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Bump version to v1.0.0rc7 (#1465)
* update * update info * update changelog * update * update description * change to v1.0.0rc7
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README.md

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## What's new
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🌟 v1.0.0rc6 was released in 06/04/2023
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🌟 v1.0.0rc7 was released in 07/04/2023
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- Integrated Self-supervised leanrning algorithms from **MMSelfSup**, such as `MAE`, `BEiT`, `MILAN`, etc.
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- Integrated Self-supervised learning algorithms from **MMSelfSup**, such as **MAE**, **BEiT**, etc.
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- Support **RIFormer**, a simple but effective vision backbone by removing token mixer.
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- Add t-SNE visualization.
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- Refactor dataset pipeline visualization.
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Previous version update
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Update of previous versions
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- Support **LeViT**, **XCiT**, **ViG**, **ConvNeXt-V2**, **EVA**, **RevViT**, **EfficientnetV2**, **CLIP**, **TinyViT** and **MixMIM** backbones.
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- Reproduce the training accuracy of **ConvNeXt** and **RepVGG**.
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<li><a href="configs/vig">ViG</a></li>
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<li><a href="configs/xcit">XCiT</a></li>
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<li><a href="configs/levit">LeViT</a></li>
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<li><a href="configs/riformer">RIFormer</a></li>
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</ul>
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</td>
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README_zh-CN.md

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## 更新日志
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🌟 2023/4/6 发布了 v1.0.0rc6 版本
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🌟 2023/4/7 发布了 v1.0.0rc7 版本
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- 整和来自 MMSelfSup 的自监督学习算法,例如 `MAE`, `BEiT`, `MILAN`
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- 整和来自 MMSelfSup 的自监督学习算法,例如 `MAE`, `BEiT`
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- 支持了 **RIFormer**,简单但有效的视觉主干网络,却移除了 token mixer
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- 支持 t-SNE 可视化
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- 重构数据管道可视化
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<li><a href="configs/vig">ViG</a></li>
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<li><a href="configs/xcit">XCiT</a></li>
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<li><a href="configs/levit">LeViT</a></li>
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<li><a href="configs/riformer">RIFormer</a></li>
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</ul>
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</td>
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configs/riformer/metafile.yml

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Title: "RIFormer: Keep Your Vision Backbone Effective But Removing Token Mixer"
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README: configs/riformer/README.md
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Code:
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Version: v1.0.0rc6
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Version: v1.0.0rc7
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URL: null
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Models:

docs/en/get_started.md

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Just install with mim.
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```shell
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pip install -U openmim && mim install "mmpretrain>=1.0.0rc6"
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pip install -U openmim && mim install "mmpretrain>=1.0.0rc7"
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```
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```{note}

