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Bump version to v0.14.0 (#389)
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mzr1996 authored Aug 4, 2021
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -31,7 +31,7 @@ This project is released under the [Apache 2.0 license](LICENSE).

## Changelog

v0.12.0 was released in 3/6/2021.
v0.14.0 was released in 4/8/2021.
Please refer to [changelog.md](docs/changelog.md) for details and release history.

## Benchmark and model zoo
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2 changes: 1 addition & 1 deletion README_zh-CN.md
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Expand Up @@ -30,7 +30,7 @@ MMClassification 是一款基于 PyTorch 的开源图像分类工具箱,是 [O

## 更新日志

2021/6/3 发布了 v0.12.0 版本
2021/8/4 发布了 v0.14.0 版本

发布历史和更新细节请参考 [更新日志](docs/changelog.md)

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4 changes: 2 additions & 2 deletions docker/serve/Dockerfile
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Expand Up @@ -3,8 +3,8 @@ ARG CUDA="10.1"
ARG CUDNN="7"
FROM pytorch/pytorch:${PYTORCH}-cuda${CUDA}-cudnn${CUDNN}-devel

ARG MMCV="1.3.1"
ARG MMCLS="0.12.0"
ARG MMCV="1.3.8"
ARG MMCLS="0.14.0"

ENV PYTHONUNBUFFERED TRUE

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33 changes: 33 additions & 0 deletions docs/changelog.md
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@@ -1,5 +1,38 @@
## Changelog

### v0.14.0(4/8/2021)

#### Highlights
- Add transformer-in-transformer backbone and pretrain checkpoints, refers to [the paper](https://arxiv.org/abs/2103.00112).
- Add Chinese colab tutorial.
- Provide dockerfile to build mmcls dev docker image.

#### New Features

- Add transformer in transformer backbone and pretrain checkpoints. ([#339](https://github.com/open-mmlab/mmclassification/pull/339))
- Support mim, welcome to use mim to manage your mmcls project. ([#376](https://github.com/open-mmlab/mmclassification/pull/376))
- Add Dockerfile. ([#365](https://github.com/open-mmlab/mmclassification/pull/365))
- Add ResNeSt configs. ([#332](https://github.com/open-mmlab/mmclassification/pull/332))

#### Improvements

- Use the `presistent_works` option if available, to accelerate training. ([#349](https://github.com/open-mmlab/mmclassification/pull/349))
- Add Chinese ipynb tutorial. ([#306](https://github.com/open-mmlab/mmclassification/pull/306))
- Refactor unit tests. ([#321](https://github.com/open-mmlab/mmclassification/pull/321))
- Support to test mmdet inference with mmcls backbone. ([#343](https://github.com/open-mmlab/mmclassification/pull/343))
- Use zero as default value of `thrs` in metrics. ([#341](https://github.com/open-mmlab/mmclassification/pull/341))

#### Bug Fixes

- Fix ImageNet dataset annotation file parse bug. ([#370](https://github.com/open-mmlab/mmclassification/pull/370))
- Fix docstring typo and init bug in ShuffleNetV1. ([#374](https://github.com/open-mmlab/mmclassification/pull/374))
- Use local ATTENTION registry to avoid conflict with other repositories. ([#376](https://github.com/open-mmlab/mmclassification/pull/375))
- Fix swin transformer config bug. ([#355](https://github.com/open-mmlab/mmclassification/pull/355))
- Fix `patch_cfg` argument bug in SwinTransformer. ([#368](https://github.com/open-mmlab/mmclassification/pull/368))
- Fix duplicate `init_weights` call in ViT init function. ([#373](https://github.com/open-mmlab/mmclassification/pull/373))
- Fix broken `_base_` link in a resnet config. ([#361](https://github.com/open-mmlab/mmclassification/pull/361))
- Fix vgg-19 model link missing. ([#363](https://github.com/open-mmlab/mmclassification/pull/363))

### v0.13.0(3/7/2021)

- Support Swin-Transformer backbone and add training configs for Swin-Transformer on ImageNet.
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1 change: 1 addition & 0 deletions docs/install.md
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Expand Up @@ -11,6 +11,7 @@ The compatible MMClassification and MMCV versions are as below. Please install t
| MMClassification version | MMCV version |
|:------------------------:|:--------------------:|
| master | mmcv>=1.3.8, <=1.5.0 |
| 0.14.0 | mmcv>=1.3.8, <=1.5.0 |
| 0.13.0 | mmcv>=1.3.8, <=1.5.0 |
| 0.12.0 | mmcv>=1.3.1, <=1.5.0 |
| 0.11.1 | mmcv>=1.3.1, <=1.5.0 |
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9 changes: 5 additions & 4 deletions docs_zh-CN/install.md
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Expand Up @@ -10,8 +10,9 @@ MMClassification 和 MMCV 的适配关系如下,请安装正确版本的 MMCV

| MMClassification 版本 | MMCV 版本 |
|:---------------------:|:--------------------:|
| master | mmcv>=1.3.6, <=1.5.0 |
| 0.13.0 | mmcv>=1.3.6, <=1.5.0 |
| master | mmcv>=1.3.8, <=1.5.0 |
| 0.14.0 | mmcv>=1.3.8, <=1.5.0 |
| 0.13.0 | mmcv>=1.3.8, <=1.5.0 |
| 0.12.0 | mmcv>=1.3.1, <=1.5.0 |
| 0.11.1 | mmcv>=1.3.1, <=1.5.0 |
| 0.11.0 | mmcv>=1.3.0 |
Expand Down Expand Up @@ -107,9 +108,9 @@ MMClassification 提供 [Dockerfile](/docker/Dockerfile) ,可以通过以下
docker build -f ./docker/Dockerfile --rm -t mmcls:torch1.6.0-cuda10.1-cudnn7 .
```

**注意:** 确保已经安装了 [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker).
**注意** 确保已经安装了 [nvidia-container-toolkit](https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker).

运行一个基于上述镜像的容器:
运行一个基于上述镜像的容器

```shell
docker run --gpus all --shm-size=8g -it -v {DATA_DIR}:/workspace/mmclassification/data mmcls:torch1.6.0-cuda10.1-cudnn7 /bin/bash
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2 changes: 1 addition & 1 deletion mmcls/__init__.py
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Expand Up @@ -15,7 +15,7 @@ def digit_version(version_str):
return digit_version


mmcv_minimum_version = '1.3.1'
mmcv_minimum_version = '1.3.8'
mmcv_maximum_version = '1.5.0'
mmcv_version = digit_version(mmcv.__version__)

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2 changes: 1 addition & 1 deletion mmcls/version.py
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@@ -1,6 +1,6 @@
# Copyright (c) Open-MMLab. All rights reserved.

__version__ = '0.13.0'
__version__ = '0.14.0'


def parse_version_info(version_str):
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2 changes: 1 addition & 1 deletion requirements/readthedocs.txt
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@@ -1,3 +1,3 @@
mmcv>=1.3.0
mmcv>=1.3.8
torch
torchvision

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