.travis.yml

sudo: required
language: python
git:
  depth: 3
services:
  - docker
python:
  - "2.7"
  - "3.6"
env:
  global:
    - T2T_PROBLEM=algorithmic_reverse_binary40_test
    - T2T_DATA_DIR=/tmp/t2t-data
    - T2T_TRAIN_DIR=/tmp/t2t-train
    - TF_LATEST="1.10.*"
    # This is necessary to have gsutil work with Python 2.7
    - BOTO_CONFIG=/dev/null
  matrix:
    # We test against recent versions of TensorFlow and tf-nightly.
    # If updating, also update TF_LATEST above
    - TF_VERSION="1.9.*"
    - TF_VERSION="1.10.*"
    - TF_VERSION="tf-nightly"
matrix:
  exclude:
    # We test against all versions in Python 2 but only the latest in Python 3
    - python: "3.6"
      env: TF_VERSION="1.9.*"
    - python: "3.6"
      env: TF_VERSION="tf-nightly"
before_install:
  - sudo apt-get update -qq
  - sudo apt-get install -qq libhdf5-dev
install:
  - if [[ "$TF_VERSION" == "tf-nightly"  ]];
    then
      pip install tf-nightly;
    else
      pip install -q "tensorflow==$TF_VERSION";
    fi
  # First ensure that the base dependencies are sufficient for a full import
  - pip install -q .
  - t2t-trainer --registry_help
  # Then install the test dependencies
  - pip install -q .[tests,allen]
  # Make sure to install the atari extras for gym
  - pip install "gym[atari]"
  # Make sure we have the latest version of numpy - avoid problems we were
  # seeing with Python 3
  - pip install -q -U numpy
script:
  # Check import
  - python -c "from tensor2tensor.models import transformer; print(transformer.Transformer.__name__)"

  # Run tests
  # Ignores:
  # Tested separately:
  #   * registry_test
  #   * trainer_lib_test
  #   * visualization_test
  #   * trainer_model_based_test
  #   * allen_brain_test
  #   * trainer_model_based_stochastic_test
  #   * models/research
  # algorithmic_math_test: flaky
  # universal_transformer_test: requires new feature in tf.foldl (rm with TF 1.9)
  - pytest
    --ignore=tensor2tensor/utils/registry_test.py
    --ignore=tensor2tensor/utils/trainer_lib_test.py
    --ignore=tensor2tensor/visualization/visualization_test.py
    --ignore=tensor2tensor/bin/t2t_trainer_test.py
    --ignore=tensor2tensor/data_generators/algorithmic_math_test.py
    --ignore=tensor2tensor/models/research/universal_transformer_test.py
    --ignore=tensor2tensor/rl/trainer_model_based_test.py
    --ignore=tensor2tensor/data_generators/allen_brain_test.py
    --ignore=tensor2tensor/rl/trainer_model_based_stochastic_test.py
    --ignore=tensor2tensor/models/research
  - pytest tensor2tensor/utils/registry_test.py
  - pytest tensor2tensor/utils/trainer_lib_test.py
  - pytest tensor2tensor/visualization/visualization_test.py
  - pytest tensor2tensor/data_generators/allen_brain_test.py
  - if [[ "$TF_VERSION" == "$TF_LATEST"  ]] || [[ "$TF_VERSION" == "tf-nightly"  ]];
    then
      pytest tensor2tensor/models/research;
    fi

  # Run installed scripts
  - t2t-datagen 2>&1 | grep translate && echo passed
  - t2t-trainer --registry_help

  # Test --t2t_usr_dir
  - t2t-trainer --registry_help --t2t_usr_dir=./tensor2tensor/test_data/example_usr_dir 2>&1 | grep my_very_own_hparams && echo passed

  # Run data generation, training, and decoding on a dummy problem
  - t2t-datagen --problem=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR
  - t2t-trainer --problem=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR --model=transformer --hparams_set=transformer_tiny --train_steps=5 --eval_steps=5 --output_dir=$T2T_TRAIN_DIR
  - t2t-decoder --problem=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR --model=transformer --hparams_set=transformer_tiny --output_dir=$T2T_TRAIN_DIR --decode_hparams='num_samples=10'

  # Do some things only on Python 2 and the latest TF version
  # Each should be in a separate block to get proper errors on Travis.
  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]] && [[ "$TF_VERSION" == "tf-nightly"  ]]; then
        pylint -j 2 tensor2tensor;
    fi
  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]] && [[ "$TF_VERSION" == "$TF_LATEST"  ]]; then
        pytest tensor2tensor/rl/trainer_model_based_test.py;
    fi
  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]] && [[ "$TF_VERSION" == "$TF_LATEST"  ]]; then
        jupyter nbconvert --ExecutePreprocessor.timeout=600 --to notebook --execute tensor2tensor/notebooks/hello_t2t.ipynb;
    fi
  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]] && [[ "$TF_VERSION" == "$TF_LATEST"  ]]; then
        jupyter nbconvert --ExecutePreprocessor.timeout=600 --to notebook --execute tensor2tensor/notebooks/t2t_problem.ipynb;
    fi

  # Export and query
  - if [[ "$TRAVIS_PYTHON_VERSION" == "2.7" ]] && [[ "$TF_VERSION" == "$TF_LATEST"  ]]; then
        t2t-exporter --problem=$T2T_PROBLEM --data_dir=$T2T_DATA_DIR --model=transformer --hparams_set=transformer_tiny --output_dir=$T2T_TRAIN_DIR;
        pip install tensorflow-serving-api;
        docker run -d -p 8500:8500 --mount type=bind,source=$T2T_TRAIN_DIR/export/Servo,target=/models/my_model -e MODEL_NAME=my_model -t tensorflow/serving;
        sleep 10;
        t2t-query-server --problem=$T2T_PROBLEM --server=localhost:8500 --servable_name=my_model --data_dir=$T2T_DATA_DIR --inputs_once='1 0 1 0 1 0';
    fi