mirror of
https://github.com/saymrwulf/pytorch.git
synced 2026-05-14 20:57:59 +00:00
c15638d803
A swapfile on Linux runner has been prepared by https://github.com/pytorch/test-infra/pull/6058. So this PR does 2 things: * Start using the swapfile on all Linux build and test jobs * Testing the rollout https://github.com/pytorch-labs/pytorch-gha-infra/pull/582 ### Testing Run `swapon` inside the container and the swapfile shows up correctly: ``` jenkins@259dfb0a314c:~/workspace$ swapon NAME TYPE SIZE USED PRIO /swapfile file 3G 256K -2 ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/143316 Approved by: https://github.com/ZainRizvi, https://github.com/atalman
466 lines
21 KiB
YAML
466 lines
21 KiB
YAML
name: linux-test
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on:
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workflow_call:
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inputs:
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build-environment:
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required: true
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type: string
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description: Top-level label for what's being built/tested.
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test-matrix:
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required: true
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type: string
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description: JSON description of what test configs to run.
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docker-image:
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required: true
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type: string
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description: Docker image to run in.
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sync-tag:
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required: false
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type: string
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default: ""
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description: |
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If this is set, our linter will use this to make sure that every other
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job with the same `sync-tag` is identical.
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timeout-minutes:
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required: false
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type: number
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default: 240
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description: |
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Set the maximum (in minutes) how long the workflow should take to finish
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use-gha:
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required: false
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type: string
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default: ""
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description: If set to any value, upload to GHA. Otherwise upload to S3.
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dashboard-tag:
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required: false
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type: string
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default: ""
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s3-bucket:
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description: S3 bucket to download artifact
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required: false
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type: string
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default: "gha-artifacts"
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aws-role-to-assume:
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description: role to assume for downloading artifacts
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required: false
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type: string
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default: ""
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disable-monitor:
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description: |
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[Experimental] Disable utilization monitoring for tests.
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Currently, by default we disable the monitor job and only look for specific tests,
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since we are investigating the behaviour of the monitor script with different tests.
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required: false
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type: boolean
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default: false
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secrets:
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HUGGING_FACE_HUB_TOKEN:
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required: false
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description: |
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HF Auth token to avoid rate limits when downloading models or datasets from hub
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SCRIBE_GRAPHQL_ACCESS_TOKEN:
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required: false
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description: |
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FB app token to write to scribe endpoint
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env:
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GIT_DEFAULT_BRANCH: ${{ github.event.repository.default_branch }}
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jobs:
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test:
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# Don't run on forked repos or empty test matrix
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if: github.repository_owner == 'pytorch' && toJSON(fromJSON(inputs.test-matrix).include) != '[]'
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strategy:
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matrix: ${{ fromJSON(inputs.test-matrix) }}
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fail-fast: false
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environment: ${{ github.ref == 'refs/heads/main' && 'scribe-protected' || startsWith(github.ref, 'refs/heads/release/') && 'scribe-protected' || contains(github.event.pull_request.labels.*.name, 'ci-scribe') && 'scribe-pr' || '' }}
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runs-on: ${{ matrix.runner }}
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timeout-minutes: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
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steps:
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- name: Setup SSH (Click me for login details)
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uses: pytorch/test-infra/.github/actions/setup-ssh@main
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if: ${{ !contains(matrix.runner, 'gcp.a100') }}
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with:
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github-secret: ${{ secrets.GITHUB_TOKEN }}
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instructions: |
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All testing is done inside the container, to start an interactive session run:
