Add pypi deployment (#11)

* add pypi deployment

* remove useless jobs

* fixed typo and cleanup

* delete build.tx

* add change log

Co-authored-by: Jiarui XU <xvjiarui0826@gmail.com>

.github/CONTRIBUTING.md

@@ -27,7 +27,7 @@ We use the following tools for linting and formatting:
 - [yapf](https://github.com/google/yapf): formatter
 - [isort](https://github.com/timothycrosley/isort): sort imports
 
-Style configurations of yapf and isort can be found in [.style.yapf](../.style.yapf) and [.isort.cfg](../.isort.cfg).
+Style configurations of yapf and isort can be found in [setup.cfg](../setup.cfg) and [.isort.cfg](../.isort.cfg).
 
 We use [pre-commit hook](https://pre-commit.com/) that checks and formats for `flake8`, `yapf`, `isort`, `trailing whitespaces`,
  fixes `end-of-files`, sorts `requirments.txt` automatically on every commit.

.github/workflows/build.yml

@@ -1,12 +1,8 @@
-# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
-# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
-
 name: build
 
 on: [push, pull_request]
 
 jobs:
-
   lint:
     runs-on: ubuntu-latest
     steps:
@@ -53,49 +49,49 @@ jobs:
             python-version: 3.7
 
     steps:
-    - uses: actions/checkout@v2
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install CUDA
-      if: ${{matrix.torch == '1.5.0+cu101'}}
-      run: |
-        export INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
-        wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}
-        sudo dpkg -i ${INSTALLER}
-        wget https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub
-        sudo apt-key add 7fa2af80.pub
-        sudo apt update -qq
-        sudo apt install -y cuda-${CUDA_SHORT/./-} cuda-cufft-dev-${CUDA_SHORT/./-}
-        sudo apt clean
-        export CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
-        export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${CUDA_HOME}/include:${LD_LIBRARY_PATH}
-        export PATH=${CUDA_HOME}/bin:${PATH}
-        sudo apt-get install -y ninja-build
-    - name: Install Pillow
-      if: ${{matrix.torchvision == '0.4.2+cpu'}}
-      run: pip install Pillow==6.2.2
-    - name: Install PyTorch
-      run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
-    - name: Install mmseg dependencies
-      run: |
-        pip install mmcv-full==latest+torch${{matrix.torch}} -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-        pip install -r requirements.txt
-    - name: Build and install
-      run: rm -rf .eggs && pip install -e .
-    - name: Run unittests and generate coverage report
-      run: |
-        coverage run --branch --source mmseg -m pytest tests/
-        coverage xml
-        coverage report -m --omit="mmseg/utils/*","mmseg/apis/*"
-    # Only upload coverage report for python3.7 && pytorch1.5
-    - name: Upload coverage to Codecov
-      if: ${{matrix.torch == '1.5.0+cu101' && matrix.python-version == '3.7'}}
-      uses: codecov/codecov-action@v1.0.10
-      with:
-        file: ./coverage.xml
-        flags: unittests
-        env_vars: OS,PYTHON
-        name: codecov-umbrella
-        fail_ci_if_error: false
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install CUDA
+        if: ${{matrix.torch == '1.5.0+cu101'}}
+        run: |
+          export INSTALLER=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
+          wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${INSTALLER}
+          sudo dpkg -i ${INSTALLER}
+          wget https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub
+          sudo apt-key add 7fa2af80.pub
+          sudo apt update -qq
+          sudo apt install -y cuda-${CUDA_SHORT/./-} cuda-cufft-dev-${CUDA_SHORT/./-}
+          sudo apt clean
+          export CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
+          export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${CUDA_HOME}/include:${LD_LIBRARY_PATH}
+          export PATH=${CUDA_HOME}/bin:${PATH}
+          sudo apt-get install -y ninja-build
+      - name: Install Pillow
+        if: ${{matrix.torchvision == '0.4.2+cpu'}}
+        run: pip install Pillow==6.2.2
+      - name: Install PyTorch
+        run: pip install torch==${{matrix.torch}} torchvision==${{matrix.torchvision}} -f https://download.pytorch.org/whl/torch_stable.html
+      - name: Install mmseg dependencies
+        run: |
+          pip install mmcv-full==latest+torch${{matrix.torch}} -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
+          pip install -r requirements.txt
+      - name: Build and install
+        run: rm -rf .eggs && pip install -e .
+      - name: Run unittests and generate coverage report
+        run: |
+          coverage run --branch --source mmseg -m pytest tests/
+          coverage xml
+          coverage report -m
+      # Only upload coverage report for python3.7 && pytorch1.5
+      - name: Upload coverage to Codecov
+        if: ${{matrix.torch == '1.5.0+cu101' && matrix.python-version == '3.7'}}
+        uses: codecov/codecov-action@v1.0.10
+        with:
+          file: ./coverage.xml
+          flags: unittests
+          env_vars: OS,PYTHON
+          name: codecov-umbrella
+          fail_ci_if_error: false

