From 12eca5b94a7627a04dfb726221674b6419fd8b11 Mon Sep 17 00:00:00 2001
From: Ma Zerun <mzr1996@163.com>
Date: Tue, 6 Dec 2022 18:00:01 +0800
Subject: [PATCH] Bump version to v1.0.0rc4. (#1243)
* Bump version to v1.0.0rc4
* Update according to comments
---
README.md | 10 +++++-----
README_zh-CN.md | 15 +++++----------
docker/serve/Dockerfile | 4 ++--
docs/en/notes/changelog.md | 27 +++++++++++++++++++++++++++
docs/en/notes/faq.md | 2 +-
docs/zh_CN/notes/faq.md | 2 +-
mmcls/version.py | 2 +-
7 files changed, 42 insertions(+), 20 deletions(-)
diff --git a/README.md b/README.md
index a8bf52d1..e75daf82 100644
--- 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/).
diff --git a/README_zh-CN.md b/README_zh-CN.md
index 3f7234f3..01c728c7 100644
--- 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。
diff --git a/docker/serve/Dockerfile b/docker/serve/Dockerfile
index fa0766e6..7c254f20 100644
--- 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
diff --git a/docs/en/notes/changelog.md b/docs/en/notes/changelog.md
index 3b07c892..1baaf185 100644
--- 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
diff --git a/docs/en/notes/faq.md b/docs/en/notes/faq.md
index b390b10e..9d2c7643 100644
--- 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 |
diff --git a/docs/zh_CN/notes/faq.md b/docs/zh_CN/notes/faq.md
index 450214ae..d528b048 100644
--- 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 |
diff --git a/mmcls/version.py b/mmcls/version.py
index 5e6347a5..6a6b4cae 100644
--- 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):