unittests.yml

on: [push, pull_request]

jobs:
  build:
    runs-on: ubuntu-latest
    strategy:
      max-parallel: 10
      fail-fast: false
      matrix:
        python-version: [3.5, 3.6, 3.7, 3.8]
        pytorch-channel: [pytorch, pytorch-nightly]
        exclude:
          # excludes pytorch-nightly python 3.5 as it was dropped
          - pytorch-channel: pytorch-nightly
            python-version: 3.5

    steps:
    - uses: actions/checkout@v2
    - name: Setup Conda
      run: |
        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:$PATH"
        conda config --set always_yes yes --set changeps1 no
        conda update -q conda
        # Useful for debugging any issues with conda
        conda info -a
        conda create -q -n test-environment pytorch cpuonly python=${{ matrix.python-version }} -c ${{ matrix.pytorch-channel }}
        
    - name: Install dependencies
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        # Keep fix in case of problem with torchvision nightly releases
        # if [[ "${{ matrix.pytorch-channel }}" == "pytorch-nightly" ]]; then pip install --upgrade git+https://github.com/pytorch/vision.git; else conda install torchvision cpuonly python=${{ matrix.python-version }} -c ${{ matrix.pytorch-channel }}; fi
        conda install torchvision cpuonly python=${{ matrix.python-version }} -c ${{ matrix.pytorch-channel }}
        pip install -r requirements-dev.txt
        python setup.py install

    - name: Run Tests
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        CUDA_VISIBLE_DEVICES="" py.test --tx 4*popen//python=python${{ matrix.python-version }} --cov ignite --cov-report term-missing -vvv tests/
        # tests for distributed ops
        export WORLD_SIZE=2
        py.test --cov ignite --cov-append --cov-report term-missing --dist=each --tx $WORLD_SIZE*popen//python=python${{ matrix.python-version }} tests -m distributed -vvv

    - name: Run MNIST Examples
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        # 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
        # 3.1) mnist_with_tensorboard.py with tbX
        python examples/mnist/mnist_with_tensorboard.py --epochs=1
        # 3.2) mnist_with_tensorboard.py with native torch tb
        pip uninstall -y tensorboardX
        python examples/mnist/mnist_with_tensorboard.py --epochs=1

    - name: Run MNIST Example With Crash
      continue-on-error: true
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        # 4) mnist_save_resume_engine.py
        python examples/mnist/mnist_save_resume_engine.py --epochs=2 --crash_iteration 1100
        
    - name: Resume MNIST from previous crash
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        python examples/mnist/mnist_save_resume_engine.py --epochs=2 --resume_from=/tmp/mnist_save_resume/checkpoint_1.pt

    - name: Run GAN example
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        # DCGAN
        python examples/gan/dcgan.py --dataset fake --dataroot /tmp/fakedata --output-dir /tmp/outputs-dcgan --batch-size 2 --epochs 2  --workers 0
    
    - name: Run RL Examples
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        # 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

    - name: Run Neural Style Example
      run: |
        export PATH="$HOME/miniconda/bin:$PATH"
        source activate test-environment
        #fast-neural-style
        #train
        mkdir -p ~/.cache/torch/checkpoints/ && wget "https://download.pytorch.org/models/vgg16-397923af.pth" -O ~/.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