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Bump v0.21.0 (open-mmlab#1258)
* change version to v0.21.0 * change version to v0.21.0 * change version to v0.21.0 * change version to v0.21.0
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‎README.md

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## Changelog
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v0.20.2 was released in 12/15/2021.
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v0.21.0 was released in 1/29/2022.
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Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
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## Benchmark and model zoo

‎README_zh-CN.md

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## 更新日志
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最新的月度版本 v0.20.2 在 2021.12.15 发布。
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最新的月度版本 v0.21.0 在 2022.1.29 发布。
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如果想了解更多版本更新细节和历史信息，请阅读[更新日志](docs/en/changelog.md)。
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## 基准测试和模型库

‎docker/serve/Dockerfile

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ARG CUDNN="7"
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FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
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ARG MMCV="1.3.13"
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ARG MMSEG="0.20.0"
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ARG MMCV="1.4.4"
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ARG MMSEG="0.21.0"
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ENV PYTHONUNBUFFERED TRUE
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‎docs/en/changelog.md

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## Changelog
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### V0.21 (1/29/2022)
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**Highlights**
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- Officially Support CPUs training and inference, please use the latest MMCV (1.4.4) to try it out.
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- Support Segmenter: Transformer for Semantic Segmentation (ICCV'2021).
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- Support ISPRS Potsdam and Vaihingen Dataset.
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- Add Mosaic transform and `MultiImageMixDataset` class in `dataset_wrappers`.
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**New Features**
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- Support Segmenter: Transformer for Semantic Segmentation (ICCV'2021) ([#955](https://github.com/open-mmlab/mmsegmentation/pull/955))
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- Support ISPRS Potsdam and Vaihingen Dataset ([#1097](https://github.com/open-mmlab/mmsegmentation/pull/1097), [#1171](https://github.com/open-mmlab/mmsegmentation/pull/1171))
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- Add segformer‘s benchmark on cityscapes ([#1155](https://github.com/open-mmlab/mmsegmentation/pull/1155))
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- Add auto resume ([#1172](https://github.com/open-mmlab/mmsegmentation/pull/1172))
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- Add Mosaic transform and `MultiImageMixDataset` class in `dataset_wrappers` ([#1093](https://github.com/open-mmlab/mmsegmentation/pull/1093), [#1105](https://github.com/open-mmlab/mmsegmentation/pull/1105))
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- Add log collector ([#1175](https://github.com/open-mmlab/mmsegmentation/pull/1175))
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**Improvements**
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- New-style CPU training and inference ([#1251](https://github.com/open-mmlab/mmsegmentation/pull/1251))
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- Add UNet benchmark with multiple losses supervision ([#1143](https://github.com/open-mmlab/mmsegmentation/pull/1143))
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**Bug Fixes**
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- Fix the model statistics in doc for readthedoc ([#1153](https://github.com/open-mmlab/mmsegmentation/pull/1153))
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- Set random seed for `palette` if not given ([#1152](https://github.com/open-mmlab/mmsegmentation/pull/1152))
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- Add `COCOStuffDataset` in `class_names.py` ([#1222](https://github.com/open-mmlab/mmsegmentation/pull/1222))
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- Fix bug in non-distributed multi-gpu training/testing ([#1247](https://github.com/open-mmlab/mmsegmentation/pull/1247))
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- Delete unnecessary lines of STDCHead ([#1231](https://github.com/open-mmlab/mmsegmentation/pull/1231))
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**Contributors**
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- @jbwang1997 made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1152
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- @BeaverCC made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1206
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- @Echo-minn made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/1214
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- @rstrudel made their first contribution in https://github.com/open-mmlab/mmsegmentation/pull/955
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### V0.20.2 (12/15/2021)
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**Bug Fixes**
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**Bug Fixes**
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- Fix incorrectly loading init_cfg or pretrained models of several transformer models ([#999](https://github.com/open-mmlab/mmsegmentation/pull/999), [#1069](https://github.com/open-mmlab/mmsegmentation/pull/1069), [#1102](https://github.com/open-mmlab/mmsegmentation/pull/1102))
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- Fix EfficientMultiheadAttention in SegFormer ([#1003](https://github.com/open-mmlab/mmsegmentation/pull/1037))
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- Fix EfficientMultiheadAttention in SegFormer ([#1037](https://github.com/open-mmlab/mmsegmentation/pull/1037))
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- Remove `fp16` folder in `configs` ([#1031](https://github.com/open-mmlab/mmsegmentation/pull/1031))
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- Fix several typos in .yml file (Dice Metric [#1041](https://github.com/open-mmlab/mmsegmentation/pull/1041), ADE20K dataset [#1120](https://github.com/open-mmlab/mmsegmentation/pull/1120), Training Memory (GB) [#1083](https://github.com/open-mmlab/mmsegmentation/pull/1083))
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- Fix test error when using `--show-dir` ([#1091](https://github.com/open-mmlab/mmsegmentation/pull/1091))