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docker exec -it $(docker container ps --format '{{.ID}}') bash
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- name: Checkout PyTorch
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uses: pytorch/pytorch/.github/actions/checkout-pytorch@main
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with:
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no-sudo: true
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- name: Setup Linux
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uses: ./.github/actions/setup-linux
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- name: configure aws credentials
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if : ${{ inputs.aws-role-to-assume != '' }}
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uses: aws-actions/configure-aws-credentials@v3
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with:
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role-to-assume: ${{ inputs.aws-role-to-assume }}
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role-session-name: gha-linux-test
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aws-region: us-east-1
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- name: Calculate docker image
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id: calculate-docker-image
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uses: pytorch/test-infra/.github/actions/calculate-docker-image@main
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with:
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docker-image-name: ${{ inputs.docker-image }}
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- name: Use following to pull public copy of the image
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id: print-ghcr-mirror
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env:
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ECR_DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
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shell: bash
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run: |
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tag=${ECR_DOCKER_IMAGE##*/}
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echo "docker pull ghcr.io/pytorch/ci-image:${tag/:/-}"
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- name: Pull docker image
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uses: pytorch/test-infra/.github/actions/pull-docker-image@main
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with:
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docker-image: ${{ steps.calculate-docker-image.outputs.docker-image }}
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- name: Check if in a container runner
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shell: bash
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id: check_container_runner
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run: echo "IN_CONTAINER_RUNNER=$(if [ -f /.inarc ] || [ -f /.incontainer ]; then echo true ; else echo false; fi)" >> "$GITHUB_OUTPUT"
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- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
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id: install-nvidia-driver
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uses: pytorch/test-infra/.github/actions/setup-nvidia@main
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if: ${{ contains(inputs.build-environment, 'cuda') && !contains(matrix.config, 'nogpu') && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' }}
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- name: Setup GPU_FLAG for docker run
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id: setup-gpu-flag
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run: echo "GPU_FLAG=--gpus all -e NVIDIA_DRIVER_CAPABILITIES=all" >> "${GITHUB_ENV}"
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if: ${{ contains(inputs.build-environment, 'cuda') && !contains(matrix.config, 'nogpu') && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'true' }}
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- name: Setup SCCACHE_SERVER_PORT environment for docker run when on container
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id: setup-sscache-port-flag
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run: echo "SCCACHE_SERVER_PORT_DOCKER_FLAG=-e SCCACHE_SERVER_PORT=$((RUNNER_UID + 4226))" >> "${GITHUB_ENV}"
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if: ${{ steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'true' }}
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- name: Lock NVIDIA A100 40GB Frequency
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run: |
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sudo nvidia-smi -pm 1
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sudo nvidia-smi -ac 1215,1410
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nvidia-smi
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if: ${{ contains(matrix.runner, 'a100') && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false' }}
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- name: Start monitoring script
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id: monitor-script
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if: ${{ !inputs.disable-monitor }}
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shell: bash
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continue-on-error: true
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run: |
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python3 -m pip install psutil==5.9.1 nvidia-ml-py==11.525.84
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python3 -m tools.stats.monitor > usage_log.txt 2>&1 &
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echo "monitor-script-pid=${!}" >> "${GITHUB_OUTPUT}"
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- name: Download build artifacts
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uses: ./.github/actions/download-build-artifacts
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with:
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name: ${{ inputs.build-environment }}
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s3-bucket: ${{ inputs.s3-bucket }}
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- name: Download TD artifacts
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continue-on-error: true
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uses: ./.github/actions/download-td-artifacts
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- name: Parse ref
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id: parse-ref
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run: .github/scripts/parse_ref.py
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- name: Get workflow job id
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id: get-job-id
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uses: ./.github/actions/get-workflow-job-id
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if: always()
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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- name: Check for keep-going label and re-enabled test issues
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# This uses the filter-test-configs action because it conviniently
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# checks for labels and re-enabled test issues. It does not actually do
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# any filtering. All filtering is done in the build step.
