.travis.yml

language: python
python:
  - "3.6"
 # - "2.7"

# cache:
#   directories:
#     - $HOME/.torch

stages:
#  - lint_check
  - test
#  - docs

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:$PATH"
  - hash -r
  - conda config --set always_yes yes --set changeps1 no
  - conda update -q conda
  # Useful for debugging any issues with conda
  - conda info -a
  - conda create -q -n test-environment -c pytorch python=$TRAVIS_PYTHON_VERSION numpy mock pytorch-cpu
  - if [[ $TRAVIS_PYTHON_VERSION == 2.7 ]]; then pip install enum34; fi
  - source activate test-environment
  - python setup.py install
  - pip install --upgrade pytest #codecov pytest-cov
  # Test contrib dependencies
  # - pip install scikit-learn
  # Examples dependencies
  - pip install -r requirements.txt
  #visdom torchvision tensorboardX
  #- pip install gym
  #- pip install tqdm

script:
  - python -m pytest -s tests #--cov pretrainedmodels --cov-report term-missing

  # 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

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

  # #fast-neural-style
  # #train
  # - 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

after_success:
  # Ignore codecov failures as the codecov server is not
  # very reliable but we don't want travis to report a failure
  # in the github UI just because the coverage report failed to
  # be published.
  - codecov || echo "codecov upload failed"

# jobs:
#   include:
#     - stage: lint_check
#       python: "3.6"
#       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: "3.6"
#       install:
#         # Minimal install : ignite and dependencies just to build the docs
#         - pip install -r docs/requirements.txt
#         - pip install http://download.pytorch.org/whl/cpu/torch-0.4.1-cp35-cp35m-linux_x86_64.whl
#         # Add contrib dependencies (otherwise doc is not built)
#         - pip install scikit-learn scipy
#         # `pip install .` vs `python setup.py install` : 1st works better to produce _module/ignite with source links
#         - pip install .
#       script:
#         - cd docs && make html
#         # Create .nojekyll file to serve correctly _static and friends
#         - touch build/html/.nojekyll
#       after_success: # Nothing to do
#       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