.travis.yml

language: python

python:
  - "3.7"

env:
  - PYTORCH_CHANNEL=pytorch
  - PYTORCH_CHANNEL=pytorch-nightly

stages:
  - Lint check
  - Test
  - Docs
  - Deploy
  - Nightly

before_install: &before_install
  - sudo apt-get update
  - wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh;
  - bash miniconda.sh -b -p $HOME/miniconda
  - export PATH="$HOME/miniconda/bin:$PATH"
  - hash -r
  - conda config --set always_yes yes --set changeps1 no
  - conda update -q conda
  # Useful for debugging any issues with conda
  - conda info -a
  - conda create -q -n test-environment pytorch cpuonly torchvision python=$TRAVIS_PYTHON_VERSION -c $PYTORCH_CHANNEL
  - source activate test-environment
  # Test contrib dependencies
  - pip install tqdm scikit-learn matplotlib tensorboardX visdom polyaxon-client mlflow neptune-client tensorboard pynvml

install:
  - python setup.py install
  - pip install numpy pytest codecov pytest-cov pytest-xdist
  # Examples dependencies
  - pip install pandas
  - pip install gym

script:
  - CUDA_VISIBLE_DEVICES="" py.test --tx 4*popen//python=python$TRAVIS_PYTHON_VERSION --cov ignite --cov-report term-missing -vvv tests/
  # Run test on cuda device
  # As no GPUs on travis -> all tests will be skipped
  - CUDA_VISIBLE_DEVICES=0 py.test --cov ignite --cov-append --cov-report term-missing -vvv tests/ -k "on_cuda"

  # Smoke tests for the examples
  # Mnist
  # 1) mnist.py
  - python examples/mnist/mnist.py --epochs=1
  # 2) mnist_with_visdom.py
  - python -c "from visdom.server import download_scripts; download_scripts()" # download scripts : https://github.com/facebookresearch/visdom/blob/master/py/server.py#L929
  - python -m visdom.server &
  - sleep 10
  - python examples/mnist/mnist_with_visdom.py --epochs=1
  - kill %1
  # 3) mnist_with_tensorboardx.py
  - python examples/mnist/mnist_with_tensorboardx.py --epochs=1
  # 4) mnist_save_resume_engine.py
  - python examples/mnist/mnist_save_resume_engine.py --epochs=1 --crash_iteration 700
  - python examples/mnist/mnist_save_resume_engine.py --epochs=1 --resume_from=/tmp/mnist_save_resume/checkpoint_550.pth

  # dcgan.py
  - python examples/gan/dcgan.py --dataset fake --dataroot /tmp/fakedata --output-dir /tmp/outputs-dcgan --batch-size 2 --epochs 2  --workers 0

  # RL
  # 1) Actor-Critic
  - python examples/reinforcement_learning/actor_critic.py --max-episodes=2
  # 2) Reinforce
  - python examples/reinforcement_learning/reinforce.py --max-episodes=2

  #fast-neural-style
  #train
  - mkdir -p /home/travis/.cache/torch/checkpoints/ && wget "https://download.pytorch.org/models/vgg16-397923af.pth" -O/home/travis/.cache/torch/checkpoints/vgg16-397923af.pth
  - python examples/fast_neural_style/neural_style.py train --epochs 1 --cuda 0 --dataset test --dataroot . --image_size 32 --style_image examples/fast_neural_style/images/style_images/mosaic.jpg --style_size 32

  # tests for distributed ops
  # As no GPUs on travis -> all tests will be skipped
  # 2 is the number of processes <-> number of available GPUs
  - export WORLD_SIZE=2
  - py.test --cov ignite --cov-append --cov-report term-missing --dist=each --tx $WORLD_SIZE*popen//python=python$TRAVIS_PYTHON_VERSION tests -m distributed -vvv

after_success:
  - codecov

jobs:
  include:
    - stage: Lint check
      python: "3.7"
      before_install: # Nothing to do
      install: pip install flake8
      script: flake8
      after_success: # Nothing to do

    # GitHub Pages Deployment: https://docs.travis-ci.com/user/deployment/pages/
    - stage: Docs
      python: "3.7"
      if: type != cron
      # Use previously defined before_install
      before_install: *before_install

      install:
        - pip install -r docs/requirements.txt
        - pip install git+https://github.com/vfdev-5/sphinxcontrib-versioning.git

      script:
        - sphinx-versioning --use-master-conf --use-master-templates build --greatest-tag --whitelist-branches master docs/source docs/build/html
        # Create .nojekyll file to serve correctly _static and friends
        - touch docs/build/html/.nojekyll
      after_success: # Nothing to do

