Bump version to v1.0.0rc7 (#1465)
* update * update info * update changelog * update * update description * change to v1.0.0rc7pull/1471/head v1.0.0rc7
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@ -78,13 +78,14 @@ The `main` branch works with **PyTorch 1.8+**.
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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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@ -198,6 +199,7 @@ Results and models are available in the [model zoo](https://mmpretrain.readthedo
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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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<td>
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@ -76,9 +76,10 @@ MMPreTrain 是一款基于 PyTorch 的开源深度学习预训练工具箱,是
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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` 等
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- 整和来自 MMSelfSup 的自监督学习算法,例如 `MAE`, `BEiT` 等
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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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@ -194,6 +195,7 @@ mim install -e .
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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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<td>
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@ -11,7 +11,7 @@ Collections:
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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:
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@ -63,7 +63,7 @@ pip install -U openmim && mim install -e .
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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}
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@ -1,4 +1,52 @@
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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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@ -16,7 +16,7 @@ and make sure you fill in all required information in the template.
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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
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@ -67,7 +67,7 @@ pip install -U openmim && mim install -e .
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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>=1.0.0rc6"
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pip install -U openmim && mim install "mmpretrain>=1.0.0rc7"
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```
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```{note}
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@ -13,7 +13,7 @@
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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
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@ -1,6 +1,6 @@
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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):
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@ -29,7 +29,6 @@ Import:
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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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@ -67,3 +66,4 @@ Import:
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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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@ -1,2 +1,2 @@
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mmcv>=2.0.0rc1,<=2.0.0
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mmcv>=2.0.0rc4,<2.1.0
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mmengine>=0.4.0,<1.0.0
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@ -1,5 +1,5 @@
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--extra-index-url https://download.pytorch.org/whl/cpu
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mmcv-lite>=2.0.0rc1
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mmcv-lite>=2.0.0rc4
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mmengine
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torch
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torchvision
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