trunk.yml

name: trunk

on:
  push:
    branches:
      - main
      - release/*
    tags:
      - ciflow/trunk/*
  pull_request:
    paths:
      - .ci/docker/ci_commit_pins/pytorch.txt
      - .ci/scripts/**
  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:
  gather-models:
    runs-on: ubuntu-22.04
    outputs:
      models: ${{ steps.gather-models.outputs.models }}
    steps:
      - uses: actions/checkout@v3
        with:
          submodules: 'false'
      - uses: actions/setup-python@v4
        with:
          python-version: '3.10'
      - name: Extract the list of models to test
        id: gather-models
        run: |
          set -eux

          PYTHONPATH="${PWD}" python .ci/scripts/gather_test_models.py --target-os macos --event "${GITHUB_EVENT_NAME}"

  test-models-macos:
    name: test-models-macos
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    needs: gather-models
    strategy:
      matrix: ${{ fromJSON(needs.gather-models.outputs.models) }}
      fail-fast: false
    with:
      runner: ${{ matrix.runner }}
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: ${{ matrix.timeout }}
      script: |
        MODEL_NAME=${{ matrix.model }}
        BUILD_TOOL=${{ matrix.build-tool }}
        BACKEND=${{ matrix.backend }}
        DEMO_BACKEND_DELEGATION=${{ matrix.demo_backend_delegation }}

        bash .ci/scripts/setup-conda.sh
        # Setup MacOS dependencies as there is no Docker support on MacOS atm
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"
        # Build and test xecutorch
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_model.sh "${MODEL_NAME}" "${BUILD_TOOL}" "${BACKEND}" "${DEMO_BACKEND_DELEGATION}"

  test-custom-ops-macos:
    name: test-custom-ops-macos
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    strategy:
      matrix:
        include:
          - build-tool: cmake
      fail-fast: false
    with:
      runner: macos-m1-stable
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      script: |
        BUILD_TOOL=${{ matrix.build-tool }}

        bash .ci/scripts/setup-conda.sh
        # Setup MacOS dependencies as there is no Docker support on MacOS atm
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"
        # Build and test custom ops
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash examples/portable/custom_ops/test_custom_ops.sh "${BUILD_TOOL}"

  test-selective-build-macos:
    name: test-selective-build-macos
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    strategy:
      matrix:
        include:
          - build-tool: cmake
      fail-fast: false
    with:
      runner: macos-m1-stable
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      script: |
        BUILD_TOOL=${{ matrix.build-tool }}

        bash .ci/scripts/setup-conda.sh
        # Setup MacOS dependencies as there is no Docker support on MacOS atm
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"
        # Build and test selective build
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash examples/selective_build/test_selective_build.sh "${BUILD_TOOL}"

  test-demo-backend-delegation:
    name: test-demo-backend-delegation
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    strategy:
      matrix:
        include:
          - build-tool: buck2
          - build-tool: cmake
      fail-fast: false
    with:
      runner: linux.2xlarge
      docker-image: executorch-ubuntu-22.04-clang12
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      script: |
        # The generic Linux job chooses to use base env, not the one setup by the image
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"

        BUILD_TOOL=${{ matrix.build-tool }}
        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh "${BUILD_TOOL}"
        # Test selective build
        PYTHON_EXECUTABLE=python bash examples/portable/scripts/test_demo_backend_delegation.sh "${BUILD_TOOL}"

  test-arm-backend-delegation:
    name: test-arm-backend-delegation
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    with:
      runner: linux.2xlarge
      docker-image: executorch-ubuntu-22.04-arm-sdk
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 90
      script: |
        # The generic Linux job chooses to use base env, not the one setup by the image
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"

        source .ci/scripts/utils.sh
        install_executorch

        install_arm

        # Increase number of files user can monitor to bypass buck failures.
        # Hopefully this is high enough for this setup.
        sudo sysctl fs.inotify.max_user_watches=1048576 # 1024 * 1024

        # Test ethos-u delegate examples with run.sh
        PYTHON_EXECUTABLE=python bash examples/arm/run.sh examples/arm/ethos-u-scratch/

  test-arm-reference-delegation:
    name: test-arm-reference-delegation
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    with:
      runner: linux.2xlarge
      docker-image: executorch-ubuntu-22.04-arm-sdk
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 90
      script: |
        # The generic Linux job chooses to use base env, not the one setup by the image
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"

        source .ci/scripts/utils.sh
        install_executorch

        install_arm

        # Run arm unit tests
        pytest -c /dev/null -v -n auto --cov=./ --cov-report=xml backends/arm/test

  test-coreml-delegate:
    name: test-coreml-delegate
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    with:
      runner: macos-13-xlarge
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 90
      script: |
        BUILD_TOOL=cmake

        bash .ci/scripts/setup-conda.sh
        # Setup MacOS dependencies as there is no Docker support on MacOS atm
        GITHUB_RUNNER=1 PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"
        # Build and test coreml delegate
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/coreml/scripts/build_all.sh

  test-pybind-build-macos:
    name: test-pybind-build-macos
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    strategy:
      matrix:
        include:
          - build-tool: cmake
      fail-fast: false
    with:
      runner: macos-m1-stable
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 180
      script: |
        bash .ci/scripts/setup-conda.sh