‎docs/en/get_started.md

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The compatible MMSegmentation and MMCV versions are as below. Please install the correct version of MMCV to avoid installation issues.
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| MMSegmentation version | MMCV version |
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|:-------------------:|:-------------------:|
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| master | mmcv-full>=1.3.13, <1.5.0 |
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| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 |
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| 0.19.0 | mmcv-full>=1.3.13, <1.4.0 |
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| 0.18.0 | mmcv-full>=1.3.13, <1.4.0 |
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| 0.17.0 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.16.0 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.15.0 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.14.1 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 |
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| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 |
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| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 |
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| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 |
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| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 |
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| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 |
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| MMSegmentation version | MMCV version |
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|:----------------------:|:--------------------------:|
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| master | mmcv-full>=1.4.4, <1.5.0 |
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| 0.21.0 | mmcv-full>=1.4.4, <1.5.0 |
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| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 |
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| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 |
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| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 |
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| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 |
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| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 |
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| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 |
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| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 |
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| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 |
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| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 |
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:::{note}
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You need to run `pip uninstall mmcv` first if you have mmcv installed.

‎docs/zh_cn/get_started.md

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可编译的 MMSegmentation 和 MMCV 版本如下所示，请对照对应版本安装以避免安装问题。
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| MMSegmentation 版本 | MMCV 版本 |
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|:-------------------:|:-------------------:|
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| master | mmcv-full>=1.3.13, <1.5.0 |
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| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 |
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| 0.19.0 | mmcv-full>=1.3.13, <1.4.0 |
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| 0.18.0 | mmcv-full>=1.3.13, <1.4.0 |
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| 0.17.0 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.16.0 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.15.0 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.14.1 | mmcv-full>=1.3.7, <1.4.0 |
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| 0.14.0 | mmcv-full>=1.3.1, <1.4.0 |
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| 0.13.0 | mmcv-full>=1.3.1, <1.4.0 |
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| 0.12.0 | mmcv-full>=1.1.4, <1.4.0 |
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| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 |
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| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 |
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| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 |
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| MMSegmentation 版本 | MMCV 版本 |
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|:-----------------:|:--------------------------:|
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| master | mmcv-full>=1.4.4, <1.5.0 |
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| 0.21.0 | mmcv-full>=1.4.4, <1.5.0 |
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| 0.20.0 | mmcv-full>=1.3.13, <1.5.0 |
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| 0.19.0 | mmcv-full>=1.3.13, <1.3.17 |
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| 0.18.0 | mmcv-full>=1.3.13, <1.3.17 |
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| 0.17.0 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.16.0 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.15.0 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.14.1 | mmcv-full>=1.3.7, <1.3.17 |
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| 0.14.0 | mmcv-full>=1.3.1, <1.3.2 |
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| 0.13.0 | mmcv-full>=1.3.1, <1.3.2 |
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| 0.12.0 | mmcv-full>=1.1.4, <1.3.2 |
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| 0.11.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.10.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.9.0 | mmcv-full>=1.1.4, <1.3.0 |
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| 0.8.0 | mmcv-full>=1.1.4, <1.2.0 |
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| 0.7.0 | mmcv-full>=1.1.2, <1.2.0 |
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| 0.6.0 | mmcv-full>=1.1.2, <1.2.0 |
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注意: 如果您已经安装好 mmcv， 您首先需要运行 `pip uninstall mmcv`。
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如果 mmcv 和 mmcv-full 同时被安装，会报错 `ModuleNotFoundError`。

‎mmseg/version.py

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# Copyright (c) Open-MMLab. All rights reserved.
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__version__ = '0.20.2'
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__version__ = '0.21.0'
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def parse_version_info(version_str):

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