.travis.yml

dist: trusty
language: python
python:
  - "2.7"
  - "3.4"
  - "3.6"
services:
  - docker

before_install:
  # force latest Debian for Python 3.6 and nightly TensorFlow which requires new glibc
  - |
    if [[ $TRAVIS_PYTHON_VERSION == "3.6" || $TF_PACKAGE == "tf-nightly" ]]; then
      export DEBIAN=sid
    else
      export DEBIAN=jessie
    fi
  - docker pull debian:$DEBIAN
  # run docker container for an hour
  - docker run -v `pwd`:/horovod debian:$DEBIAN /bin/sh -c "sleep 3600" &
  # wait for docker to start
  - sleep 5
  - export CONTAINER=$(docker ps -q | head -n 1)
  - docker exec $CONTAINER /bin/sh -c "apt-get update -qq"
  # install Python, if it's Python 3 - add symlink for `python`
  - |
    if [[ $TRAVIS_PYTHON_VERSION == 3* ]]; then
      docker exec $CONTAINER /bin/sh -c "apt-get install -y python$TRAVIS_PYTHON_VERSION python3-pip"
      docker exec $CONTAINER /bin/sh -c "pip3 install -U --force pip"
      docker exec $CONTAINER /bin/sh -c "ln -s /usr/bin/python3 /usr/bin/python"
    else
      docker exec $CONTAINER /bin/sh -c "apt-get install -y python$TRAVIS_PYTHON_VERSION python-pip"
      docker exec $CONTAINER /bin/sh -c "pip install -U --force pip"
    fi
  # install necessary network tools
  - docker exec $CONTAINER /bin/sh -c "apt-get install -y wget openssh-client git"

env:
  matrix:
    - TF_PACKAGE=tensorflow==1.1.0 KERAS_PACKAGE=keras==2.0.0 MPI=OpenMPI
    - TF_PACKAGE=tensorflow==1.4.0 KERAS_PACKAGE=keras==2.1.2 MPI=OpenMPI
    - TF_PACKAGE=tf-nightly KERAS_PACKAGE=git+https://github.com/keras-team/keras.git MPI=OpenMPI
    - TF_PACKAGE=tensorflow==1.1.0 KERAS_PACKAGE=keras==2.0.0 MPI=MPICH

matrix:
  fast_finish: true
  exclude:
    - python: "3.4"
      env: TF_PACKAGE=tensorflow==1.1.0 KERAS_PACKAGE=keras==2.0.0 MPI=MPICH
    - python: "3.6"
      env: TF_PACKAGE=tensorflow==1.1.0 KERAS_PACKAGE=keras==2.0.0 MPI=MPICH
    - python: "3.4"
      env: TF_PACKAGE=tf-nightly KERAS_PACKAGE=git+https://github.com/keras-team/keras.git MPI=OpenMPI

install:
  - |
    if [[ $MPI == "OpenMPI" ]]; then
      docker exec $CONTAINER /bin/sh -c "wget -O /tmp/openmpi-3.0.0-bin.tar.gz https://github.com/uber/horovod/files/1596799/openmpi-3.0.0-bin.tar.gz"
      docker exec $CONTAINER /bin/sh -c "cd /usr/local && tar -zxf /tmp/openmpi-3.0.0-bin.tar.gz && ldconfig"
    else
      # installs mpich version 3.0.4
      docker exec $CONTAINER /bin/sh -c "apt-get install -y mpich"
    fi

  # TensorFlow
  - docker exec $CONTAINER /bin/sh -c "pip install $TF_PACKAGE"

  # Keras
  - docker exec $CONTAINER /bin/sh -c "pip install $KERAS_PACKAGE"

  # h5py for Keras model saving
  - docker exec $CONTAINER /bin/sh -c "pip install h5py"

  # scipy for Keras image preprocessing
  - docker exec $CONTAINER /bin/sh -c "pip install scipy"

  # Horovod
  - docker exec $CONTAINER /bin/sh -c "cd /horovod && python setup.py sdist"
  - docker exec $CONTAINER /bin/sh -c "pip install -v /horovod/dist/horovod-*.tar.gz"

script:
  - |
    if [[ $MPI == "OpenMPI" ]]; then
      export MPIRUN="mpirun -allow-run-as-root -np 2 -H localhost:2 -bind-to none -map-by slot"
    else
      export MPIRUN="mpirun -np 2"
    fi
  

  # run unit tests
  - docker exec $CONTAINER /bin/sh -c "$MPIRUN python /horovod/horovod/tensorflow/mpi_ops_test.py"

  # hack TensorFlow MNIST example to be smaller
  - docker exec $CONTAINER /bin/sh -c "sed -i \"s/last_step=20000/last_step=100/\" /horovod/examples/tensorflow_mnist.py"

  # run TensorFlow MNIST example
  - docker exec $CONTAINER /bin/sh -c "$MPIRUN python /horovod/examples/tensorflow_mnist.py"

  # download Keras MNIST dataset
  - docker exec $CONTAINER /bin/sh -c "python -c \"from keras.datasets import mnist; mnist.load_data()\""

  # hack Keras MNIST advanced example to be smaller
  - docker exec $CONTAINER /bin/sh -c "sed -i \"s/epochs = .*/epochs = 12/\" /horovod/examples/keras_mnist_advanced.py"
  - docker exec $CONTAINER /bin/sh -c "sed -i \"s/model.add(Conv2D(32, kernel_size=(3, 3),/model.add(Conv2D(1, kernel_size=(3, 3),/\" /horovod/examples/keras_mnist_advanced.py"
  - docker exec $CONTAINER /bin/sh -c "sed -i \"s/model.add(Conv2D(64, (3, 3), activation='relu'))//\" /horovod/examples/keras_mnist_advanced.py"

  # run Keras MNIST advanced example
  - docker exec $CONTAINER /bin/sh -c "$MPIRUN python /horovod/examples/keras_mnist_advanced.py"