        # build module for executorch.extension.pybindings.portable_lib
        BUILD_TOOL=${{ matrix.build-tool }}
        EXECUTORCH_BUILD_PYBIND=ON PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"

        # see if we can import the module successfully
        ${CONDA_RUN} python -c "from executorch.extension.pybindings import portable_lib; print('success!')"

  test-llama-runner-macos:
    name: test-llama-runner-mac
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    strategy:
      matrix:
        dtype: [fp32]
        mode: [portable, xnnpack+kv+custom, mps, coreml]
        include:
          - dtype: bf16
            mode: portable
          - dtype: bf16
            mode: custom
      fail-fast: false
    with:
      runner: macos-m1-stable
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 900
      script: |

        DTYPE=${{ matrix.dtype }}
        MODE=${{ matrix.mode }}

        bash .ci/scripts/setup-conda.sh

        # Setup executorch
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh cmake

        if [[ "${MODE}" == "mps" ]]; then
          # Install mps delegate
          PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/mps/install_requirements.sh
          echo "Finishing installing mps."
        elif [[ "${MODE}" == "coreml" ]]; then
          # Install coreml delegate
          PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/coreml/scripts/install_requirements.sh
          echo "Finishing installing coreml."
        fi

        # Install requirements for export_llama
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash examples/models/llama/install_requirements.sh
        # Test llama2
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_llama.sh stories110M cmake "${DTYPE}" "${MODE}"

  # # TODO(jackzhxng): Runner consistently runs out of memory before test finishes. Try to find a more powerful runner.
  # test-llava-runner-macos:
  #   name: test-llava-runner-macos
  #   uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
  #   strategy:
  #     fail-fast: false
  #   with:
  #     runner: macos-14-xlarge
  #     python-version: '3.11'
  #     submodules: 'true'
  #     ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
  #     timeout: 900
  #     script: |
  #       BUILD_TOOL=cmake

  #       bash .ci/scripts/setup-conda.sh
  #       # Setup MacOS dependencies as there is no Docker support on MacOS atm
  #       GITHUB_RUNNER=1 PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"

  #       # install Llava requirements
  #       ${CONDA_RUN} bash examples/models/llama/install_requirements.sh
  #       ${CONDA_RUN} bash examples/models/llava/install_requirements.sh

  #       # run python unittest
  #       ${CONDA_RUN} python -m unittest examples.models.llava.test.test_llava

  #       # run e2e (export, tokenizer and runner)
  #       PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_llava.sh Release

  test-qnn-model:
    name: test-qnn-model
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    strategy:
      matrix:
        dtype: [fp32]
        model: [dl3, mv3, mv2, ic4, ic3, vit]
      fail-fast: false
    with:
      runner: linux.2xlarge
      docker-image: executorch-ubuntu-22.04-clang12-android
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 900
      script: |
        # The generic Linux job chooses to use base env, not the one setup by the image
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"
        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh cmake
        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-qnn-deps.sh
        PYTHON_EXECUTABLE=python bash .ci/scripts/build-qnn-sdk.sh
        PYTHON_EXECUTABLE=python bash .ci/scripts/test_model.sh ${{ matrix.model }} "cmake" "qnn"

  test-apple-model:
    name: test-apple-model
    uses: pytorch/test-infra/.github/workflows/macos_job.yml@main
    strategy:
      fail-fast: false
    with:
      runner: macos-m1-stable
      python-version: '3.11'
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 90
      script: |
        BUILD_TOOL=cmake

        bash .ci/scripts/setup-conda.sh

        # Setup MacOS dependencies as there is no Docker support on MacOS atm
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/setup-macos.sh "${BUILD_TOOL}"
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/coreml/scripts/install_requirements.sh
        echo "Finishing installing coreml."
        PYTHON_EXECUTABLE=python ${CONDA_RUN} bash backends/apple/mps/install_requirements.sh
        echo "Finishing installing mps."

