From 552cbf0f7286eba89a5da2bcbd65ec240e45d6c8 Mon Sep 17 00:00:00 2001 From: HIT-cwh <2892770585@qq.com> Date: Mon, 13 Mar 2023 18:17:45 +0800 Subject: [PATCH] add metafiles and fix readme --- configs/distill/mmcls/dist/metafile.yml | 34 ++++++++++++++++++ configs/distill/mmdet/mgd/metafile.yml | 32 +++++++++++++++++ configs/nas/mmcls/autoformer/metafile.yml | 27 ++++++++++++++ configs/nas/mmcls/bignas/README.md | 10 +++--- configs/nas/mmcls/bignas/metafile.yml | 43 +++++++++++++++++++++++ configs/nas/mmcls/dsnas/README.md | 6 ++-- configs/nas/mmcls/dsnas/metafile.yml | 27 ++++++++++++++ configs/nas/mmcls/onceforall/README.md | 6 ++-- configs/nas/mmcls/onceforall/metafile.yml | 41 +++++++++++++++++++++ 9 files changed, 215 insertions(+), 11 deletions(-) create mode 100644 configs/distill/mmcls/dist/metafile.yml create mode 100644 configs/distill/mmdet/mgd/metafile.yml create mode 100644 configs/nas/mmcls/autoformer/metafile.yml create mode 100644 configs/nas/mmcls/bignas/metafile.yml create mode 100644 configs/nas/mmcls/dsnas/metafile.yml create mode 100644 configs/nas/mmcls/onceforall/metafile.yml diff --git a/configs/distill/mmcls/dist/metafile.yml b/configs/distill/mmcls/dist/metafile.yml new file mode 100644 index 000000000..e7fc686ae --- /dev/null +++ b/configs/distill/mmcls/dist/metafile.yml @@ -0,0 +1,34 @@ +Collections: + - Name: DIST + Metadata: + Training Data: + - ImageNet-1k + Paper: + URL: https://arxiv.org/abs/2205.10536 + Title: Knowledge Distillation from A Stronger Teacher + README: configs/distill/mmcls/dist/README.md + +Models: + - Name: dist_logits_resnet34_resnet18_8xb32_in1k + In Collection: DIST + Metadata: + Location: logits + Student: + Config: mmcls::resnet/resnet18_8xb32_in1k.py + Weights: https://download.openmmlab.com/mmclassification/v0/resnet/resnet18_8xb32_in1k_20210831-fbbb1da6.pth + Metrics: + Top 1 Accuracy: 69.90 + Top 5 Accuracy: 89.43 + Teacher: + Config: mmcls::resnet/resnet34_8xb32_in1k.py + Weights: https://download.openmmlab.com/mmclassification/v0/resnet/resnet34_8xb32_in1k_20210831-f257d4e6.pth + Metrics: + Top 1 Accuracy: 73.62 + Top 5 Accuracy: 91.59 + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 71.61 + Config: configs/distill/mmcls/dist/dist_logits_resnet34_resnet18_8xb32_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/distillation/dist_logits_resnet34_resnet18_8xb32_in1k.pth diff --git a/configs/distill/mmdet/mgd/metafile.yml b/configs/distill/mmdet/mgd/metafile.yml new file mode 100644 index 000000000..923f3d1e3 --- /dev/null +++ b/configs/distill/mmdet/mgd/metafile.yml @@ -0,0 +1,32 @@ +Collections: + - Name: MGD + Metadata: + Training Data: + - COCO + Paper: + URL: https://arxiv.org/abs/2205.01529 + Title: Masked Generative Distillation + README: configs/distill/mmdet/mgd/README.md + +Models: + - Name: mgd_fpn_retina_x101_retina_r50_2x_coco + In Collection: MGD + Metadata: + Location: FPN + Student: + Metrics: + box AP: 37.4 + Config: mmdet::retinanet/retinanet_r50_fpn_2x_coco.py + Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_r50_fpn_2x_coco/retinanet_r50_fpn_2x_coco_20200131-fdb43119.pth + Teacher: + Metrics: + box AP: 41.0 + Config: mmdet::retinanet/retinanet_x101-64x4d_fpn_1x_coco.py + Weights: https://download.openmmlab.com/mmdetection/v2.0/retinanet/retinanet_x101_64x4d_fpn_1x_coco/retinanet_x101_64x4d_fpn_1x_coco_20200130-366f5af1.pth + Results: + - Task: Object Detection + Dataset: COCO + Metrics: + box AP: 41.0 + Config: configs/distill/mmdet/mgd/mgd_fpn_retina_x101_retina_r50_2x_coco.py + Weights: https://download.openmmlab.com/mmrazor/v1/mgd/mgd_fpn_retina_x101_retina_r50_2x_coco_20221209_191847-87141529.pth