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[v1.x] Add ONNX model support matrix #20230

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[v1.x] Add ONNX model support matrix #20230

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f4805f1
add model support matrix
Apr 29, 2021
a7077e2
add gluon links
Apr 30, 2021
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171 changes: 171 additions & 0 deletions python/mxnet/onnx/README.md
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Expand Up @@ -181,5 +181,176 @@ If you are a user of earlier MXNet versions and do not want to upgrade MXNet, yo
|zeros_like|1.7 1.8 |

### GluonCV Pretrained Model Support Matrix
|Image Classification|
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Shall we link to GluonCV pretained model page here? wdyt
Sorry about the late review, we can also do this in another pr and merge this one

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Sure, added link to both gluoncv and gluonnlp

|:-|
|alexnet|
|cifar_resnet20_v1|
|cifar_resnet56_v1|
|cifar_resnet110_v1|
|cifar_resnet20_v2|
|cifar_resnet56_v2|
|cifar_resnet110_v2|
|cifar_wideresnet16_10|
|cifar_wideresnet28_10|
|cifar_wideresnet40_8|
|cifar_resnext29_16x64d|
|darknet53|
|densenet121|
|densenet161|
|densenet169|
|densenet201|
|googlenet|
|mobilenet1.0|
|mobilenet0.75|
|mobilenet0.5|
|mobilenet0.25|
|mobilenetv2_1.0|
|mobilenetv2_0.75|
|mobilenetv2_0.5|
|mobilenetv2_0.25|
|mobilenetv3_large|
|mobilenetv3_small|
|resnest14|
|resnest26|
|resnest50|
|resnest101|
|resnest200|
|resnest269|
|resnet18_v1|
|resnet18_v1b_0.89|
|resnet18_v2|
|resnet34_v1|
|resnet34_v2|
|resnet50_v1|
|resnet50_v1d_0.86|
|resnet50_v1d_0.48|
|resnet50_v1d_0.37|
|resnet50_v1d_0.11|
|resnet50_v2|
|resnet101_v1|
|resnet101_v1d_0.76|
|resnet101_v1d_0.73|
|resnet101_v2|
|resnet152_v1|
|resnet152_v2|
|resnext50_32x4d|
|resnext101_32x4d|
|resnext101_64x4d|
|senet_154|
|se_resnext101_32x4d|
|se_resnext101_64x4d|
|se_resnext50_32x4d|
|squeezenet1.0|
|squeezenet1.1|
|vgg11|
|vgg11_bn|
|vgg13|
|vgg13_bn|
|vgg16|
|vgg16_bn|
|vgg19|
|vgg19_bn|
|xception|
|inceptionv3|

|Object Detection|
|:-|
|center_net_resnet18_v1b_voc|
|center_net_resnet50_v1b_voc|
|center_net_resnet101_v1b_voc|
|center_net_resnet18_v1b_coco|
|center_net_resnet50_v1b_coco|
|center_net_resnet101_v1b_coco|
|ssd_300_vgg16_atrous_voc|
|ssd_512_vgg16_atrous_voc|
|ssd_512_resnet50_v1_voc|
|ssd_512_mobilenet1.0_voc|
|faster_rcnn_resnet50_v1b_voc|
|yolo3_darknet53_voc|
|yolo3_mobilenet1.0_voc|
|ssd_300_vgg16_atrous_coco|
|ssd_512_vgg16_atrous_coco|
|ssd_300_resnet34_v1b_coco|
|ssd_512_resnet50_v1_coco|
|ssd_512_mobilenet1.0_coco|
|faster_rcnn_resnet50_v1b_coco|
|faster_rcnn_resnet101_v1d_coco|
|yolo3_darknet53_coco|
|yolo3_mobilenet1.0_coco|
|faster_rcnn_fpn_resnet50_v1b_coco|
|faster_rcnn_fpn_resnet101_v1d_coco|
|mask_rcnn_fpn_resnet18_v1b_coco|
|mask_rcnn_resnet18_v1b_coco|
|mask_rcnn_resnet50_v1b_coco|
|mask_rcnn_resnet101_v1d_coco|
|mask_rcnn_fpn_resnet50_v1b_coco|
|mask_rcnn_fpn_resnet101_v1d_coco|

|Image Segmentation|
|:-|
|fcn_resnet50_ade|
|fcn_resnet101_ade|
|deeplab_resnet50_ade|
|deeplab_resnet101_ade|
|deeplab_resnest50_ade|
|deeplab_resnest101_ade|
|deeplab_resnest269_ade|
|fcn_resnet101_coco|
|deeplab_resnet101_coco|
|fcn_resnet101_voc|
|deeplab_resnet101_voc|
|deeplab_resnet152_voc|
|deeplab_resnet50_citys|
|deeplab_resnet101_citys|
|deeplab_v3b_plus_wideresnet_citys|
|danet_resnet50_citys|
|danet_resnet101_citys|

|Pose Estimation|
|:-|
|simple_pose_resnet18_v1b|
|simple_pose_resnet50_v1b|
|simple_pose_resnet50_v1d|
|simple_pose_resnet101_v1b|
|simple_pose_resnet101_v1d|
|simple_pose_resnet152_v1b|
|simple_pose_resnet152_v1d|
|alpha_pose_resnet101_v1b_coco|
|mobile_pose_resnet18_v1b|
|mobile_pose_resnet50_v1b|
|mobile_pose_mobilenet1.0|
|mobile_pose_mobilenetv2_1.0|
|mobile_pose_mobilenetv3_large|
|mobile_pose_mobilenetv3_small|

|Action Estimation|
|:-|
|inceptionv1_kinetics400|
|resnet18_v1b_kinetics400|
|resnet34_v1b_kinetics400|
|resnet50_v1b_kinetics400|
|resnet101_v1b_kinetics400|
|resnet152_v1b_kinetics400|
|resnet50_v1b_hmdb51|
|resnet50_v1b_sthsthv2|
|vgg16_ucf101|
|inceptionv3_kinetics400|
|inceptionv3_ucf101|

### GluonNLP Pretrained Model Support Matrix
|NLP Models|
|:-|
|awd_lstm_lm_600|
|awd_lstm_lm_1150|
|bert_12_768_12|
|bert_24_1024_16|
|distilbert_6_768_12|
|ernie_12_768_12|
|gpt2_117m|
|gpt2_345m|
|roberta_12_768_12|
|roberta_24_1024_16|
|standard_lstm_lm_200|
|standard_lstm_lm_650|
|standard_lstm_lm_1500|
|transformer_en_de_512|
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