.github/workflows/deploy.yml

@@ -0,0 +1,20 @@
+name: deploy
+
+on: push
+
+jobs:
+  build-n-publish:
+    runs-on: ubuntu-latest
+    if: startsWith(github.event.ref, 'refs/tags')
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python 3.7
+        uses: actions/setup-python@v2
+        with:
+          python-version: 3.7
+      - name: Build MMSegmentation
+        run: python setup.py sdist bdist_wheel
+      - name: Publish distribution to PyPI
+        run: |
+          pip install twine
+          twine upload dist/* -u __token__ -p ${{ secrets.pypi_password }}

.style.yapf

@@ -1,4 +0,0 @@
-[style]
-BASED_ON_STYLE = pep8
-BLANK_LINE_BEFORE_NESTED_CLASS_OR_DEF = true
-SPLIT_BEFORE_EXPRESSION_AFTER_OPENING_PAREN = true

README.md

@@ -41,6 +41,10 @@ The master branch works with **PyTorch 1.3 to 1.5**.
 
 This project is released under the [Apache 2.0 license](LICENSE).
 
+## Changelog
+
+v0.5.0 was released in 10/7/2020.
+
 ## Benchmark and model zoo
 
 Results and models are available in the [model zoo](docs/model_zoo.md).

docs/install.md

@@ -18,41 +18,31 @@ conda activate open-mmlab
 
 b. Install PyTorch and torchvision following the [official instructions](https://pytorch.org/).
 Here we use PyTorch 1.5.0 and CUDA 10.1.
-You may also switch to other version by specifying version number.
+You may also switch to other version by specifying the version number.
 
 ```shell
 conda install pytorch=1.5.0 torchvision cudatoolkit=10.1 -c pytorch
 ```
 
-c. Clone the mmsegmentation repository.
+c. Install [MMCV](https://mmcv.readthedocs.io/en/latest/) following the [official instructions](https://mmcv.readthedocs.io/en/latest/#installation).
+Either `mmcv` or `mmcv-full` is compatible with MMSegmentation, but for methods like CCNet and PSANet, CUDA ops in `mmcv-full` is required
+
+The pre-build mmcv-full (with PyTorch 1.5 and CUDA 10.1) can be installed by running: (other available versions could be found [here](https://mmcv.readthedocs.io/en/latest/#install-with-pip))
 
 ```shell
-git clone http://github.com/open-mmlab/mmsegmentation
-cd mmsegmentation
-```
-
-d. Install [MMCV](https://mmcv.readthedocs.io/en/latest/).
-Either *mmcv* or *mmcv-full* is compatible with MMSegmentation, but for methods like CCNet and PSANet, CUDA ops in *mmcv-full* is required
-
-The pre-build *mmcv-full* could be installed by running: (available versions could be found [here](https://mmcv.readthedocs.io/en/latest/#install-with-pip))
-```
 pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
 ```
 
-Optionally, you could also install lite version by running:
-```
-pip install mmcv
-```
-or build full version from source:
-```
-pip install mmcv-full
-```
-
-e. Install build requirements and then install MMSegmentation.
+d. Install MMSegmentation.
 
 ```shell
-pip install -r requirements/build.txt  # or "pip install -r requirements.txt" for everything.
-pip install -e .  # or "python setup.py develop"
+pip install mmseg # install the latest release
+```
+
+or
+
+```shell
+pip install git+https://github.com/open-mmlab/mmsegmentation.git # install the master branch
 ```
 
 Note:
@@ -68,7 +58,6 @@ you can install it before installing MMCV.
 4. Some dependencies are optional. Simply running `pip install -e .` will only install the minimum runtime requirements.
 To use optional dependencies like `cityscapessripts`  either install them manually with `pip install -r requirements/optional.txt` or specify desired extras when calling `pip` (e.g. `pip install -e .[optional]`). Valid keys for the extras field are: `all`, `tests`, `build`, and `optional`.
 
-
 ### A from-scratch setup script
 
 Here is a full script for setting up mmsegmentation with conda and link the dataset path (supposing that your dataset path is $DATA_ROOT).
@@ -78,11 +67,8 @@ conda create -n open-mmlab python=3.7 -y
 conda activate open-mmlab
 
 conda install pytorch=1.5.0 torchvision cudatoolkit=10.1 -c pytorch
-git clone http://github.com/open-mmlab/mmsegmentation
-cd mmsegmentation
 pip install mmcv-full==latest+torch1.5.0+cu101 -f https://openmmlab.oss-accelerate.aliyuncs.com/mmcv/dist/index.html
-pip install -r requirements/build.txt
-pip install -e .
+pip install git+https://github.com/open-mmlab/mmsegmentation.git
 
 mkdir data
 ln -s $DATA_ROOT data

docs/model_zoo.md

@@ -35,7 +35,7 @@ Please refer to [PSPNet](https://github.com/open-mmlab/mmsegmentation/blob/maste
 
 ### DeepLabV3
 
-Please refer to [DeepLabV3](https://github.com/open-mmlab/mmsegmentatio/blob/master/configs/deeplabv3) for details.
+Please refer to [DeepLabV3](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3) for details.
 