diff --git a/configs/nas/mmcls/autoformer/metafile.yml b/configs/nas/mmcls/autoformer/metafile.yml new file mode 100644 index 000000000..33d97057f --- /dev/null +++ b/configs/nas/mmcls/autoformer/metafile.yml @@ -0,0 +1,27 @@ +Collections: + - Name: AUTOFORMER + Metadata: + Training Data: + - ImageNet-1k + Paper: + URL: https://arxiv.org/abs/2107.00651 + Title: Searching Transformers for Visual Recognition + README: configs/nas/mmcls/autoformer/README.md + Code: + URL: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/mmrazor/models/algorithms/nas/autoformer.py + Version: V1.0.0rc2 + +Models: + - Name: autoformer_subnet_8xb256_in1k + In Collection: AUTOFORMER + Metadata: + Flops(G): 10.57 + Params(M): 54.319 + Subnet: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/autoformer/AUTOFORMER_SUBNET_B.yaml + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 82.47 + Config: configs/nas/mmcls/autoformer/autoformer_subnet_8xb256_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/autoformer/autoformer_supernet_32xb256_in1k_20220919_110144-c658ce8f.pth diff --git a/configs/nas/mmcls/bignas/README.md b/configs/nas/mmcls/bignas/README.md index d6b117f11..e4036f4e1 100644 --- a/configs/nas/mmcls/bignas/README.md +++ b/configs/nas/mmcls/bignas/README.md @@ -37,11 +37,11 @@ CUDA_VISIBLE_DEVICES=0 PORT=29500 ./tools/dist_test.sh \ ## Results and models -| Dataset | Supernet | Subnet | Params(M) | Flops(G) | Top-1 | Config | Download | Remarks | -| :------: | :------------------: | :-------------------------------------------------------------------------------------------------------------------------------: | :--------------------: | :------------------: | :---------------------: | :-------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------: | -| ImageNet | AttentiveMobileNetV3 | [search space](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/_base_/nas_backbones/attentive_mobilenetv3_supernet.py) | 8.854(min) / 23.3(max) | 212(min) / 1944(max) | 77.19(min) / 81.42(max) | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/bignas/attentive_mobilenet_supernet_32xb64_in1k.py) | [model\*](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_supernet_32xb64_in1k_flops-2G_acc-81.72_20221229_200440-954772a3.pth) | [log](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_supernet_32xb64_in1k_20221227_175800-bcf94eaa.json) (`sandwich rule`) | -| ImageNet | AttentiveMobileNetV3 | [AttentiveNAS-A0\*](https://download.openmmlab.com/mmrazor/v1/bignas/ATTENTIVE_SUBNET_A0.yaml) | 8.854 | 212 | 77.19 | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/bignas/attentive_mobilenet_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_subnet_8xb256_in1k_flops-0.21G_acc-77.19_20221229_200440-282a1f70.pth) | Converted from the repo | -| ImageNet | AttentiveMobileNetV3 | [AttentiveNAS-A6\*](https://download.openmmlab.com/mmrazor/v1/bignas/ATTENTIVE_SUBNET_A6.yaml) | 15.594 | 927 | 80.81 | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/bignas/attentive_mobilenet_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_subnet_8xb256_in1k_flops-0.93G_acc-80.81_20221229_200440-73d92cc6.pth) | Converted from the repo | +| Dataset | Supernet | Subnet | Params(M) | Flops(G) | Top-1 | Config | Download | Remarks | +| :------: | :------------------: | :-------------------------------------------------------------------------------------------------------------------------------: | :--------------------: | :----------------------: | :---------------------: | :-------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------------------------------------------------------: | +| ImageNet | AttentiveMobileNetV3 | [search space](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/_base_/nas_backbones/attentive_mobilenetv3_supernet.py) | 8.854(min) / 23.3(max) | 0.212(min) / 0.1944(max) | 77.19(min) / 81.42(max) | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/bignas/attentive_mobilenet_supernet_32xb64_in1k.py) | [model\*](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_supernet_32xb64_in1k_flops-2G_acc-81.72_20221229_200440-954772a3.pth) | [log](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_supernet_32xb64_in1k_20221227_175800-bcf94eaa.json) (`sandwich rule`) | +| ImageNet | AttentiveMobileNetV3 | [AttentiveNAS-A0\*](https://download.openmmlab.com/mmrazor/v1/bignas/ATTENTIVE_SUBNET_A0.yaml) | 8.854 | 0.212 | 77.19 | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/bignas/attentive_mobilenet_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_subnet_8xb256_in1k_flops-0.21G_acc-77.19_20221229_200440-282a1f70.pth) | Converted from the repo | +| ImageNet | AttentiveMobileNetV3 | [AttentiveNAS-A6\*](https://download.openmmlab.com/mmrazor/v1/bignas/ATTENTIVE_SUBNET_A6.yaml) | 15.594 | 0.927 | 80.81 | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/bignas/attentive_mobilenet_subnet_8xb256_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_subnet_8xb256_in1k_flops-0.93G_acc-80.81_20221229_200440-73d92cc6.pth) | Converted from the repo | *Models with * are converted from the [official repo](https://github.com/facebookresearch/AttentiveNAS). The config files of these models are only for inference. We support training the supernet by `sandwich rule`, which is different from `rejection sampling` in [official repo](https://github.com/facebookresearch/AttentiveNAS), and welcome you to contribute your reproduction results.* diff --git a/configs/nas/mmcls/bignas/metafile.yml b/configs/nas/mmcls/bignas/metafile.yml new file mode 100644 index 000000000..0f5aad199 --- /dev/null +++ b/configs/nas/mmcls/bignas/metafile.yml @@ -0,0 +1,43 @@ +Collections: + - Name: BigNAS + Metadata: + Training Data: + - ImageNet-1k + Paper: + URL: https://arxiv.org/abs/2003.11142 + Title: BigNAS Scaling Up Neural Architecture Search with Big Single-Stage Models + README: configs/nas/mmcls/bignas/README.md + Code: + URL: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/mmrazor/models/algorithms/nas/bignas.py + Version: V1.0.0rc2 + +Models: + - Name: attentive_mobilenet_subnet_8xb256_in1k_flops-927M + In Collection: BigNAS + Metadata: + Flops(G): 0.927 + Params(M): 15.594 + Supernet: AttentiveMobileNetV3 + Subnet: https://download.openmmlab.com/mmrazor/v1/bignas/ATTENTIVE_SUBNET_A6.yaml + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 80.81 + Config: configs/nas/mmcls/bignas/attentive_mobilenet_subnet_8xb256_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_subnet_8xb256_in1k_flops-0.93G_acc-80.81_20221229_200440-73d92cc6.pth + + - Name: attentive_mobilenet_subnet_8xb256_in1k_flops-212M + In Collection: BigNAS + Metadata: + Flops(G): 0.212 + Params(M): 8.854 + Supernet: AttentiveMobileNetV3 + Channel: https://download.openmmlab.com/mmrazor/v1/bignas/ATTENTIVE_SUBNET_A0.yaml + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 77.19 + Config: configs/nas/mmcls/bignas/attentive_mobilenet_subnet_8xb256_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/bignas/attentive_mobilenet_subnet_8xb256_in1k_flops-0.21G_acc-77.19_20221229_200440-282a1f70.pth diff --git a/configs/nas/mmcls/dsnas/README.md b/configs/nas/mmcls/dsnas/README.md index 222e731de..fac1e9b6c 100644 --- a/configs/nas/mmcls/dsnas/README.md +++ b/configs/nas/mmcls/dsnas/README.md @@ -34,9 +34,9 @@ CUDA_VISIBLE_DEVICES=0 PORT=29500 ./tools/dist_test.sh \ ### Supernet -| Dataset | Params(M) | FLOPs (G) | Top-1 Acc (%) | Top-5 Acc (%) | Config | Download | Remarks | -| :------: | :-------: | :-------: | :-----------: | :-----------: | :---------------------------------------: | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------: | -| ImageNet | 3.33 | 0.299 | 73.56 | 91.24 | [config](./dsnas_supernet_8xb128_in1k.py) | [model](https://openmmlab-share.oss-cn-hangzhou.aliyuncs.com/mmrazor/v1/dsnas/dsnas_supernet_8xb128_in1k_20220926_171954-29b87e3a.pth) \| [log](https://download.openmmlab.com/mmrazor/v1/dsnas/dsnas_supernet_8xb128_in1k_20220926_171954-29b87e3a.log) | MMRazor searched | +| Dataset | Params(M) | FLOPs (G) | Top-1 Acc (%) | Top-5 Acc (%) | Config | Download | Remarks | +| :------: | :-------: | :-------: | :-----------: | :-----------: | :---------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :--------------: | +| ImageNet | 3.33 | 0.299 | 73.56 | 91.24 | [config](./dsnas_supernet_8xb128_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/dsnas/dsnas_supernet_8xb128_in1k_20220926_171954-29b87e3a.pth) \| [log](https://download.openmmlab.com/mmrazor/v1/dsnas/dsnas_supernet_8xb128_in1k_20220926_171954-29b87e3a.log) | MMRazor searched | **Note**: diff --git a/configs/nas/mmcls/dsnas/metafile.yml b/configs/nas/mmcls/dsnas/metafile.yml new file mode 100644 index 000000000..faf605a17 --- /dev/null +++ b/configs/nas/mmcls/dsnas/metafile.yml @@ -0,0 +1,27 @@ +Collections: + - Name: DSNAS + Metadata: + Training Data: + - ImageNet-1k + Paper: + URL: https://arxiv.org/abs/2002.09128.pdf + Title: DSNAS Direct Neural Architecture Search without Parameter Retraining + README: configs/nas/mmcls/dsnas/README.md + Code: + URL: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/mmrazor/models/algorithms/nas/dsnas.py + Version: V1.0.0rc2 + +Models: + - Name: dsnas_subnet_8xb128_in1k + In Collection: DSNAS + Metadata: + Flops(G): 0.299 + Params(M): 3.33 + Subnet: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/dsnas/DSNAS_SUBNET_IMAGENET_PAPER_ALIAS.yaml + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 73.56 + Config: configs/nas/mmcls/dsnas/dsnas_subnet_8xb128_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/dsnas/dsnas_supernet_8xb128_in1k_20220926_171954-29b87e3a.pth diff --git a/configs/nas/mmcls/onceforall/README.md b/configs/nas/mmcls/onceforall/README.md index 92270f708..e9d360f10 100644 --- a/configs/nas/mmcls/onceforall/README.md +++ b/configs/nas/mmcls/onceforall/README.md @@ -25,9 +25,9 @@ CUDA_VISIBLE_DEVICES=0 PORT=29500 ./tools/dist_test.sh \ | Dataset | Supernet | Subnet | Params(M) | Flops(G) | Top-1 | Config | Download | Remarks | | :------: | :------------------: | :-------------------------------------------------------------------------------------------------------------------------: | :-------: | :------: | :---: | :-----------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------------------------------------------------------: | :---------------------: | -| ImageNet | AttentiveMobileNetV3 | [search space](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/_base_/nas_backbones/ofa_mobilenetv3_supernet.py) | 7.6 | 747.8 | 77.5 | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/onceforall/ofa_mobilenet_supernet_32xb64_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_supernet_d234_e346_k357_w1_0.py_20221214_0940-d0ebc66f.pth) | Converted from the repo | -| ImageNet | AttentiveMobileNetV3 | note8_lat@22ms_top1@70.4_finetune@25 | 4.3 | 70.9 | 70.3 | [config](https://download.openmmlab.com/mmrazor/v1/ofa/rtmdet/OFA_SUBNET_NOTE8_LAT22.yaml) | [model](https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_subnet_8xb256_in1k_note8_lat%4022ms_top1%4070.4_finetune%4025.py_20221214_0938-fb7fb84f.pth) | Converted from the repo | -| ImageNet | AttentiveMobileNetV3 | note8_lat@31ms_top1@72.8_finetune@25 | 4.6 | 105.4 | 72.6 | [config](https://download.openmmlab.com/mmrazor/v1/ofa/rtmdet/OFA_SUBNET_NOTE8_LAT31.yaml) | [model](https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_subnet_8xb256_in1k_note8_lat%4031ms_top1%4072.8_finetune%4025.py_20221214_0939-981a8b2a.pth) | Converted from the repo | +| ImageNet | AttentiveMobileNetV3 | [search space](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/_base_/nas_backbones/ofa_mobilenetv3_supernet.py) | 7.6 | 0.747 | 77.5 | [config](https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/onceforall/ofa_mobilenet_supernet_32xb64_in1k.py) | [model](https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_supernet_d234_e346_k357_w1_0.py_20221214_0940-d0ebc66f.pth) | Converted from the repo | +| ImageNet | AttentiveMobileNetV3 | note8_lat@22ms_top1@70.4_finetune@25 | 4.3 | 0.070 | 70.3 | [config](https://download.openmmlab.com/mmrazor/v1/ofa/rtmdet/OFA_SUBNET_NOTE8_LAT22.yaml) | [model](https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_subnet_8xb256_in1k_note8_lat%4022ms_top1%4070.4_finetune%4025.py_20221214_0938-fb7fb84f.pth) | Converted from the repo | +| ImageNet | AttentiveMobileNetV3 | note8_lat@31ms_top1@72.8_finetune@25 | 4.6 | 0.105 | 72.6 | [config](https://download.openmmlab.com/mmrazor/v1/ofa/rtmdet/OFA_SUBNET_NOTE8_LAT31.yaml) | [model](https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_subnet_8xb256_in1k_note8_lat%4031ms_top1%4072.8_finetune%4025.py_20221214_0939-981a8b2a.pth) | Converted from the repo | **Note**: diff --git a/configs/nas/mmcls/onceforall/metafile.yml b/configs/nas/mmcls/onceforall/metafile.yml new file mode 100644 index 000000000..41df87902 --- /dev/null +++ b/configs/nas/mmcls/onceforall/metafile.yml @@ -0,0 +1,41 @@ +Collections: + - Name: OFA + Metadata: + Training Data: + - ImageNet-1k + Paper: + URL: https://arxiv.org/abs/1908.09791 + Title: ONCE-FOR-ALL TRAIN ONE NETWORK AND SPE- CIALIZE IT FOR EFFICIENT DEPLOYMENT + README: configs/nas/mmcls/onceforall/README.md + Code: + URL: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/mmrazor/models/algorithms/nas/bignas.py + Version: V1.0.0rc2 + +Models: + - Name: ofa_mobilenet_subnet_8xb256_in1k_lat-22ms + In Collection: OFA + Metadata: + Flops(G): 0.070 + Params(M): 4.3 + Subnet: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/onceforall/OFA_SUBNET_NOTE8_LAT22.yaml + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 70.3 + Config: configs/nas/mmcls/onceforall/ofa_mobilenet_subnet_8xb256_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_subnet_8xb256_in1k_note8_lat%4022ms_top1%4070.4_finetune%4025.py_20221214_0938-fb7fb84f.pth + + - Name: ofa_mobilenet_subnet_8xb256_in1k_lat-31ms + In Collection: OFA + Metadata: + Flops(G): 0.105 + Params(M): 4.6 + Subnet: https://github.com/open-mmlab/mmrazor/blob/dev-1.x/configs/nas/mmcls/onceforall/OFA_SUBNET_NOTE8_LAT31.yaml + Results: + - Task: Image Classification + Dataset: ImageNet-1k + Metrics: + Top 1 Accuracy: 72.6 + Config: configs/nas/mmcls/onceforall/ofa_mobilenet_subnet_8xb256_in1k.py + Weights: https://download.openmmlab.com/mmrazor/v1/ofa/ofa_mobilenet_subnet_8xb256_in1k_note8_lat%4031ms_top1%4072.8_finetune%4025.py_20221214_0939-981a8b2a.pth