build.yml

# This is a basic workflow to help you get started with Actions

name: CI

# Controls when the workflow will run
# Triggers the workflow on push or pull request events 
# workflow_dispatch allows you to run workflow manually
on:
  push:
    branches:
      - mlflow
      - deterministic
      - mcdropout
      - ensemble
      - sngp
  pull_request:
    branches:
      - mlflow
      - deterministic
      - mcdropout
      - ensemble
      - sngp
  workflow_dispatch:

# A workflow run is made up of one or more jobs that can run sequentially or in parallel
jobs:
  # This workflow contains a single job called "build"
  build:
    # The type of runner that the job will run on
    runs-on: ubuntu-latest

    # Steps represent a sequence of tasks that will be executed as part of the job
    steps:

      # extract branch name
      - name: Extract branch name
        shell: bash
        run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF#refs/heads/})"
        id: extract_branch

      # Checks-out your repository under $GITHUB_WORKSPACE, so your job can access it
      - uses: actions/checkout@v2
        with:
          ref: ${{ steps.extract_branch.outputs.branch }}

      - name: Set up Python 3.9
        uses: actions/setup-python@v2
        with:
          python-version: 3.9
      
      - name: Setup SSH Key
        run: |
          mkdir -p ~/.ssh;
          chmod 700 ~/.ssh;
          printf "Host * \n    StrictHostKeyChecking no" > ~/.ssh/config;
          chmod 400 ~/.ssh/config;
          echo "${{ secrets.ACTIONS_PRIVATE_KEY }}" > ~/.ssh/id_rsa;
          chmod 600 ~/.ssh/id_rsa;
          
      - name: Install Poetry
        uses: abatilo/actions-poetry@v2.0.0
        with:
          poetry-version: 1.1.5
          
      - name: Install Dependencies
        run: |
           pip install paramiko;
           poetry config virtualenvs.create false \
            && poetry install
          
      - name: Run Tests
        run: |
          python -m pytest tests
      
      # We use the branch name to select the relevant experiment
      - name: Build Docker and Run MLFlow
        run: |
          docker build -t uq . && mlflow run . -A gpus=all -e ${{ steps.extract_branch.outputs.branch }}
        # Don't do this (below) as it will not use the latest code! Leaving in as an example of running arbitary command via the ssh connection.
        # ssh -f arcnicd@mlflow.uksouth.cloudapp.azure.com "source ~/.profile; cd uncertainty-estimation; mlflow run . -A d"
        env:
          MLFLOW_TRACKING_USERNAME: ${{ secrets.MLFLOW_TRACKING_USERNAME }}
          MLFLOW_TRACKING_PASSWORD: ${{ secrets.MLFLOW_TRACKING_PASSWORD }}
          MLFLOW_TRACKING_URI: ${{ secrets.MLFLOW_TRACKING_URI }}
          AZURE_STORAGE_ACCESS_KEY: ${{ secrets.AZURE_STORAGE_ACCESS_KEY }}
          DOCKER_HOST: ${{ secrets.DOCKER_HOST }}