.travis.yml

dist: bionic
language: python
cache: pip
jobs:
  include:
    - python: 2.7
    - python: 3.7
env:
  - CUDA=10.1.105-1 CUDA_APT=10-1 CUDA_SHORT=10.1 UBUNTU_VERSION=ubuntu1804
before_install:
  - CUDA_REPO=cuda-repo-${UBUNTU_VERSION}_${CUDA}_amd64.deb
  - NCCL_REPO=nvidia-machine-learning-repo-${UBUNTU_VERSION}_1.0.0-1_amd64.deb
  - wget http://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/${CUDA_REPO}
  - sudo dpkg -i ${CUDA_REPO}
  - sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/${UBUNTU_VERSION}/x86_64/7fa2af80.pub
  - wget http://developer.download.nvidia.com/compute/machine-learning/repos/${UBUNTU_VERSION}/x86_64/${NCCL_REPO}
  - sudo dpkg -i ${NCCL_REPO}
  - sudo apt update -qq
  - sudo apt install -y cuda-10-1 libnccl2 libnccl-dev libnuma-dev
  - sudo apt clean
  - export CUDA_HOME=/usr/local/cuda-${CUDA_SHORT}
  - export LD_LIBRARY_PATH=${CUDA_HOME}/lib64:${LD_LIBRARY_PATH}
  - export PATH=${CUDA_HOME}/bin:${PATH}
  - pip install future mxnet-cu101 tensorflow-gpu torch torchvision
install:
  - export BYTEPS_CUDA_HOME=${CUDA_HOME}
  - python setup.py install
  - cd 3rdparty/ps-lite && make -j && cd -
script:
  - export DMLC_NODE_HOST=127.0.0.1
  - export PORT=8000
  - 3rdparty/ps-lite/tests/local.sh 1 1 3rdparty/ps-lite/tests/test_benchmark 1024000 10 0
  - export PORT=8001
  - 3rdparty/ps-lite/tests/local.sh 2 2 3rdparty/ps-lite/tests/test_benchmark 1024000 10 0
  - export PORT=8002
  - 3rdparty/ps-lite/tests/local.sh 4 4 3rdparty/ps-lite/tests/test_benchmark 1024000 10 0