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id: keep-going
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uses: ./.github/actions/filter-test-configs
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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test-matrix: ${{ inputs.test-matrix }}
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job-name: ${{ steps.get-job-id.outputs.job-name }}
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- name: Set Test step time
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id: test-timeout
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shell: bash
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env:
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JOB_TIMEOUT: ${{ matrix.mem_leak_check == 'mem_leak_check' && 600 || inputs.timeout-minutes }}
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run: |
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echo "timeout=$((JOB_TIMEOUT-30))" >> "${GITHUB_OUTPUT}"
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- name: Test
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id: test
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timeout-minutes: ${{ fromJson(steps.test-timeout.outputs.timeout) }}
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env:
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BUILD_ENVIRONMENT: ${{ inputs.build-environment }}
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PR_NUMBER: ${{ github.event.pull_request.number }}
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GITHUB_REPOSITORY: ${{ github.repository }}
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GITHUB_WORKFLOW: ${{ github.workflow }}
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GITHUB_JOB: ${{ github.job }}
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GITHUB_RUN_ID: ${{ github.run_id }}
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GITHUB_RUN_NUMBER: ${{ github.run_number }}
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GITHUB_RUN_ATTEMPT: ${{ github.run_attempt }}
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JOB_ID: ${{ steps.get-job-id.outputs.job-id }}
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JOB_NAME: ${{ steps.get-job-id.outputs.job-name }}
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BRANCH: ${{ steps.parse-ref.outputs.branch }}
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SHA1: ${{ github.event.pull_request.head.sha || github.sha }}
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BASE_SHA: ${{ github.event.pull_request.base.sha || github.sha }}
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TEST_CONFIG: ${{ matrix.config }}
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SHARD_NUMBER: ${{ matrix.shard }}
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NUM_TEST_SHARDS: ${{ matrix.num_shards }}
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REENABLED_ISSUES: ${{ steps.keep-going.outputs.reenabled-issues }}
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CONTINUE_THROUGH_ERROR: ${{ steps.keep-going.outputs.keep-going }}
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VERBOSE_TEST_LOGS: ${{ steps.keep-going.outputs.ci-verbose-test-logs }}
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TEST_SHOWLOCALS: ${{ steps.keep-going.outputs.ci-test-showlocals }}
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NO_TEST_TIMEOUT: ${{ steps.keep-going.outputs.ci-no-test-timeout }}
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NO_TD: ${{ steps.keep-going.outputs.ci-no-td }}
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TD_DISTRIBUTED: ${{ steps.keep-going.outputs.ci-td-distributed }}
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SCCACHE_BUCKET: ossci-compiler-cache-circleci-v2
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SCCACHE_REGION: us-east-1
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SCCACHE_S3_KEY_PREFIX: ${{ github.workflow }}
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SHM_SIZE: ${{ contains(inputs.build-environment, 'cuda') && '2g' || '1g' }}
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DOCKER_IMAGE: ${{ inputs.docker-image }}
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XLA_CUDA: ${{ contains(inputs.build-environment, 'xla') && '0' || '' }}
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XLA_CLANG_CACHE_S3_BUCKET_NAME: ossci-compiler-clang-cache-circleci-xla
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PYTORCH_TEST_CUDA_MEM_LEAK_CHECK: ${{ matrix.mem_leak_check && '1' || '0' }}
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PYTORCH_TEST_RERUN_DISABLED_TESTS: ${{ matrix.rerun_disabled_tests && '1' || '0' }}
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DASHBOARD_TAG: ${{ inputs.dashboard-tag }}
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HUGGING_FACE_HUB_TOKEN: ${{ secrets.HUGGING_FACE_HUB_TOKEN }}
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SCRIBE_GRAPHQL_ACCESS_TOKEN: ${{ secrets.SCRIBE_GRAPHQL_ACCESS_TOKEN }}
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IS_A100_RUNNER: ${{ contains(matrix.runner, 'a100') && '1' || '0' }}
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ARTIFACTS_FILE_SUFFIX: ${{ github.job }}-${{ matrix.config }}-${{ matrix.shard }}-${{ matrix.num_shards }}-${{ matrix.runner }}_${{ steps.get-job-id.outputs.job-id }}
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run: |
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set -x