        # Build and test coreml model
        MODELS=(mv3 ic4 resnet50 edsr mobilebert w2l)
        for MODEL_NAME in "${MODELS[@]}"; do
          echo "::group::Exporting coreml model: $MODEL_NAME"
          PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_model.sh "${MODEL_NAME}" "${BUILD_TOOL}" "coreml"
          echo "::endgroup::"

          echo "::group::Exporting mps model: $MODEL_NAME"
          PYTHON_EXECUTABLE=python ${CONDA_RUN} bash .ci/scripts/test_model.sh "${MODEL_NAME}" "${BUILD_TOOL}" "mps"
          echo "::endgroup::"
        done

  test-huggingface-transformers:
    name: test-huggingface-transformers
    uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
    secrets: inherit
    strategy:
      matrix:
        hf_model_repo: [google/gemma-2b]
      fail-fast: false
    with:
      secrets-env: EXECUTORCH_HF_TOKEN
      runner: linux.12xlarge
      docker-image: executorch-ubuntu-22.04-clang12
      submodules: 'true'
      ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
      timeout: 90
      script: |
        echo "::group::Set up ExecuTorch"
        # The generic Linux job chooses to use base env, not the one setup by the image
        CONDA_ENV=$(conda env list --json | jq -r ".envs | .[-1]")
        conda activate "${CONDA_ENV}"
        PYTHON_EXECUTABLE=python bash .ci/scripts/setup-linux.sh cmake

        echo "Installing libexecutorch.a, libextension_module.so, libportable_ops_lib.a"
        rm -rf cmake-out
        cmake \
            -DCMAKE_INSTALL_PREFIX=cmake-out \
            -DCMAKE_BUILD_TYPE=Release \
            -DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON \
            -DEXECUTORCH_BUILD_EXTENSION_MODULE=ON \
            -DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON \
            -DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \
            -DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \
            -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \
            -DEXECUTORCH_BUILD_XNNPACK=ON \
            -DPYTHON_EXECUTABLE=python \
            -Bcmake-out .
        cmake --build cmake-out -j9 --target install --config Release

        echo "Build llama runner"
        dir="examples/models/llama"
        cmake \
            -DCMAKE_INSTALL_PREFIX=cmake-out \
            -DCMAKE_BUILD_TYPE=Release \
            -DEXECUTORCH_BUILD_KERNELS_CUSTOM=ON \
            -DEXECUTORCH_BUILD_KERNELS_OPTIMIZED=ON \
            -DEXECUTORCH_BUILD_KERNELS_QUANTIZED=ON \
            -DEXECUTORCH_BUILD_XNNPACK=ON \
            -DPYTHON_EXECUTABLE=python \
            -Bcmake-out/${dir} \
            ${dir}
        cmake --build cmake-out/${dir} -j9 --config Release
        echo "::endgroup::"

        echo "::group::Set up HuggingFace Dependencies"
        if [ -z "$SECRET_EXECUTORCH_HF_TOKEN" ]; then
          echo "::error::SECRET_EXECUTORCH_HF_TOKEN is empty. For security reason secrets won't be accessible on forked PRs. Please make sure you submit a non-forked PR."
          exit 1
        fi
        pip install -U "huggingface_hub[cli]"
        huggingface-cli login --token $SECRET_EXECUTORCH_HF_TOKEN
        pip install accelerate sentencepiece
        # TODO(guangyang): Switch to use released transformers library after all required patches are included
        pip install "git+https://github.com/huggingface/transformers.git@6cc4dfe3f1e8d421c6d6351388e06e9b123cbfe1"
        pip list
        echo "::endgroup::"

        echo "::group::Export to ExecuTorch"
        TOKENIZER_FILE=tokenizer.model
        TOKENIZER_BIN_FILE=tokenizer.bin
        ET_MODEL_NAME=et_model
        # Fetch the file using a Python one-liner
        DOWNLOADED_TOKENIZER_FILE_PATH=$(python -c "
        from huggingface_hub import hf_hub_download
        # Download the file from the Hugging Face Hub
        downloaded_path = hf_hub_download(
            repo_id='${{ matrix.hf_model_repo }}',
            filename='${TOKENIZER_FILE}'
        )
        print(downloaded_path)
        ")
        if [ -f "$DOWNLOADED_TOKENIZER_FILE_PATH" ]; then
            echo "${TOKENIZER_FILE} downloaded successfully at: $DOWNLOADED_TOKENIZER_FILE_PATH"
            python -m extension.llm.tokenizer.tokenizer -t $DOWNLOADED_TOKENIZER_FILE_PATH -o ./${TOKENIZER_BIN_FILE}
            ls ./tokenizer.bin
        else
            echo "Failed to download ${TOKENIZER_FILE} from ${{ matrix.hf_model_repo }}."
            exit 1
        fi

        python -m extension.export_util.export_hf_model -hfm=${{ matrix.hf_model_repo }} -o ${ET_MODEL_NAME}

        cmake-out/examples/models/llama/llama_main --model_path=${ET_MODEL_NAME}.pte --tokenizer_path=${TOKENIZER_BIN_FILE} --prompt="My name is"
        echo "::endgroup::"