name: android-perf

on:
  schedule:
    - cron: 0 0 * * *
  # Note: GitHub has an upper limit of 10 inputs
  workflow_dispatch:
    inputs:
      models:
        description: Models to be benchmarked
        required: false
        type: string
        default: stories110M
      devices:
        description: Target devices to run benchmark
        required: false
        type: string
        default: samsung_galaxy_s22
      delegates:
        description: Backend delegates
        required: false
        type: string
        default: xnnpack
      threadpool:
        description: Run with threadpool?
        required: false
        type: boolean
        default: false
      benchmark_configs:
        description: The list of configs used the benchmark
        required: false
        type: string
      test_spec:
        description: The test spec to drive the test on AWS devices
        required: false
        type: string
  workflow_call:
    inputs:
      models:
        description: Models to be benchmarked
        required: false
        type: string
        default: stories110M
      devices:
        description: Target devices to run benchmark
        required: false
        type: string
        default: samsung_galaxy_s22
      delegates:
        description: Backend delegates
        required: false
        type: string
        default: xnnpack
      threadpool:
        description: Run with threadpool?
        required: false
        type: boolean
        default: false
      benchmark_configs:
        description: The list of configs used the benchmark
        required: false
        type: string
      test_spec:
        description: The test spec to drive the test on AWS devices
        required: false
        type: string

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

jobs:
  set-parameters:
    runs-on: linux.2xlarge
    outputs:
      models: ${{ steps.set-parameters.outputs.models }}
      devices: ${{ steps.set-parameters.outputs.devices }}
      delegates: ${{ steps.set-parameters.outputs.delegates }}
    steps:
      - name: Set parameters
        id: set-parameters
        shell: bash
        env:
          # Separate default values from the workflow dispatch. To ensure defaults are accessible
          # during scheduled runs and to provide flexibility for different defaults between
          # on-demand and periodic benchmarking.
          CRON_DEFAULT_MODELS: "stories110M,dl3,mv3,mv2,ic4,ic3,vit"
          CRON_DEFAULT_DEVICES: "samsung_galaxy_s22"
          CRON_DEFAULT_DELEGATES: "xnnpack,qnn"
        run: |
          set -ex
          MODELS="${{ inputs.models }}"
          if [ -z "$MODELS" ]; then
            MODELS="$CRON_DEFAULT_MODELS"
          fi
          DEVICES="${{ inputs.devices }}"
          if [ -z "$DEVICES" ]; then
            DEVICES="$CRON_DEFAULT_DEVICES"
          fi
          DELEGATES="${{ inputs.delegates }}"
          if [ -z "$DELEGATES" ]; then
            DELEGATES="$CRON_DEFAULT_DELEGATES"
          fi

          # Mapping devices to their corresponding device-pool-arn
          declare -A DEVICE_POOL_ARNS
          DEVICE_POOL_ARNS[samsung_galaxy_s22]="arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/e59f866a-30aa-4aa1-87b7-4510e5820dfa"
          DEVICE_POOL_ARNS[samsung_galaxy_s24]="arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/98f8788c-2e25-4a3c-8bb2-0d1e8897c0db"

          # Resolve device names with their corresponding ARNs
          if [[ ! $(echo "$DEVICES" | jq empty 2>/dev/null) ]]; then
            DEVICES=$(echo "$DEVICES" | jq -Rc 'split(",")')
          fi
          declare -a MAPPED_ARNS=()
          for DEVICE in $(echo "$DEVICES" | jq -r '.[]'); do
            if [[ -z "${DEVICE_POOL_ARNS[$DEVICE]}" ]]; then
              echo "Error: No ARN found for device '$DEVICE'. Abort." >&2
              exit 1
            fi
            MAPPED_ARNS+=("${DEVICE_POOL_ARNS[$DEVICE]}")
          done

          echo "models=$(echo $MODELS | jq -Rc 'split(",")')" >> $GITHUB_OUTPUT
          MAPPED_ARNS_JSON=$(printf '%s\n' "${MAPPED_ARNS[@]}" | jq -R . | jq -s .)
          echo "devices=$(echo "$MAPPED_ARNS_JSON" | jq -c .)" >> $GITHUB_OUTPUT
          echo "delegates=$(echo $DELEGATES | jq -Rc 'split(",")')" >> $GITHUB_OUTPUT

  export-models:
    name: export-models
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@release/2.5
    needs: set-parameters
    strategy:
      matrix:
          model: ${{ fromJson(needs.set-parameters.outputs.models) }}
          delegate: ${{ fromJson(needs.set-parameters.outputs.delegates) }}
      fail-fast: false
    with:
      runner: linux.4xlarge
      docker-image: executorch-ubuntu-22.04-qnn-sdk
      submodules: 'true'
      timeout: 60
      upload-artifact: android-models
      upload-artifact-to-s3: true
      script: |
        # The generic Linux job chooses to use base env, not the one setup by the image
        echo "::group::Setting up dev environment"
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"
        if [[ ${{ matrix.delegate }} == "qnn" ]]; then
            PYTHON_EXECUTABLE=python bash .ci/scripts/setup-qnn-deps.sh
            PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh
        fi
        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "cmake"
        ARTIFACTS_DIR_NAME=artifacts-to-be-uploaded/${{ matrix.model }}_${{ matrix.delegate }}
        echo "::endgroup::"

        echo "::group::Exporting ${{ matrix.delegate }} model: ${{ matrix.model }}"
        BUILD_MODE="cmake"
        DTYPE="fp32"