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if [[ $TEST_CONFIG == 'multigpu' ]]; then
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TEST_COMMAND=.ci/pytorch/multigpu-test.sh
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elif [[ $BUILD_ENVIRONMENT == *onnx* ]]; then
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TEST_COMMAND=.ci/onnx/test.sh
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else
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TEST_COMMAND=.ci/pytorch/test.sh
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fi
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# Leaving 1GB for the runner and other things
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TOTAL_AVAILABLE_MEMORY_IN_GB=$(awk '/MemTotal/ { printf "%.3f \n", $2/1024/1024 - 1 }' /proc/meminfo)
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# https://docs.docker.com/engine/containers/resource_constraints/#--memory-swap-details, the 3GB swap
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# comes from https://github.com/pytorch/test-infra/pull/6058
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TOTAL_MEMORY_WITH_SWAP=$(("${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}" + 3))
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# detached container should get cleaned up by teardown_ec2_linux
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# TODO: Stop building test binaries as part of the build phase
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# Used for GPU_FLAG since that doesn't play nice
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# shellcheck disable=SC2086,SC2090
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container_name=$(docker run \
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${GPU_FLAG:-} \
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${SCCACHE_SERVER_PORT_DOCKER_FLAG:-} \
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-e BUILD_ENVIRONMENT \
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-e PR_NUMBER \
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-e GITHUB_ACTIONS \
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-e GITHUB_REPOSITORY \
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-e GITHUB_WORKFLOW \
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-e GITHUB_JOB \
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-e GITHUB_RUN_ID \
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-e GITHUB_RUN_NUMBER \
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-e GITHUB_RUN_ATTEMPT \
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-e JOB_ID \
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-e JOB_NAME \
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-e BASE_SHA \
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-e BRANCH \
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-e SHA1 \
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-e AWS_DEFAULT_REGION \
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-e IN_WHEEL_TEST \
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-e SHARD_NUMBER \
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-e TEST_CONFIG \
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-e NUM_TEST_SHARDS \
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-e REENABLED_ISSUES \
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-e CONTINUE_THROUGH_ERROR \
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-e VERBOSE_TEST_LOGS \
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-e TEST_SHOWLOCALS \
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-e NO_TEST_TIMEOUT \
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-e NO_TD \
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-e TD_DISTRIBUTED \
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-e PR_LABELS \
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-e MAX_JOBS="$(nproc --ignore=2)" \
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-e SCCACHE_BUCKET \
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-e SCCACHE_REGION \
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-e SCCACHE_S3_KEY_PREFIX \
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-e XLA_CUDA \
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-e XLA_CLANG_CACHE_S3_BUCKET_NAME \
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-e PYTORCH_TEST_CUDA_MEM_LEAK_CHECK \
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-e PYTORCH_TEST_RERUN_DISABLED_TESTS \
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-e SKIP_SCCACHE_INITIALIZATION=1 \
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-e HUGGING_FACE_HUB_TOKEN \
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-e SCRIBE_GRAPHQL_ACCESS_TOKEN \
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-e DASHBOARD_TAG \
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-e IS_A100_RUNNER \
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-e ARTIFACTS_FILE_SUFFIX \
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--memory="${TOTAL_AVAILABLE_MEMORY_IN_GB%.*}g" \
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--memory-swap="${TOTAL_MEMORY_WITH_SWAP}g" \
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--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
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--security-opt seccomp=unconfined \
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--cap-add=SYS_PTRACE \
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--ipc=host \
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--shm-size="${SHM_SIZE}" \
