Bump version to v0.14.0 (#389)

README.md

@@ -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

README_zh-CN.md

@@ -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)
 

docker/serve/Dockerfile

@@ -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
 

docs/changelog.md

@@ -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.

docs/install.md

@@ -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 |

docs_zh-CN/install.md

@@ -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          |
@@ -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

mmcls/__init__.py

@@ -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__)
 

mmcls/version.py

@@ -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):

requirements/readthedocs.txt

@@ -1,3 +1,3 @@
-mmcv>=1.3.0
+mmcv>=1.3.8
 torch
 torchvision