android.yml

name: Android

on:
  push:
    branches:
      - main
      - release/*
    tags:
      - ciflow/android/*
  pull_request:
    paths:
      - .ci/docker/**
      - .github/workflows/android.yml
      - build/*android*.sh
      - install_requirements.sh
      - examples/demo-apps/android/**
      - extension/android/**
      - extension/module/**
  workflow_dispatch:

concurrency:
  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
  cancel-in-progress: true

jobs:
  build-aar:
    name: build-aar
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    with:
      runner: linux.2xlarge
      docker-image: executorch-ubuntu-22.04-clang12-android
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 90
      upload-artifact: android-apps
      upload-artifact-to-s3: true
      script: |
        set -eux

        # The generic Linux job chooses to use base env, not the one setup by the image
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"
        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh buck2
        export ARTIFACTS_DIR_NAME=artifacts-to-be-uploaded

        # Build LLM Demo for Android
        # bash build/build_android_llm_demo.sh ${ARTIFACTS_DIR_NAME}

        mkdir -p "${ARTIFACTS_DIR_NAME}/llm_demo"
        touch "${ARTIFACTS_DIR_NAME}/llm_demo/executorch.aar"

  upload-release-aar:
    name: upload-release-aar
    needs: build-aar
    if: ${{ startsWith(github.ref, 'refs/tags/ciflow/android/release') }}
    runs-on: ubuntu-22.04
    timeout-minutes: 10
    steps:
      - name: Upload AAR to RC if ciflow/android/release tag is present
        shell: bash
        run: |
          wget https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/llm_demo/executorch.aar

          pip install awscli==1.32.18
          AWS_CMD="aws s3 cp --dryrun"
          VERSION_NAME="$(date +'%Y%m%d')"
          ${AWS_CMD} executorch.aar s3://ossci-android/executorch/release/${VERSION_NAME}/executorch.aar --acl public-read

  # Running Android emulator directly on the runner and not using Docker
  run-emulator:
    needs: build-aar
    # NB: Use metal install for KVM support to run the emulator faster
    runs-on: linux.24xl.spr-metal
    env:
      ANDROID_NDK_VERSION: r26c
      API_LEVEL: 34
    steps:
      - name: Setup SSH (Click me for login details)
        uses: pytorch/test-infra/.github/actions/setup-ssh@main
        with:
          github-secret: ${{ secrets.GITHUB_TOKEN }}
          instructions: |
            This is used to run Android emulators, ANDROID_HOME is installed at /opt/android/sdk

      - uses: actions/checkout@v3
        with:
          submodules: false

      - name: Setup conda
        uses: pytorch/test-infra/.github/actions/setup-miniconda@main
        with:
          python-version: '3.10'

      - name: Install Android dependencies
        shell: bash
        run: |
          set -eux

          # Reuse the script that install Android on ET Docker image
          sudo -E bash .ci/docker/common/install_android.sh

      - name: Gradle cache
        uses: gradle/actions/setup-gradle@v3

      - name: AVD cache
        uses: actions/cache@v4
        id: avd-cache
        with:
          path: |
            ~/.android/avd/*
            ~/.android/adb*
          key: avd-${{ env.API_LEVEL }}

      # NB: It takes about 10m to cold boot the emulator here
      - name: Run Android emulator
        env:
          ANDROID_HOME: /opt/android/sdk
        uses: reactivecircus/android-emulator-runner@v2
        with:
          api-level: ${{ env.API_LEVEL }}
          arch: x86_64
          script: ./build/run_android_emulator.sh
          # NB: This is to boot the emulator faster following the instructions on
          # https://github.com/ReactiveCircus/android-emulator-runner. The max number
          # of cores we can set is 6, any higher number will be reduced to 6.
          cores: 6
          ram-size: 12288M
          force-avd-creation: false
          disable-animations: true
          emulator-options: -no-snapshot-save -no-window -gpu swiftshader_indirect -noaudio -no-boot-anim -camera-back none
          # This is to make sure that the job doesn't fail flakily
          emulator-boot-timeout: 900