      # Deploy built docs : a) when PR is merged to master, b) when a tag is built
      deploy:
        - provider: pages
          skip-cleanup: true
          github-token: $GITHUB_TOKEN # Set in the settings page of your repository, as a secure variable
          keep-history: false
          local_dir: docs/build/html
          on:
            branch: master
        - provider: pages
          skip-cleanup: true
          github-token: $GITHUB_TOKEN # Set in the settings page of your repository, as a secure variable
          keep-history: false
          local_dir: docs/build/html
          on:
            tags: true

    - stage: Deploy
      python: "3.7"
      env:
        - PYTORCH_CHANNEL=pytorch
      if: tag IS present

      # Use previously defined before_install
      before_install: *before_install

      install:
        - python setup.py install

      script: true

      after_success: # Nothing to do

      before_deploy:
        # Conda deploy if on tag
        # ANACONDA_TOKEN should be provided by Travis
        # How to generate ANACONDA_TOKEN: https://docs.anaconda.com/anaconda-cloud/user-guide/tasks/work-with-accounts#creating-access-tokens

        # https://conda.io/docs/user-guide/tasks/build-packages/install-conda-build.html
        - conda install -y conda-build conda-verify anaconda-client
        - conda config --set anaconda_upload no
        - travis_wait 60 conda build --quiet --no-test --output-folder conda_build conda.recipe
        # Convert to other platforms: OSX, WIN
        - conda convert --platform win-64 conda_build/linux-64/*.tar.bz2 -o conda_build/
        - conda convert --platform osx-64 conda_build/linux-64/*.tar.bz2 -o conda_build/
        # Upload to Anaconda
        # We could use --all but too much platforms to uploaded
        - ls conda_build/*/*.tar.bz2 | xargs -I {} anaconda -v -t $ANACONDA_TOKEN upload -u pytorch {}

      # PyPI Deployment: https://docs.travis-ci.com/user/deployment/pypi/
      deploy:
        provider: pypi

        user: $PYPI_USER
        # If password contains non alphanumeric characters
        # https://github.com/travis-ci/dpl/issues/377
        # pass it as secured variable
        password: $PYPI_TOKEN
        # otherwise, follow "How to encrypt the password": https://docs.travis-ci.com/user/encryption-keys/
        # `travis encrypt deploy.password="password"`
        #  secure: "secured_password"

        skip_cleanup: true

        distributions: "sdist bdist_wheel"

        on:
          tags: true

    - stage: Nightly
      python: "3.7"
      if: type = cron
      env:
        - PYTORCH_CHANNEL=pytorch-nightly
      # Use previously defined before_install
      before_install: *before_install
      install:
        - sed -i "s/__version__ = '\(.*\)'/__version__ = '\1.dev$(date -u +%Y%m%d)'/g" ignite/__init__.py
      script: true
      after_success: # Nothing to do
      before_deploy:
        # ANACONDA_TOKEN should be provided by Travis
        # How to generate ANACONDA_TOKEN: https://docs.anaconda.com/anaconda-cloud/user-guide/tasks/work-with-accounts#creating-access-tokens
        # https://conda.io/docs/user-guide/tasks/build-packages/install-conda-build.html
        - conda install -y conda-build conda-verify anaconda-client
        - conda config --set anaconda_upload no
        - travis_wait 60 conda build --quiet --no-test --output-folder conda_build conda.recipe -c pytorch
        # Convert to other platforms: OSX, WIN
        - conda convert --platform win-64 conda_build/linux-64/*.tar.bz2 -o conda_build/
        - conda convert --platform osx-64 conda_build/linux-64/*.tar.bz2 -o conda_build/
        # Upload to Anaconda
        # We could use --all but too much platforms to uploaded
        - ls conda_build/*/*.tar.bz2 | xargs -I {} anaconda -v -t $ANACONDA_TOKEN upload -u pytorch-nightly {}

      # PyPI Deployment: https://docs.travis-ci.com/user/deployment/pypi/
      deploy:
        provider: pypi
        user: $PYPI_USER
        # If password contains non alphanumeric characters
        # https://github.com/travis-ci/dpl/issues/377
        # pass it as secured variable
        password: $PYPI_TOKEN
        # otherwise, follow "How to encrypt the password": https://docs.travis-ci.com/user/encryption-keys/
        # `travis encrypt deploy.password="password"`
        #  secure: "secured_password"
        skip_cleanup: true
        distributions: "sdist bdist_wheel"
        on:
          branch:
            - master