        if [[ ${{ matrix.model }} =~ ^stories* ]]; then
            # Install requirements for export_llama
            PYTHON_EXECUTABLE=python bash examples/models/llama/install_requirements.sh
            # Test llama2
            if [[ ${{ matrix.delegate }} == "xnnpack" ]]; then
                DELEGATE_CONFIG="xnnpack+custom+qe"
            elif [[ ${{ matrix.delegate }} == "qnn" ]]; then
                DELEGATE_CONFIG="qnn"
            else
                echo "Unsupported delegate ${{ matrix.delegate }}"
                exit 1
            fi
            PYTHON_EXECUTABLE=python bash .ci/scripts/test_llama.sh "${{ matrix.model }}" "${BUILD_MODE}" "${DTYPE}" "${DELEGATE_CONFIG}" "${ARTIFACTS_DIR_NAME}"
        else
            PYTHON_EXECUTABLE=python bash .ci/scripts/test_model.sh "${{ matrix.model }}" "${BUILD_MODE}" "${{ matrix.delegate }}" "${ARTIFACTS_DIR_NAME}"
        fi
        echo "::endgroup::"

  build-benchmark-app:
    name: build-benchmark-app
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    needs: set-parameters
    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 cmake
        export ARTIFACTS_DIR_NAME=artifacts-to-be-uploaded

        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-qnn-deps.sh
        PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh

        export ANDROID_ABIS="arm64-v8a"
        PYTHON_EXECUTABLE=python EXECUTORCH_BUILD_QNN=ON QNN_SDK_ROOT=/tmp/qnn/2.25.0.240728 bash build/build_android_llm_demo.sh ${ARTIFACTS_DIR_NAME}

  # Let's see how expensive this job is, we might want to tone it down by running it periodically
  benchmark-on-device:
    if: always()
    permissions:
      id-token: write
      contents: read
    uses: pytorch/test-infra/.github/workflows/mobile_job.yml@release/2.5
    needs:
      - set-parameters
      - build-benchmark-app
      - export-models
    strategy:
      matrix:
        model: ${{ fromJson(needs.set-parameters.outputs.models) }}
        delegate: ${{ fromJson(needs.set-parameters.outputs.delegates) }}
        device: ${{ fromJson(needs.set-parameters.outputs.devices) }}
      fail-fast: false
    with:
      # Due to scheduling a job may be pushed beyond the default 60m threshold
      timeout: 120
      device-type: android
      runner: linux.2xlarge
      test-infra-ref: ''
      # This is the ARN of ExecuTorch project on AWS
      project-arn: arn:aws:devicefarm:us-west-2:308535385114:project:02a2cf0f-6d9b-45ee-ba1a-a086587469e6
      device-pool-arn: ${{ matrix.device }}
      android-app-archive: https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/minibench/app-debug.apk
      android-test-archive: https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/minibench/app-debug-androidTest.apk
      # NB: Need to set the default spec here so that it works for periodic too
      test-spec: ${{ inputs.test_spec || 'https://ossci-android.s3.amazonaws.com/executorch/android-llm-device-farm-test-spec.yml' }}
      # Uploaded to S3 from the previous job
      extra-data: https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/${{ matrix.model }}_${{ matrix.delegate }}/model.zip

  upload-benchmark-results:
    needs:
      - benchmark-on-device
    if: always()
    runs-on: linux.2xlarge
    environment: upload-benchmark-results
    permissions:
      id-token: write
      contents: read
    steps:
      - uses: actions/checkout@v3
        with:
          submodules: false

      - name: Authenticate with AWS
        uses: aws-actions/configure-aws-credentials@v4
        with:
          role-to-assume: arn:aws:iam::308535385114:role/gha_workflow_upload-benchmark-results
          # The max duration enforced by the server side
          role-duration-seconds: 18000
          aws-region: us-east-1

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

      - name: Download the list of artifacts from S3
        env:
          ARTIFACTS_S3_DIR: s3://gha-artifacts/device_farm/${{ github.run_id }}/${{ github.run_attempt }}/artifacts/
        shell: bash
        run: |
          set -eux
          ${CONDA_RUN} python -mpip install awscli==1.32.18

          mkdir -p artifacts
          pushd artifacts
          ${CONDA_RUN} aws s3 sync "${ARTIFACTS_S3_DIR}" .
          popd

          ls -lah artifacts

      - name: Extract the benchmark results JSON
        shell: bash
        run: |
          set -eux

          mkdir -p benchmark-results

          for ARTIFACTS_BY_JOB in artifacts/*.json; do
            [ -f "${ARTIFACTS_BY_JOB}" ] || break
            echo "${ARTIFACTS_BY_JOB}"
            ${CONDA_RUN} python .github/scripts/extract_benchmark_results.py \
              --artifacts "${ARTIFACTS_BY_JOB}" \
              --output-dir benchmark-results \
              --repo ${{ github.repository }} \
              --head-branch ${{ github.head_ref || github.ref_name }} \
              --workflow-name "${{ github.workflow }}" \
              --workflow-run-id ${{ github.run_id }} \
              --workflow-run-attempt ${{ github.run_attempt }}
          done

          ls -lah benchmark-results

          for BENCHMARK_RESULTS in benchmark-results/*.json; do
            cat "${BENCHMARK_RESULTS}"
            echo
          done

      - name: Upload the benchmark results
        uses: pytorch/test-infra/.github/actions/upload-benchmark-results@main
        with:
          benchmark-results-dir: 'benchmark-results'
          dry-run: false