Bump version to v1.0.0rc7 (#1465)

* update

* update info

* update changelog

* update

* update description

* change to v1.0.0rc7

Author: fangyixiao18

README.md

@@ -78,13 +78,14 @@ The `main` branch works with **PyTorch 1.8+**.
 
 ## What's new
 
-🌟 v1.0.0rc6 was released in 06/04/2023
+🌟 v1.0.0rc7 was released in 07/04/2023
 
-- Integrated Self-supervised leanrning algorithms from **MMSelfSup**, such as `MAE`, `BEiT`, `MILAN`, etc.
+- Integrated Self-supervised learning algorithms from **MMSelfSup**, such as **MAE**, **BEiT**, etc.
+- Support **RIFormer**, a simple but effective vision backbone by removing token mixer.
 - Add t-SNE visualization.
 - Refactor dataset pipeline visualization.
 
-Previous version update
+Update of previous versions
 
 - Support **LeViT**, **XCiT**, **ViG**, **ConvNeXt-V2**, **EVA**, **RevViT**, **EfficientnetV2**, **CLIP**, **TinyViT** and **MixMIM** backbones.
 - Reproduce the training accuracy of **ConvNeXt** and **RepVGG**.
@@ -198,6 +199,7 @@ Results and models are available in the [model zoo](https://mmpretrain.readthedo
         <li><a href="configs/vig">ViG</a></li>
         <li><a href="configs/xcit">XCiT</a></li>
         <li><a href="configs/levit">LeViT</a></li>
+        <li><a href="configs/riformer">RIFormer</a></li>
         </ul>
       </td>
       <td>

README_zh-CN.md

@@ -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
 
 ## 更新日志
 
-🌟 2023/4/6 发布了 v1.0.0rc6 版本
+🌟 2023/4/7 发布了 v1.0.0rc7 版本
 
-- 整和来自 MMSelfSup 的自监督学习算法，例如 `MAE`, `BEiT`, `MILAN` 等
+- 整和来自 MMSelfSup 的自监督学习算法，例如 `MAE`, `BEiT` 等
+- 支持了 **RIFormer**，简单但有效的视觉主干网络，却移除了 token mixer
 - 支持 t-SNE 可视化
 - 重构数据管道可视化
 
@@ -194,6 +195,7 @@ mim install -e .
         <li><a href="configs/vig">ViG</a></li>
         <li><a href="configs/xcit">XCiT</a></li>
         <li><a href="configs/levit">LeViT</a></li>
+        <li><a href="configs/riformer">RIFormer</a></li>
         </ul>
       </td>
       <td>

configs/riformer/metafile.yml

@@ -11,7 +11,7 @@ Collections:
       Title: "RIFormer: Keep Your Vision Backbone Effective But Removing Token Mixer"
     README: configs/riformer/README.md
     Code:
-      Version: v1.0.0rc6
+      Version: v1.0.0rc7
       URL: null
 
 Models:

