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Move the tutorials build to OSDC runners
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Lines changed: 109 additions & 138 deletions

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‎.github/labeler.yml‎

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- .ci/docker/**
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- .github/workflows/docker-build.yml
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draft: false
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"ciflow/docs":
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globs:
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- "*.rst"
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- "*.py"
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- Makefile
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- requirements.txt
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- _static/**
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- "*_source/**"
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- .jenkins/**
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- .github/workflows/_build-tutorials-base.yml
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- .github/workflows/build-tutorials.yml
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draft: false

‎.github/pytorch-probot.yml‎

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tracking_issue: 1896
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ciflow_push_tags:
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- ciflow/docker
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- ciflow/docs
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labeler_config: labeler.yml

‎.github/workflows/_build-tutorials-base.yml‎

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default: "pytorch/tutorials"
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jobs:
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worker:
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name: pytorch_tutorial_build_worker
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strategy:
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matrix:
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include:
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- { shard: 1, num_shards: 15, runner: "linux.g5.12xlarge.nvidia.gpu" }
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- { shard: 2, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 3, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 4, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 5, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 6, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 7, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 8, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 9, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 10, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 11, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 12, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 13, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 14, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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- { shard: 15, num_shards: 15, runner: "linux.g5.4xlarge.nvidia.gpu" }
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fail-fast: false
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runs-on: ${{ matrix.runner }}
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docker-image:
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name: Resolve CI docker image
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runs-on: ubuntu-latest
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outputs:
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docker-image: ${{ steps.tag.outputs.docker-image }}
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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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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 Tutorials
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uses: actions/checkout@v6
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with:
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fetch-depth: 0
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- name: Setup Linux
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uses: pytorch/pytorch/.github/actions/setup-linux@main
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- name: Install nvidia driver, nvidia-docker runtime, set GPU_FLAG
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uses: pytorch/test-infra/.github/actions/setup-nvidia@main
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- name: Calculate/build 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: tutorials
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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: Build
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shell: bash
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env:
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DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
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NUM_WORKERS: ${{ matrix.num_shards }}
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WORKER_ID: ${{ matrix.shard }}
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COMMIT_ID: ${{ github.sha }}
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JOB_TYPE: worker
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COMMIT_SOURCE: ${{ github.ref }}
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USE_NIGHTLY: ${{ inputs.USE_NIGHTLY }}
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UPLOAD: ${{ inputs.UPLOAD }}
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# Built and pushed by docker-build.yml, which a PR changing .ci/docker gets
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# through the ciflow/docker label
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- name: Compute the image tag
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id: tag
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run: |
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set -ex
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chmod +x ".jenkins/build.sh"
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container_name=$(docker run \
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${GPU_FLAG:-} \
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-e WORKER_ID \
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-e NUM_WORKERS \
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-e COMMIT_ID \
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-e JOB_TYPE \
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-e COMMIT_SOURCE \
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-e USE_NIGHTLY \
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-e UPLOAD \
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--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
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--tty \
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--detach \
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--shm-size=2gb \
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--name="${container_name}" \
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-v "${GITHUB_WORKSPACE}:/var/lib/workspace" \
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-w /var/lib/workspace \
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"${DOCKER_IMAGE}"
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)
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docker exec -u ci-user -t "${container_name}" sh -c ".jenkins/build.sh"
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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()
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set -eu
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DOCKER_TAG="$(git rev-parse HEAD:.ci/docker)"
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echo "docker-image=308535385114.dkr.ecr.us-east-1.amazonaws.com/tutorials/tutorials:${DOCKER_TAG}" >> "${GITHUB_OUTPUT}"
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worker:
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name: pytorch_tutorial_build_worker
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needs: docker-image
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uses: pytorch/test-infra/.github/workflows/linux_job_v3.yml@main
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permissions:
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id-token: write
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contents: read
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strategy:
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matrix:
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include:
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- { shard: 1, num_shards: 15, runner: "mt-l-x86aavx2-45-167-a10g-4" }
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- { shard: 2, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 3, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 4, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 5, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 6, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 7, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 8, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 9, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 10, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 11, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 12, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 13, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 14, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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- { shard: 15, num_shards: 15, runner: "mt-l-x86aavx2-11-41-a10g" }
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fail-fast: false
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with:
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job-name: pytorch_tutorial_build_worker
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runner: ${{ matrix.runner }}
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docker-image: ${{ needs.docker-image.outputs.docker-image }}
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gpu-arch-type: cuda