docs/en/notes/changelog.md

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# Changelog
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# Changelog (MMPreTrain)
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## v1.0.0rc7(07/04/2023)
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### Highlights
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- Integrated Self-supervised learning algorithms from **MMSelfSup**, such as **MAE**, **BEiT**, etc.
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- Support **RIFormer**, a simple but effective vision backbone by removing token mixer.
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- Support **LeViT**, **XCiT**, **ViG** and **ConvNeXt-V2** backbone.
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- Add t-SNE visualization.
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- Refactor dataset pipeline visualization.
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- Support confusion matrix calculation and plot.
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### New Features
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- Support RIFormer. ([#1453](https://github.com/open-mmlab/mmpretrain/pull/1453))
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- Support XCiT Backbone. ([#1305](https://github.com/open-mmlab/mmclassification/pull/1305))
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- Support calculate confusion matrix and plot it. ([#1287](https://github.com/open-mmlab/mmclassification/pull/1287))
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- Support RetrieverRecall metric & Add ArcFace config ([#1316](https://github.com/open-mmlab/mmclassification/pull/1316))
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- Add `ImageClassificationInferencer`. ([#1261](https://github.com/open-mmlab/mmclassification/pull/1261))
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- Support InShop Dataset (Image Retrieval). ([#1019](https://github.com/open-mmlab/mmclassification/pull/1019))
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- Support LeViT backbone. ([#1238](https://github.com/open-mmlab/mmclassification/pull/1238))
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- Support VIG Backbone. ([#1304](https://github.com/open-mmlab/mmclassification/pull/1304))
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- Support ConvNeXt-V2 backbone. ([#1294](https://github.com/open-mmlab/mmclassification/pull/1294))
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### Improvements
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- Use PyTorch official `scaled_dot_product_attention` to accelerate `MultiheadAttention`. ([#1434](https://github.com/open-mmlab/mmpretrain/pull/1434))
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- Add ln to vit avg_featmap output ([#1447](https://github.com/open-mmlab/mmpretrain/pull/1447))
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- Update analysis tools and documentations. ([#1359](https://github.com/open-mmlab/mmclassification/pull/1359))
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- Unify the `--out` and `--dump` in `tools/test.py`. ([#1307](https://github.com/open-mmlab/mmclassification/pull/1307))
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- Enable to toggle whether Gem Pooling is trainable or not. ([#1246](https://github.com/open-mmlab/mmclassification/pull/1246))
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- Update registries of mmcls. ([#1306](https://github.com/open-mmlab/mmclassification/pull/1306))
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- Add metafile fill and validation tools. ([#1297](https://github.com/open-mmlab/mmclassification/pull/1297))
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- Remove useless EfficientnetV2 config files. ([#1300](https://github.com/open-mmlab/mmclassification/pull/1300))
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### Bug Fixes
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- Fix precise bn hook ([#1466](https://github.com/open-mmlab/mmpretrain/pull/1466))
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- Fix retrieval multi gpu bug ([#1319](https://github.com/open-mmlab/mmclassification/pull/1319))
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- Fix error repvgg-deploy base config path. ([#1357](https://github.com/open-mmlab/mmclassification/pull/1357))
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- Fix bug in test tools. ([#1309](https://github.com/open-mmlab/mmclassification/pull/1309))
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### Docs Update
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- Translate some tools tutorials to Chinese. ([#1321](https://github.com/open-mmlab/mmclassification/pull/1321))
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- Add Chinese translation for runtime.md. ([#1313](https://github.com/open-mmlab/mmclassification/pull/1313))
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# Changelog (MMClassification)
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## v1.0.0rc5(30/12/2022)
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docs/en/notes/faq.md

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| MMPretrain version | MMEngine version | MMCV version |
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| :----------------: | :---------------: | :--------------: |
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| 1.0.0rc0 (main) | mmengine >= 0.4.0 | mmcv >= 2.0.0rc4 |
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| 1.0.0rc7 (main) | mmengine >= 0.5.0 | mmcv >= 2.0.0rc4 |
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```{note}
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Since the `dev` branch is under frequent development, the MMEngine and MMCV

docs/zh_CN/get_started.md

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直接使用 mim 安装即可。
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```shell
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pip install -U openmim && mim install "mmpretrain>=1.0.0rc7"
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```
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```{note}

docs/zh_CN/notes/faq.md

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| MMPretrain 版本 | MMEngine 版本 | MMCV 版本 |
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| :-------------: | :---------------: | :--------------: |
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| 1.0.0rc0 (main) | mmengine >= 0.4.0 | mmcv >= 2.0.0rc4 |
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| 1.0.0rc7 (main) | mmengine >= 0.5.0 | mmcv >= 2.0.0rc4 |
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```{note}
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由于 `dev` 分支处于频繁开发中,MMEngine 和 MMCV 版本依赖可能不准确。如果您在使用

mmpretrain/version.py

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# Copyright (c) OpenMMLab. All rights reserved
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__version__ = '1.0.0rc5'
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__version__ = '1.0.0rc7'
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def parse_version_info(version_str):

model-index.yml

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- configs/convmixer/metafile.yml
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- configs/densenet/metafile.yml
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- configs/poolformer/metafile.yml
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- configs/riformer/metafile.yml
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- configs/inception_v3/metafile.yml
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- configs/mvit/metafile.yml
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- configs/edgenext/metafile.yml
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- configs/cae/metafile.yml
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- configs/maskfeat/metafile.yml
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- configs/milan/metafile.yml
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- configs/riformer/metafile.yml

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