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--tty \
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--detach \
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--name="${container_name}" \
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--user jenkins \
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-v "${GITHUB_WORKSPACE}:/var/lib/jenkins/workspace" \
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-w /var/lib/jenkins/workspace \
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"${DOCKER_IMAGE}"
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)
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# Propagate download.pytorch.org IP to container
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grep download.pytorch.org /etc/hosts | docker exec -i "${container_name}" sudo bash -c "/bin/cat >> /etc/hosts"
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echo "DOCKER_CONTAINER_ID=${container_name}" >> "${GITHUB_ENV}"
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docker exec -t "${container_name}" sh -c "python3 -m pip install $(echo dist/*.whl)[opt-einsum] && ${TEST_COMMAND}"
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- name: Upload pytest cache if tests failed
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uses: ./.github/actions/pytest-cache-upload
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continue-on-error: true
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if: failure() && steps.test.conclusion && steps.test.conclusion == 'failure'
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with:
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cache_dir: .pytest_cache
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shard: ${{ matrix.shard }}
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sha: ${{ github.event.pull_request.head.sha || github.sha }}
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test_config: ${{ matrix.config }}
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job_identifier: ${{ github.workflow }}_${{ inputs.build-environment }}
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- name: Upload the benchmark results
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uses: pytorch/test-infra/.github/actions/upload-benchmark-results@main
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with:
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benchmark-results-dir: test/test-reports
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dry-run: false
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schema-version: v3
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github-token: ${{ secrets.GITHUB_TOKEN }}
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- name: Print remaining test logs
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shell: bash
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if: always() && steps.test.conclusion
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run: |
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cat test/**/*_toprint.log || true
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- name: Stop monitoring script
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if: ${{ always() && steps.monitor-script.outputs.monitor-script-pid }}
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shell: bash
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continue-on-error: true
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env:
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MONITOR_SCRIPT_PID: ${{ steps.monitor-script.outputs.monitor-script-pid }}
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run: |
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kill "$MONITOR_SCRIPT_PID"
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- name: Upload test artifacts
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uses: ./.github/actions/upload-test-artifacts
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if: always() && steps.test.conclusion && steps.test.conclusion != 'skipped'
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with:
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file-suffix: ${{ github.job }}-${{ matrix.config }}-${{ matrix.shard }}-${{ matrix.num_shards }}-${{ matrix.runner }}_${{ steps.get-job-id.outputs.job-id }}
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use-gha: ${{ inputs.use-gha }}
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s3-bucket: ${{ inputs.s3-bucket }}
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- name: Collect backtraces from coredumps (if any)
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if: always()
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run: |
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# shellcheck disable=SC2156
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find . -iname "core.[1-9]*" -exec docker exec "${DOCKER_CONTAINER_ID}" sh -c "gdb python {} -ex 'bt' -ex 'q'" \;
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- name: Store Core dumps on S3
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uses: seemethere/upload-artifact-s3@v5
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if: failure()
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with:
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name: coredumps-${{ matrix.config }}-${{ matrix.shard }}-${{ matrix.num_shards }}-${{ matrix.runner }}
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retention-days: 14
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if-no-files-found: ignore
