[Docs] Update mdformat settings (#323)
* update mdformat setting * update mdformat * remove pip upgradepull/326/head
Yixiao Fang
GitHub
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bbdf670d00
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@ -110,8 +110,6 @@ jobs:
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uses: actions/setup-python@v2
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with:
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python-version: ${{ matrix.python }}
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- name: Upgrade pip
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run: pip install pip --upgrade --user
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- name: Install PyTorch
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# As a complement to Linux CI, we test on PyTorch LTS version
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run: pip install torch==1.8.2+${{ matrix.platform }} torchvision==0.9.2+${{ matrix.platform }} -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html
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@ -36,12 +36,12 @@ repos:
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- id: docformatter
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args: ["--in-place", "--wrap-descriptions", "79"]
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- repo: https://github.com/executablebooks/mdformat
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rev: 0.7.14
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rev: 0.7.9
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hooks:
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- id: mdformat
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args: ["--number"]
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additional_dependencies:
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- mdformat-gfm
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- mdformat-openmmlab
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- mdformat_frontmatter
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- linkify-it-py
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- repo: https://github.com/open-mmlab/pre-commit-hooks
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@ -128,7 +128,7 @@ MMSelfSup 依赖 [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open
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## 基准测试
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| 基准测试方法 | 参考设置 |
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| 基准测试方法 | 参考设置 |
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| -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| ImageNet Linear Classification (Multi-head) | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
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| ImageNet Linear Classification (Last) | |
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@ -4,7 +4,7 @@
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## 预训练模型
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| 算法 | 配置文件 | 下载链接 |
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| 算法 | 配置文件 | 下载链接 |
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| ------------------------------------------------------------------------------------------------------------------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| [Relative Location](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/README.md) | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220225-84784688.pth) \| [log](https://download.openmmlab.com/mmselfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k_20220211_124808.log.json) |
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| [Rotation Prediction](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/README.md) | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | [model](https://download.openmmlab.com/mmselfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220225-5b9f06a0.pth) \| [log](https://download.openmmlab.com/mmselfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k_20220215_185303.log.json) |
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@ -41,21 +41,21 @@
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如果没有特殊说明，下列实验采用 [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf) 的设置，或者采用的训练设置写在备注中。
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| 算法 | 配置文件 | 备注 | Top-1 (%) |
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| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------- | --------- |
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| Relative Location | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | | 38.78 |
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| Rotation Prediction | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | | 48.12 |
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| DeepCluster | [deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/deepcluster/deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py) | | 46.92 |
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| NPID | [npid_resnet50_8xb32-steplr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k.py) | | 58.97 |
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| ODC | [odc_resnet50_8xb64-steplr-440e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/odc/odc_resnet50_8xb64-steplr-440e_in1k.py) | | 53.43 |
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| 算法 | 配置文件 | 备注 | Top-1 (%) |
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| ------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------- | --------- |
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| Relative Location | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | | 38.78 |
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| Rotation Prediction | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | | 48.12 |
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| DeepCluster | [deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/deepcluster/deepcluster-sobel_resnet50_8xb64-steplr-200e_in1k.py) | | 46.92 |
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| NPID | [npid_resnet50_8xb32-steplr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/npid/npid_resnet50_8xb32-steplr-200e_in1k.py) | | 58.97 |
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| ODC | [odc_resnet50_8xb64-steplr-440e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/odc/odc_resnet50_8xb64-steplr-440e_in1k.py) | | 53.43 |
