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

* Update according to comments
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mzr1996 committed Dec 6, 2022
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10 changes: 5 additions & 5 deletions README.md
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Expand Up @@ -58,18 +58,18 @@ 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).
- Add **TIMM and HuggingFace** wrappers. Now you can train/use models in TIMM/HuggingFace directly, see [#1102](https://github.com/open-mmlab/mmclassification/pull/1102).
- 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/).

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15 changes: 5 additions & 10 deletions README_zh-CN.md
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Expand Up @@ -57,23 +57,18 @@ 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
- 添加了 **TIMM 和 HuggingFace** 包装器,现在我们可以直接训练、使用 TIMM 和 HuggingFace 中的模型
- 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。
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4 changes: 2 additions & 2 deletions docker/serve/Dockerfile
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Expand Up @@ -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

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27 changes: 27 additions & 0 deletions docs/en/notes/changelog.md
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# 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
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2 changes: 1 addition & 1 deletion docs/en/notes/faq.md
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Expand Up @@ -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 |
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2 changes: 1 addition & 1 deletion docs/zh_CN/notes/faq.md
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Expand Up @@ -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 |
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2 changes: 1 addition & 1 deletion mmcls/version.py
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# Copyright (c) OpenMMLab. All rights reserved

__version__ = '1.0.0rc3'
__version__ = '1.0.0rc4'


def parse_version_info(version_str):
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