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apple-perf.yml
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name: apple-perf
on:
schedule:
- cron: 0 1 * * *
# 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: apple_iphone_15
delegates:
description: Backend delegates
required: false
type: string
default: xnnpack
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: apple_iphone_15
delegates:
description: Backend delegates
required: false
type: string
default: xnnpack
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: ${{ steps.set-parameters.outputs.delegates }}
steps:
- name: Set parameters
id: set-parameters
shell: bash
env:
# Separate default values from the workflow dispatch. To ensure defaults are accessible
# during scheduled runs and to provide flexibility for different defaults between
# on-demand and periodic benchmarking.
CRON_DEFAULT_MODELS: "stories110M,mv3,ic4,resnet50,edsr,mobilebert,w2l"
CRON_DEFAULT_DEVICES: "apple_iphone_15"
CRON_DEFAULT_DELEGATES: "xnnpack,coreml"
run: |
set -ex
MODELS="${{ 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[apple_iphone_15]="arn:aws:devicefarm:us-west-2:308535385114:devicepool:02a2cf0f-6d9b-45ee-ba1a-a086587469e6/3b5acd2e-92e2-4778-b651-7726bafe129d"
# 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/macos_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:
# NB: Need to use our AWS MacOS runner to upload large models to S3
runner: macos-m1-stable
python-version: '3.11'
submodules: 'true'
timeout: 60
upload-artifact: ios-models
upload-artifact-to-s3: true
script: |
set -eux
echo "::group::Setting up CI environment"
.ci/scripts/setup-conda.sh
BUILD_TOOL=cmake
# Setup MacOS dependencies as there is no Docker support on MacOS atm
GITHUB_RUNNER=1 PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
.ci/scripts/setup-macos.sh "${BUILD_TOOL}"
if [[ ${{ matrix.delegate }} == "coreml" ]]; then
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
backends/apple/coreml/scripts/install_requirements.sh
fi
if [[ ${{ matrix.delegate }} == "mps" ]]; then
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
backends/apple/mps/install_requirements.sh
fi
ARTIFACTS_DIR_NAME=artifacts-to-be-uploaded/${{ 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 ${CONDA_RUN} --no-capture-output \
bash examples/models/llama2/install_requirements.sh
# Test llama2
if [[ ${{ matrix.delegate }} == "xnnpack" ]]; then
DELEGATE_CONFIG="xnnpack+custom+qe"
elif [[ ${{ matrix.delegate }} == "coreml" ]]; then
DELEGATE_CONFIG="coreml"
fi
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
bash .ci/scripts/test_llama.sh "${{ matrix.model }}" "${BUILD_MODE}" "${DTYPE}" "${DELEGATE_CONFIG}" "${ARTIFACTS_DIR_NAME}"
else
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
bash .ci/scripts/test_model.sh "${{ 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/macos_job.yml@main
needs:
- set-parameters
secrets: inherit
with:
runner: macos-latest-xlarge
python-version: '3.11'
submodules: 'true'
ref: ${{ github.event_name == 'pull_request' && github.event.pull_request.head.sha || github.sha }}
upload-artifact: ios-apps
secrets-env: BUILD_CERTIFICATE_BASE64 EXECUTORCH_BENCHMARK_BUILD_PROVISION_PROFILE_BASE64 KEYCHAIN_PASSWORD
timeout: 90
script: |
set -eux
echo "::group::Setting up CI environment"
.ci/scripts/setup-conda.sh
BUILD_TOOL=cmake
# Setup MacOS dependencies as there is no Docker support on MacOS atm
GITHUB_RUNNER=1 PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
.ci/scripts/setup-macos.sh "${BUILD_TOOL}"
export ARTIFACTS_DIR_NAME=artifacts-to-be-uploaded
# Setup Apple certificate for iOS development
BUILD_PROVISION_PROFILE_BASE64="${SECRET_EXECUTORCH_BENCHMARK_BUILD_PROVISION_PROFILE_BASE64}" \
BUILD_CERTIFICATE_BASE64="${SECRET_BUILD_CERTIFICATE_BASE64}" \
KEYCHAIN_PASSWORD="${SECRET_KEYCHAIN_PASSWORD}" \
.ci/scripts/setup-ios.sh
# Install CoreML Backend Requirements
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
backends/apple/coreml/scripts/install_requirements.sh
# Install MPS Backend Requirements
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
backends/apple/mps/install_requirements.sh
echo "::endgroup::"
echo "::group::Build ExecuTorch iOS frameworks"
FRAMEWORKS=(
"executorch"
"backend_coreml"
"backend_mps"
"backend_xnnpack"
"kernels_custom"
"kernels_optimized"
"kernels_portable"
"kernels_quantized"
)
# Build Release iOS Frameworks
PYTHON_EXECUTABLE=python ${CONDA_RUN} --no-capture-output \
build/build_apple_frameworks.sh --coreml --custom --mps --optimized --portable --quantized --xnnpack
mkdir -p extension/apple/Benchmark/Frameworks
for FRAMEWORK in "${FRAMEWORKS[@]}"; do (
cp -r "cmake-out/${FRAMEWORK}.xcframework" extension/apple/Benchmark/Frameworks/
) done
echo "::endgroup::"
# NB: Although exported models can be copied to this directory and bundled together with the
# app, we don't use this in CI and rely on AWS extra data parameter to make the model and the
# tokenizer available to the benchmark. This decouples the app and the model. We just need to
# create the directory here to pass the build
mkdir -p extension/apple/Benchmark/Models
${CONDA_RUN} --no-capture-output \
build/build_apple_llm_demo.sh ${ARTIFACTS_DIR_NAME}
upload-benchmark-app:
needs: build-benchmark-app
runs-on: linux.2xlarge
steps:
- name: Download the apps from GitHub
uses: actions/download-artifact@v3
with:
# The name here needs to match the name of the upload-artifact parameter
name: ios-apps
path: ${{ runner.temp }}/artifacts/
- name: Verify the apps
shell: bash
working-directory: ${{ runner.temp }}/artifacts/
run: |
ls -lah ./
- name: Upload the apps to S3
uses: seemethere/upload-artifact-s3@v5
with:
s3-bucket: gha-artifacts
s3-prefix: |
${{ github.repository }}/${{ github.run_id }}/artifacts
retention-days: 14
if-no-files-found: ignore
path: ${{ runner.temp }}/artifacts/
benchmark-on-device:
needs:
- set-parameters
- upload-benchmark-app
- export-models
permissions:
id-token: write
contents: read
uses: pytorch/test-infra/.github/workflows/mobile_job.yml@main
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: ios
# For iOS testing, the runner just needs to call AWS Device Farm, so there is no need to run this on macOS
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: ${{ matrix.device }}
# Uploaded to S3 from the previous job
ios-ipa-archive: https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/Benchmark.ipa
ios-xctestrun-zip: https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/Benchmark.xctestrun.zip
test-spec: ${{ inputs.test_spec || 'https://ossci-ios.s3.amazonaws.com/executorch/default-ios-device-farm-appium-test-spec.yml' }}
extra-data: https://gha-artifacts.s3.amazonaws.com/${{ github.repository }}/${{ github.run_id }}/artifacts/${{ matrix.model }}_${{ matrix.delegate }}/model.zip