Bump version to v1.0.0rc4. (#1243)

* Bump version to v1.0.0rc4 * Update according to comments
2022-12-06 18:00:01 +08:00 · 2022-12-06 18:00:01 +08:00 · 12eca5b94a
parent ef3610d962
commit 12eca5b94a
7 changed files with 42 additions and 20 deletions
--- a/README.md
+++ b/README.md
@ -58,6 +58,11 @@ The `1.x` branch works with **PyTorch 1.6+**.

 ## What's new

+v1.0.0rc4 was released in 06/12/2022.
+
+- Upgrade API to get pre-defined models of MMClassification. See [#1236](https://github.com/open-mmlab/mmclassification/pull/1236) for more details.
+- Refactor BEiT backbone and support v1/v2 inference. See [#1144](https://github.com/open-mmlab/mmclassification/pull/1144).
+
 v1.0.0rc3 was released in 21/11/2022.

 - Add **Switch Recipe** Hook, Now we can modify training pipeline, mixup and loss settings during training, see [#1101](https://github.com/open-mmlab/mmclassification/pull/1101).
@ -65,11 +70,6 @@ v1.0.0rc3 was released in 21/11/2022.
 - Support **retrieval tasks**, see [#1055](https://github.com/open-mmlab/mmclassification/pull/1055).
 - Reproduce **mobileone** training accuracy. See [#1191](https://github.com/open-mmlab/mmclassification/pull/1191)

-v1.0.0rc2 was released in 12/10/2022.
-
- Support Deit-3 backbone.
- Fix MMEngine version requirements.
-
 This release introduced a brand new and flexible training & test engine, but it's still in progress. Welcome
 to try according to [the documentation](https://mmclassification.readthedocs.io/en/1.x/).

--- a/README_zh-CN.md
+++ b/README_zh-CN.md
@ -57,6 +57,11 @@ MMClassification 是一款基于 PyTorch 的开源图像分类工具箱，是 [O

 ## 更新日志

+2022/12/06 发布了 v1.0.0rc4 版本
+
+- 更新了主要 API 接口，用以方便地获取 MMClassification 中预定义的模型。详见 [#1236](https://github.com/open-mmlab/mmclassification/pull/1236)。
+- 重构 BEiT 主干网络结构，并支持 v1 和 v2 模型的推理。
+
 2022/11/21 发布了 v1.0.0rc3 版本

 - 添加了 **Switch Recipe Hook**，现在我们可以在训练过程中修改数据增强、Mixup设置、loss设置等
@ -64,16 +69,6 @@ MMClassification 是一款基于 PyTorch 的开源图像分类工具箱，是 [O
 - 支持了检索任务
 - 复现了 **MobileOne** 训练精度

-2022/10/12 发布了 v1.0.0rc2 版本
-
- 支持了 Deit-3 主干网络
- 修复了 MMEngine 版本依赖问题
-
-2022/9/30 发布了 v1.0.0rc1 版本
-
- 支持了 MViT，EdgeNeXt，Swin-Transformer V2，EfficientFormer，MobileOne 等主干网络。
- 支持了 BEiT 风格的 transformer 层。
-
 2022/8/31 发布了 v1.0.0rc0 版本

 这个版本引入一个全新的，可扩展性强的训练和测试引擎，但目前仍在开发中。欢迎根据[文档](https://mmclassification.readthedocs.io/zh_CN/1.x/)进行试用。
--- a/docker/serve/Dockerfile
+++ b/docker/serve/Dockerfile
@ -7,9 +7,9 @@ FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel
 RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/3bf863cc.pub 32
 RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/7fa2af80.pub

-ARG MMENGINE="0.3.1"
+ARG MMENGINE="0.3.2"
 ARG MMCV="2.0.0rc1"
-ARG MMCLS="1.0.0rc3"
+ARG MMCLS="1.0.0rc4"

 ENV PYTHONUNBUFFERED TRUE

--- a/docs/en/notes/changelog.md
+++ b/docs/en/notes/changelog.md
@ -1,5 +1,32 @@
 # Changelog

+## v1.0.0rc4(06/12/2022)
+
+### Highlights
+
+- Upgrade API to get pre-defined models of MMClassification. See [#1236](https://github.com/open-mmlab/mmclassification/pull/1236) for more details.
+- Refactor BEiT backbone and support v1/v2 inference. See [#1144](https://github.com/open-mmlab/mmclassification/pull/1144).
+
+### New Features
+
+- Support getting model from the name defined in the model-index file. ([#1236](https://github.com/open-mmlab/mmclassification/pull/1236))
+
+### Improvements
+
+- Support evaluate on both EMA and non-EMA models. ([#1204](https://github.com/open-mmlab/mmclassification/pull/1204))
+- Refactor BEiT backbone and support v1/v2 inference. ([#1144](https://github.com/open-mmlab/mmclassification/pull/1144))
+
+### Bug Fixes
+
+- Fix `reparameterize_model.py` doesn't save meta info. ([#1221](https://github.com/open-mmlab/mmclassification/pull/1221))
+- Fix dict update in BEiT. ([#1234](https://github.com/open-mmlab/mmclassification/pull/1234))
+
+### Docs Update
+
+- Update install tutorial. ([#1223](https://github.com/open-mmlab/mmclassification/pull/1223))
+- Update MobileNetv2 & MobileNetv3 readme. ([#1222](https://github.com/open-mmlab/mmclassification/pull/1222))
+- Add version selection in the banner. ([#1217](https://github.com/open-mmlab/mmclassification/pull/1217))
+
 ## v1.0.0rc3(21/11/2022)

 ### Highlights
--- a/docs/en/notes/faq.md
+++ b/docs/en/notes/faq.md
@ -17,7 +17,7 @@ and make sure you fill in all required information in the template.

  | MMClassification version |      MMCV version      |
  | :----------------------: | :--------------------: |
-  |      1.0.0rc3 (1.x)      |     mmcv>=2.0.0rc1     |
+  |      1.0.0rc4 (1.x)      |     mmcv>=2.0.0rc1     |
  |     0.24.0 (master)      |  mmcv>=1.4.2, \<1.7.0  |
  |          0.23.1          |  mmcv>=1.4.2, \<1.6.0  |
  |          0.22.1          |  mmcv>=1.4.2, \<1.6.0  |
--- a/docs/zh_CN/notes/faq.md
+++ b/docs/zh_CN/notes/faq.md
@ -15,7 +15,7 @@

  | MMClassification version |      MMCV version      |
  | :----------------------: | :--------------------: |
-  |      1.0.0rc3 (1.x)      |     mmcv>=2.0.0rc1     |
+  |      1.0.0rc4 (1.x)      |     mmcv>=2.0.0rc1     |
  |     0.24.0 (master)      |  mmcv>=1.4.2, \<1.7.0  |
  |          0.23.1          |  mmcv>=1.4.2, \<1.6.0  |
  |          0.22.1          |  mmcv>=1.4.2, \<1.6.0  |
--- a/mmcls/version.py
+++ b/mmcls/version.py
@ -1,6 +1,6 @@
 # Copyright (c) OpenMMLab. All rights reserved

-__version__ = '1.0.0rc3'
+__version__ = '1.0.0rc4'


 def parse_version_info(version_str):