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fetch-depth: 0
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timeout: 120
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script: |
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set -ex
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export NUM_WORKERS=${{ matrix.num_shards }}
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export WORKER_ID=${{ matrix.shard }}
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export COMMIT_ID=${{ github.sha }}
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export JOB_TYPE=worker
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export COMMIT_SOURCE=${{ github.ref }}
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export USE_NIGHTLY=${{ inputs.USE_NIGHTLY }}
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export UPLOAD=${{ inputs.UPLOAD }}
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.jenkins/build.sh
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# Not on linux_job_v3: a job calling a reusable workflow cannot set the environment
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# that holds PYTORCHBOT_TOKEN, and the preview goes to a caller-chosen S3 prefix
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manager:
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name: pytorch_tutorial_build_manager
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needs: worker
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runs-on: [self-hosted, linux.2xlarge]
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needs: [docker-image, worker]
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runs-on: mt-l-x86iavx512-8-64
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container:
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image: ${{ needs.docker-image.outputs.docker-image }}
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if: ${{ inputs.UPLOAD == 1 }}
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environment: ${{ github.ref == 'refs/heads/main' && 'pytorchbot-env' || '' }}
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permissions:
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id-token: write
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contents: read
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timeout-minutes: 120
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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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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 $(docker container ps --format '{{.ID}}') bash
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# The workspace is created as uid 1001, which the image's ci-user cannot write to
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- name: Fix workspace permissions
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run: sudo chmod -R 777 "${GITHUB_WORKSPACE}" 2>/dev/null || true
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- name: Checkout Tutorials
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uses: actions/checkout@v6
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with:
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fetch-depth: 0
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- name: Setup Linux
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uses: pytorch/pytorch/.github/actions/setup-linux@main
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- name: Calculate/build 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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- name: Configure AWS credentials
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uses: aws-actions/configure-aws-credentials@v4
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with:
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docker-image-name: tutorials
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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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role-to-assume: arn:aws:iam::308535385114:role/arc
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aws-region: us-east-1
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role-duration-seconds: 18000
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- name: Build
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shell: bash
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env:
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DOCKER_IMAGE: ${{ steps.calculate-docker-image.outputs.docker-image }}
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NUM_WORKERS: 15
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WORKER_ID: 0
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COMMIT_ID: ${{ github.sha }}
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USE_NIGHTLY: ${{ inputs.USE_NIGHTLY }}
162128
run: |
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set -ex
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.jenkins/build.sh
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chmod +x ".jenkins/build.sh"
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container_name=$(docker run \
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${GPU_FLAG:-} \
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-e WORKER_ID \
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-e NUM_WORKERS \
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-e COMMIT_ID \
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-e JOB_TYPE \
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-e COMMIT_SOURCE \
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-e GITHUB_PYTORCHBOT_TOKEN \
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-e USE_NIGHTLY \
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--env-file="/tmp/github_env_${GITHUB_RUN_ID}" \
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--tty \
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--detach \
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--name="${container_name}" \
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-v "${GITHUB_WORKSPACE}:/var/lib/workspace" \
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-w /var/lib/workspace \
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"${DOCKER_IMAGE}"
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)
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docker exec -u ci-user -t "${container_name}" sh -c ".jenkins/build.sh"
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# The ciflow/docs/<pr> tag still names the pull request, so the preview
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# keeps the per-PR prefix. An expression cannot split a ref, hence the step.
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- name: Resolve the preview prefix
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id: preview
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if: ${{ startsWith(github.ref, 'refs/tags/ciflow/docs/') }}
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run: echo "prefix=${GITHUB_REF##*/}" >> "${GITHUB_OUTPUT}"
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187139
- name: Upload docs preview
188140
uses: seemethere/upload-artifact-s3@v5
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if: ${{ github.event_name == 'pull_request' }}
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if: ${{ startsWith(github.ref, 'refs/tags/ciflow/docs/') }}
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with:
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retention-days: 14
192144
s3-bucket: doc-previews
193145
if-no-files-found: error
194146
path: docs
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s3-prefix: ${{ inputs.S3_PREFIX }}/${{ github.event.pull_request.number }}
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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()
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s3-prefix: ${{ inputs.S3_PREFIX }}/${{ steps.preview.outputs.prefix }}

‎.github/workflows/build-tutorials-nightly.yml‎

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jobs:
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build:
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permissions:
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id-token: write
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contents: read
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uses: ./.github/workflows/_build-tutorials-base.yml
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secrets: inherit
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with:

‎.github/workflows/build-tutorials.yml‎

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name: Build tutorials
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on:
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pull_request:
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push:
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branches:
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- main
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# A fork PR gets no OIDC token to upload the preview, so a PR builds through
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# the ciflow/docs label, which pushes this tag from the base repo
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tags:
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- ciflow/docs/*
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concurrency:
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group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.sha }}-${{ github.event_name == 'workflow_dispatch' }}-${{ github.event_name == 'schedule' }}
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cancel-in-progress: true
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jobs:
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build:
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permissions:
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id-token: write
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contents: read
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uses: ./.github/workflows/_build-tutorials-base.yml
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secrets: inherit
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with:

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