docs/en/get_started.md

@@ -63,7 +63,7 @@ pip install -U openmim && mim install -e .
 Just install with mim.
 
 ```shell
-pip install -U openmim && mim install "mmpretrain>=1.0.0rc6"
+pip install -U openmim && mim install "mmpretrain>=1.0.0rc7"
 ```
 
 ```{note}

docs/en/notes/changelog.md

@@ -1,4 +1,52 @@
-# Changelog
+# Changelog (MMPreTrain)
+
+## v1.0.0rc7(07/04/2023)
+
+### Highlights
+
+- Integrated Self-supervised learning algorithms from **MMSelfSup**, such as **MAE**, **BEiT**, etc.
+- Support **RIFormer**, a simple but effective vision backbone by removing token mixer.
+- Support **LeViT**, **XCiT**, **ViG** and **ConvNeXt-V2** backbone.
+- Add t-SNE visualization.
+- Refactor dataset pipeline visualization.
+- Support confusion matrix calculation and plot.
+
+### New Features
+
+- Support RIFormer. ([#1453](https://github.com/open-mmlab/mmpretrain/pull/1453))
+- Support XCiT Backbone. ([#1305](https://github.com/open-mmlab/mmclassification/pull/1305))
+- Support calculate confusion matrix and plot it. ([#1287](https://github.com/open-mmlab/mmclassification/pull/1287))
+- Support RetrieverRecall metric & Add ArcFace config ([#1316](https://github.com/open-mmlab/mmclassification/pull/1316))
+- Add `ImageClassificationInferencer`. ([#1261](https://github.com/open-mmlab/mmclassification/pull/1261))
+- Support InShop Dataset (Image Retrieval). ([#1019](https://github.com/open-mmlab/mmclassification/pull/1019))
+- Support LeViT backbone. ([#1238](https://github.com/open-mmlab/mmclassification/pull/1238))
+- Support VIG Backbone. ([#1304](https://github.com/open-mmlab/mmclassification/pull/1304))
+- Support ConvNeXt-V2 backbone. ([#1294](https://github.com/open-mmlab/mmclassification/pull/1294))
+
+### Improvements
+
+- Use PyTorch official `scaled_dot_product_attention` to accelerate `MultiheadAttention`. ([#1434](https://github.com/open-mmlab/mmpretrain/pull/1434))
+- Add ln to vit avg_featmap output ([#1447](https://github.com/open-mmlab/mmpretrain/pull/1447))
+- Update analysis tools and documentations. ([#1359](https://github.com/open-mmlab/mmclassification/pull/1359))
+- Unify the `--out` and `--dump` in `tools/test.py`. ([#1307](https://github.com/open-mmlab/mmclassification/pull/1307))
+- Enable to toggle whether Gem Pooling is trainable or not. ([#1246](https://github.com/open-mmlab/mmclassification/pull/1246))
+- Update registries of mmcls. ([#1306](https://github.com/open-mmlab/mmclassification/pull/1306))
+- Add metafile fill and validation tools. ([#1297](https://github.com/open-mmlab/mmclassification/pull/1297))
+- Remove useless EfficientnetV2 config files. ([#1300](https://github.com/open-mmlab/mmclassification/pull/1300))
+
+### Bug Fixes
+
+- Fix precise bn hook ([#1466](https://github.com/open-mmlab/mmpretrain/pull/1466))
+- Fix retrieval multi gpu bug ([#1319](https://github.com/open-mmlab/mmclassification/pull/1319))
+- Fix error repvgg-deploy base config path. ([#1357](https://github.com/open-mmlab/mmclassification/pull/1357))
+- Fix bug in test tools. ([#1309](https://github.com/open-mmlab/mmclassification/pull/1309))
+
+### Docs Update
+
+- Translate some tools tutorials to Chinese. ([#1321](https://github.com/open-mmlab/mmclassification/pull/1321))
+- Add Chinese translation for runtime.md.  ([#1313](https://github.com/open-mmlab/mmclassification/pull/1313))
+
+# Changelog (MMClassification)
 
 ## v1.0.0rc5(30/12/2022)
 

docs/en/notes/faq.md

@@ -16,7 +16,7 @@ and make sure you fill in all required information in the template.
 
   | MMPretrain version | MMEngine version  |   MMCV version   |
   | :----------------: | :---------------: | :--------------: |
-  |  1.0.0rc0 (main)   | mmengine >= 0.4.0 | mmcv >= 2.0.0rc4 |
+  |  1.0.0rc7 (main)   | mmengine >= 0.5.0 | mmcv >= 2.0.0rc4 |
 
   ```{note}
   Since the `dev` branch is under frequent development, the MMEngine and MMCV

docs/zh_CN/get_started.md

@@ -67,7 +67,7 @@ pip install -U openmim && mim install -e .
 直接使用 mim 安装即可。
 
 ```shell
-pip install -U openmim && mim install "mmpretrain>=1.0.0rc6"
+pip install -U openmim && mim install "mmpretrain>=1.0.0rc7"
 ```
 
 ```{note}

docs/zh_CN/notes/faq.md

@@ -13,7 +13,7 @@
 
   | MMPretrain 版本 |   MMEngine 版本   |    MMCV 版本     |
   | :-------------: | :---------------: | :--------------: |
-  | 1.0.0rc0 (main) | mmengine >= 0.4.0 | mmcv >= 2.0.0rc4 |
+  | 1.0.0rc7 (main) | mmengine >= 0.5.0 | mmcv >= 2.0.0rc4 |
 
   ```{note}
   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

@@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved
 
-__version__ = '1.0.0rc5'
+__version__ = '1.0.0rc7'
 
 
 def parse_version_info(version_str):

model-index.yml

@@ -29,7 +29,6 @@ Import:
   - configs/convmixer/metafile.yml
   - configs/densenet/metafile.yml
   - configs/poolformer/metafile.yml
-  - configs/riformer/metafile.yml
   - configs/inception_v3/metafile.yml
   - configs/mvit/metafile.yml
   - configs/edgenext/metafile.yml
@@ -67,3 +66,4 @@ Import:
   - configs/cae/metafile.yml
   - configs/maskfeat/metafile.yml
   - configs/milan/metafile.yml
+  - configs/riformer/metafile.yml