 ### PSANet
 
@@ -43,7 +43,7 @@ Please refer to [PSANet](https://github.com/open-mmlab/mmsegmentation/blob/maste
 
 ### DeepLabV3+
 
-Please refer to [DeepLabV3+](https://github.com/open-mmlab/mmsegmentatio/blob/master/configs/deeplabv3plus) for details.
+Please refer to [DeepLabV3+](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/deeplabv3plus) for details.
 
 ### UPerNet
 
@@ -51,11 +51,11 @@ Please refer to [UPerNet](https://github.com/open-mmlab/mmsegmentation/blob/mast
 
 ### NonLocal Net
 
-Please refer to [NonLocal Net](https://github.com/open-mmlab/mmsegmentatio/blob/master/configs/nlnet) for details.
+Please refer to [NonLocal Net](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/nlnet) for details.
 
 ### EncNet
 
-Please refer to [NonLocal Net](https://github.com/open-mmlab/mmsegmentatio/blob/master/configs/encnet) for details.
+Please refer to [NonLocal Net](https://github.com/open-mmlab/mmsegmentation/blob/master/configs/encnet) for details.
 
 ### CCNet
 

mmseg/__init__.py

@@ -1,3 +1,3 @@
-from .version import __version__, short_version
+from .version import __version__, short_version, version_info
 
-__all__ = ['__version__', 'short_version']
+__all__ = ['__version__', 'short_version', 'version_info']

requirements.txt

@@ -1,4 +1,3 @@
--r requirements/build.txt
 -r requirements/optional.txt
 -r requirements/runtime.txt
 -r requirements/tests.txt

requirements/build.txt

@@ -1,2 +0,0 @@
-# These must be installed before building mmsegmentation
-numpy

requirements/tests.txt

@@ -1,4 +1,3 @@
-asynctest
 codecov
 flake8
 interrogate

setup.py

@@ -1,13 +1,8 @@
-#!/usr/bin/env python
 import os
 import subprocess
 import time
 from setuptools import find_packages, setup
 
-import torch
-from mmcv.utils.parrots_wrapper import (BuildExtension, CppExtension,
-                                        CUDAExtension)
-
 
 def readme():
     with open('README.md', encoding='utf-8') as f:
@@ -85,32 +80,6 @@ def get_version():
     return locals()['__version__']
 
 
-def make_cuda_ext(name, module, sources, sources_cuda=[]):
-
-    define_macros = []
-    extra_compile_args = {'cxx': []}
-
-    if torch.cuda.is_available() or os.getenv('FORCE_CUDA', '0') == '1':
-        define_macros += [('WITH_CUDA', None)]
-        extension = CUDAExtension
-        extra_compile_args['nvcc'] = [
-            '-D__CUDA_NO_HALF_OPERATORS__',
-            '-D__CUDA_NO_HALF_CONVERSIONS__',
-            '-D__CUDA_NO_HALF2_OPERATORS__',
-        ]
-        sources += sources_cuda
-    else:
-        print('Compiling {} without CUDA'.format(name))
-        extension = CppExtension
-        # raise EnvironmentError('CUDA is required to compile MMSegmentation!')
-
-    return extension(
-        name='{}.{}'.format(module, name),
-        sources=[os.path.join(*module.split('.'), p) for p in sources],
-        define_macros=define_macros,
-        extra_compile_args=extra_compile_args)
-
-
 def parse_requirements(fname='requirements.txt', with_version=True):
     """Parse the package dependencies listed in a requirements file but strips
     specific versioning information.
@@ -199,7 +168,6 @@ if __name__ == '__main__':
         keywords='computer vision, semantic segmentation',
         url='http://github.com/open-mmlab/mmsegmentation',
         packages=find_packages(exclude=('configs', 'tools', 'demo')),
-        package_data={'mmseg.ops': ['*/*.so']},
         classifiers=[
             'Development Status :: 4 - Beta',
             'License :: OSI Approved :: Apache Software License',
@@ -219,5 +187,4 @@ if __name__ == '__main__':
             'optional': parse_requirements('requirements/optional.txt'),
         },
         ext_modules=[],
-        cmdclass={'build_ext': BuildExtension},
         zip_safe=False)