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path: ./**/core.[1-9]*
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- name: Teardown Linux
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uses: pytorch/test-infra/.github/actions/teardown-linux@main
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if: always() && steps.check_container_runner.outputs.IN_CONTAINER_RUNNER == 'false'
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# NB: We are currently having an intermittent GPU-related issue on G5 runners with
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# A10G GPU. Once this happens, trying to reset the GPU as done in setup-nvidia does
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# not seem to help. Here are some symptoms:
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# * Calling nvidia-smi timeouts after 60 second
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# * Fail to run nvidia-smi with an unable to determine the device handle for GPU
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# unknown error
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# * Test fails with a missing CUDA GPU error when initializing CUDA in PyTorch
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# * Run docker --gpus all fails with error response from daemon
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#
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# As both the root cause and recovery path are unclear, let's take the runner out of
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# service so that it doesn't get any more jobs
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- name: Check NVIDIA driver installation step
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if: failure() && steps.install-nvidia-driver.outcome && steps.install-nvidia-driver.outcome != 'skipped'
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shell: bash
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env:
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RUNNER_WORKSPACE: ${{ runner.workspace }}
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run: |
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set +e
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set -x
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nvidia-smi
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# NB: Surprisingly, nvidia-smi command returns successfully with return code 0 even in
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# the case where the driver has already crashed as it still can get the driver version
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# and some basic information like the bus ID. However, the rest of the information
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# would be missing (ERR!), for example:
|
|
#
|
|
# +-----------------------------------------------------------------------------+
|
|
# | NVIDIA-SMI 525.89.02 Driver Version: 525.89.02 CUDA Version: 12.0 |
|
|
# |-------------------------------+----------------------+----------------------+
|
|
# | GPU Name Persistence-M| Bus-Id Disp.A | Volatile Uncorr. ECC |
|
|
# | Fan Temp Perf Pwr:Usage/Cap| Memory-Usage | GPU-Util Compute M. |
|
|
# | | | MIG M. |
|
|
# |===============================+======================+======================|
|
|
# | 0 ERR! Off | 00000000:00:1E.0 Off | ERR! |
|
|
# |ERR! ERR! ERR! ERR! / ERR! | 4184MiB / 23028MiB | ERR! Default |
|
|
# | | | ERR! |
|
|
# +-------------------------------+----------------------+----------------------+
|
|
#
|
|
# +-----------------------------------------------------------------------------+
|
|
# | Processes: |
|
|
# | GPU GI CI PID Type Process name GPU Memory |
|
|
# | ID ID Usage |
|
|
# |=============================================================================|
|
|
# +-----------------------------------------------------------------------------+
|
|
#
|
|
# This should be reported as a failure instead as it will guarantee to fail when
|
|
# Docker tries to run with --gpus all
|
|
#
|
|
# So, the correct check here is to query one of the missing piece of info like
|
|
# GPU name, so that the command can fail accordingly
|
|
nvidia-smi --query-gpu=gpu_name --format=csv,noheader --id=0
|
|
NVIDIA_SMI_STATUS=$?
|
|
|
|
# These are acceptable return code from nvidia-smi as copied from setup-nvidia GitHub action
|
|
if [ "$NVIDIA_SMI_STATUS" -ne 0 ] && [ "$NVIDIA_SMI_STATUS" -ne 14 ]; then
|
|
echo "NVIDIA driver installation has failed, shutting down the runner..."
|
|
.github/scripts/stop_runner_service.sh
|
|
fi
|
|
|
|
# For runner with multiple GPUs, we also want to confirm that the number of GPUs are the
|
|
# power of 2, i.e. 1, 2, 4, or 8. This is to avoid flaky test issue when one GPU fails
|
|
# https://github.com/pytorch/test-infra/issues/4000
|
|
GPU_COUNT=$(nvidia-smi --list-gpus | wc -l)
|
|
NVIDIA_SMI_STATUS=$?
|
|
|
|
# These are acceptable return code from nvidia-smi as copied from setup-nvidia GitHub action
|
|
if [ "$NVIDIA_SMI_STATUS" -ne 0 ] && [ "$NVIDIA_SMI_STATUS" -ne 14 ]; then
|
|
echo "NVIDIA driver installation has failed, shutting down the runner..."
|
|
.github/scripts/stop_runner_service.sh
|
|
fi
|
|
|
|
# Check the GPU count to be a power of 2
|
|
if [ "$GPU_COUNT" -le 8 ] && [ "$GPU_COUNT" -ne 1 ] && [ "$GPU_COUNT" -ne 2 ] && [ "$GPU_COUNT" -ne 4 ] && [ "$GPU_COUNT" -ne 8 ]; then
|
|
echo "NVIDIA driver detects $GPU_COUNT GPUs. The runner has a broken GPU, shutting it down..."
|
|
.github/scripts/stop_runner_service.sh
|
|
fi
|