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name: TorchBench Userbenchmark test on IBM Cloud | ||
on: | ||
workflow_dispatch: | ||
inputs: | ||
userbenchmark_name: | ||
description: "Name of the user benchmark to run" | ||
userbenchmark_options: | ||
description: "Option of the user benchmark to run" | ||
env: | ||
PLATFORM_NAME: "ibm_cloud" | ||
TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.TORCHBENCH_USERBENCHMARK_SCRIBE_GRAPHQL_ACCESS_TOKEN }} | ||
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }} | ||
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }} | ||
CONDA_ENV: "torchbench" | ||
DOCKER_IMAGE: "ghcr.io/pytorch/torchbench:latest" | ||
SETUP_SCRIPT: "/workspace/setup_instance.sh" | ||
jobs: | ||
run-userbenchmark: | ||
runs-on: [self-hosted, testrunner1545] | ||
timeout-minutes: 1440 # 24 hours | ||
steps: | ||
- name: Checkout TorchBench | ||
uses: actions/checkout@v3 | ||
with: | ||
path: benchmark | ||
- name: Install Conda | ||
run: | | ||
cd benchmark | ||
bash scripts/install_conda.sh | ||
- name: Pull docker image | ||
uses: pytorch/test-infra/.github/actions/pull-docker-image@main | ||
with: | ||
docker-image: ${{ env.DOCKER_IMAGE }} | ||
- name: Run Docker Image | ||
run: | | ||
CONTAINER_ID=$(docker run \ | ||
-e CONDA_ENV \ | ||
-e SETUP_SCRIPT \ | ||
--tty \ | ||
--detach \ | ||
-v "${PWD}/benchmark:/benchmark" \ | ||
-w / \ | ||
"${{ env.DOCKER_IMAGE }}" \ | ||
tail -f /dev/null | ||
) | ||
echo "Container ID: ${CONTAINER_ID}" | ||
# Write the CONTAINER_ID to GITHUB_ENV | ||
echo "CONTAINER_ID=${CONTAINER_ID}" >> "${GITHUB_ENV}" | ||
- name: Install TorchBench | ||
run: | | ||
docker exec -t -w "/benchmark" "${CONTAINER_ID}" bash /benchmark/scripts/torchbench_install.sh | ||
- name: Run user benchmark | ||
run: | | ||
# remove old results | ||
if [ -d benchmark-output ]; then rm -Rf benchmark-output; fi | ||
pushd benchmark | ||
if [ -d .userbenchmark ]; then rm -Rf .userbenchmark; fi | ||
# Run userbenchmark | ||
MANUAL_WORKFLOW="${{ github.event.inputs.userbenchmark_name }}" | ||
if [ -z "${MANUAL_WORKFLOW}" ]; then | ||
# Figure out what userbenchmarks we should run, and run it | ||
docker exec -t -w "/benchmark" "${CONTAINER_ID}" bash -c ". ${SETUP_SCRIPT} && conda activate ${CONDA_ENV} && \ | ||
python .github/scripts/userbenchmark/schedule-benchmarks.py --platform ${PLATFORM_NAME}" | ||
if [ -d ./.userbenchmark ]; then | ||
cp -r ./.userbenchmark ../benchmark-output | ||
else | ||
mkdir ../benchmark-output | ||
fi | ||
else | ||
docker exec -t -w "/benchmark" "${CONTAINER_ID}" bash -c ". ${SETUP_SCRIPT} && conda activate ${CONDA_ENV} && \ | ||
python run_benchmark.py \ | ||
\"${{ github.event.inputs.userbenchmark_name }}\" ${{ github.event.inputs.userbenchmark_options }}" | ||
cp -r ./.userbenchmark/"${{ github.event.inputs.userbenchmark_name }}" ../benchmark-output | ||
fi | ||
- name: Upload result jsons to Scribe | ||
run: | | ||
pushd benchmark | ||
. scripts/activate_conda.sh | ||
RESULTS=($(find ${PWD}/../benchmark-output -name "metrics-*.json" -maxdepth 2 | sort -r)) | ||
echo "Uploading result jsons: ${RESULTS}" | ||
for r in ${RESULTS[@]}; do | ||
python ./scripts/userbenchmark/upload_scribe.py --userbenchmark_json "${r}" --userbenchmark_platform "${PLATFORM_NAME}" | ||
python ./scripts/userbenchmark/upload_s3.py --upload-file "${r}" --userbenchmark_platform "${PLATFORM_NAME}" | ||
done | ||
- name: Upload artifact | ||
uses: actions/upload-artifact@v3 | ||
with: | ||
name: TorchBench result | ||
path: benchmark-output/ | ||
- name: Teardown Linux | ||
uses: pytorch/test-infra/.github/actions/teardown-linux@main | ||
if: always() | ||
|
||
concurrency: | ||
group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }} | ||
cancel-in-progress: true |