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| SimCLR | [simclr_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/simclr_resnet50_8xb32-coslr-200e_in1k.py) | SimSiam 论文设置 | 62.56 |
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| | [simclr_resnet50_16xb256-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simclr/simclr_resnet50_16xb256-coslr-200e_in1k.py) | SimSiam 论文设置 | 66.66 |
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| MoCo v2 | [mocov2_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py) | | 67.58 |
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| MoCo v2 | [mocov2_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mocov2/mocov2_resnet50_8xb32-coslr-200e_in1k.py) | | 67.58 |
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| BYOL | [byol_resnet50_8xb32-accum16-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_8xb32-accum16-coslr-200e_in1k.py) | SimSiam 论文设置 | 71.72 |
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| | [byol_resnet50_16xb256-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_16xb256-coslr-200e_in1k.py) | SimSiam 论文设置 | 71.88 |
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| | [byol_resnet50_8xb32-accum16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/byol/byol_resnet50_8xb32-accum16-coslr-300e_in1k.py) | SimSiam 论文设置 | 72.93 |
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| SwAV | [swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/swav/swav_resnet50_8xb32-mcrop-2-6-coslr-200e_in1k-224-96.py) | SwAV 论文设置 | 70.47 |
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| DenseCL | [densecl_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k.py) | | 63.62 |
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| DenseCL | [densecl_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/densecl/densecl_resnet50_8xb32-coslr-200e_in1k.py) | | 63.62 |
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| SimSiam | [simsiam_resnet50_8xb32-coslr-100e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-100e_in1k.py) | SimSiam 论文设置 | 68.28 |
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| | [simsiam_resnet50_8xb32-coslr-200e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simsiam/simsiam_resnet50_8xb32-coslr-200e_in1k.py) | SimSiam 论文设置 | 69.84 |
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| Barlow Twins | [barlowtwins_resnet50_8xb256-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/barlowtwins/barlowtwins_resnet50_8xb256-coslr-300e_in1k.py) | Barlow Twins 论文设置 | 71.66 |
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@ -63,17 +63,17 @@
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### ImageNet 微调
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| 算法 | 配置文件 | 备注 | Top-1 (%) |
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| ------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --- | --------- |
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| MAE | [mae_vit-base-p16_8xb512-coslr-400e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mae/mae_vit-base-p16_8xb512-coslr-400e_in1k.py) | | 83.1 |
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| SimMIM | [simmim_swin-base_16xb128-coslr-100e_in1k-192](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192.py) | | 82.9 |
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| CAE | [cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/cae/cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k.py) | | 83.2 |
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| 算法 | 配置文件 | 备注 | Top-1 (%) |
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| ------ | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---- | --------- |
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| MAE | [mae_vit-base-p16_8xb512-coslr-400e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/mae/mae_vit-base-p16_8xb512-coslr-400e_in1k.py) | | 83.1 |
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| SimMIM | [simmim_swin-base_16xb128-coslr-100e_in1k-192](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/simmim/simmim_swin-base_16xb128-coslr-100e_in1k-192.py) | | 82.9 |
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| CAE | [cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/cae/cae_vit-base-p16_8xb256-fp16-coslr-300e_in1k.py) | | 83.2 |
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### COCO17 目标检测和实例分割
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在 COCO17 数据集的目标检测和实例分割任务中，我们选用 [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf) 的评估设置，基于 Mask-RCNN FPN 网络架构，下列结果通过同样的 [配置文件](https://github.com/open-mmlab/mmselfsup/blob/master/configs/benchmarks/mmdetection/coco/mask_rcnn_r50_fpn_mstrain_1x_coco.py) 训练得到。
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| 算法 | 配置文件 | mAP (Box) | mAP (Mask) |
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| 算法 | 配置文件 | mAP (Box) | mAP (Mask) |
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| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | ---------- |
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| Relative Location | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | 37.5 | 33.7 |
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| Rotation Prediction | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | 37.9 | 34.2 |
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@ -89,7 +89,7 @@
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在 Pascal VOC12 Aug 语义分割任务中，我们选用 [MMSeg](https://github.com/open-mmlab/mmsegmentation) 的评估设置, 基于 FCN 网络架构, 下列结果通过同样的 [配置文件](https://github.com/open-mmlab/mmselfsup/blob/master/configs/benchmarks/mmsegmentation/voc12aug/fcn_r50-d8_512x512_20k_voc12aug.py) 训练得到。
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| 算法 | 配置文件 | mIOU |
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| 算法 | 配置文件 | mIOU |
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| ------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ----- |
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| Relative Location | [relative-loc_resnet50_8xb64-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/relative_loc/relative-loc_resnet50_8xb64-steplr-70e_in1k.py) | 63.49 |
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| Rotation Prediction | [rotation-pred_resnet50_8xb16-steplr-70e_in1k](https://github.com/open-mmlab/mmselfsup/blob/master/configs/selfsup/rotation_pred/rotation-pred_resnet50_8xb16-steplr-70e_in1k.py) | 64.31 |
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