android-perf #9
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| 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@main | |
| needs: set-parameters | |
| strategy: | |
| matrix: | |
| model: ${{ fromJson(needs.set-parameters.outputs.models) }} | |
| delegate: ${{ fromJson(needs.set-parameters.outputs.delegates) }} | |
| fail-fast: false | |
| with: | |
| runner: linux.2xlarge | |
| docker-image: executorch-ubuntu-22.04-clang12-android | |
| submodules: 'true' | |
| timeout: 60 | |
| upload-artifact: android-models | |
| upload-artifact-to-s3: true | |
| script: | | |
| # The generic Linux job chooses to use base env, not the one setup by the image | |
| echo "::group::Setting up dev environment" | |
| CONDA_ENV=$(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/llama2/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-llm-demo: | |
| name: build-llm-demo | |
| 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: | |
| permissions: | |
| id-token: write | |
| contents: read | |
| uses: pytorch/test-infra/.github/workflows/mobile_job.yml@main | |
| needs: | |
| - set-parameters | |
| - build-llm-demo | |
| - 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: ${{ matrix.device }} | |
| # Uploaded to S3 from the previous job, the name of the app comes from the project itself. | |
| # Unlike models there are limited numbers of build flavor for apps, and the model controls whether it should build with bpe/tiktoken tokenizer. | |
| # It's okay to build all possible apps with all possible flavors in job "build-llm-demo". However, in this job, once a model is given, there is only | |
| # one app+flavor that could load and run the model. | |
| android-app-archive: https://gha-artifacts.s3.amazonaws.com/${{ 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 |