以英文原文为准。

经过测试的模型

以下可折叠部分提供有关经过 Amazon SageMaker Neo 团队测试的机器学习模型的信息。展开可折叠部分，根据您的框架去查看模型是否经过测试。

注意

这不是可以使用 Neo 编译的模型的完整列表。

参见支持的框架和 SageMaker Neo 支持的运算符，了解是否可以使用 SageMaker Neo 编译模型。

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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_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

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

X86_Linux

X86_Windows

densenet121

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

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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

模型

ARMV8

ARM马里

Ambarella CV22

Ambarella CV25

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

X86_Linux

X86_Windows

densenet121

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

模型

ARMV8

ARM马里

Ambarella CV22

Ambarella CV25

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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

ResNet152v2

X

X

X

ResNet50

X

X

X

X

X

X

ResNet50V2

X

X

X

X

X

X

X

VGG16

X

X

X

X

Xception

X

X

X

X

X

X

X
TensorFlow-Lite (FP32)

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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)

模型

ARMV8

ARM马里

Ambarella CV22

Nvidia

Panorama

TI TDA4VM

高通 QCS6 03

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