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update doc and use P2P=LOC for brittle grpo test (axolotl-ai-cloud#2649)
* update doc and skip brittle grpo test * fix the path to run the multigpu tests * increase timeout, use LOC instead of NVL * typo * use hf cache from s3 backed cloudfront * mark grpo as flaky test dues to vllm start
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.github/workflows/multi-gpu-e2e.yml

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@@ -3,7 +3,7 @@ name: docker-multigpu-tests-biweekly
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on:
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pull_request:
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paths:
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- 'tests/e2e/multigpu/*.py'
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- 'tests/e2e/multigpu/**.py'
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- 'requirements.txt'
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- 'setup.py'
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- 'pyproject.toml'

.github/workflows/tests.yml

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@@ -44,96 +44,102 @@ jobs:
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env:
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SKIP: no-commit-to-branch
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preload-cache:
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name: Preload HF cache
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runs-on: ubuntu-latest
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strategy:
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fail-fast: false
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matrix:
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python_version: ["3.11"]
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pytorch_version: ["2.6.0"]
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timeout-minutes: 20
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env:
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AXOLOTL_IS_CI_CACHE_PRELOAD: "1"
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steps:
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- name: Check out repository code
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uses: actions/checkout@v4
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- name: Restore HF cache
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id: hf-cache-restore
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uses: actions/cache/restore@v4
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with:
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path: |
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/home/runner/.cache/huggingface/hub/datasets--*
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/home/runner/.cache/huggingface/hub/models--*
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key: ${{ runner.os }}-hf-hub-cache-v2
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- name: Setup Python
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uses: actions/setup-python@v5
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with:
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python-version: ${{ matrix.python_version }}
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cache: 'pip' # caching pip dependencies
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- name: upgrade pip
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run: |
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pip3 install --upgrade pip
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pip3 install --upgrade packaging==23.2 setuptools==75.8.0 wheel
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- name: Install PyTorch
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run: |
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pip3 install torch==${{ matrix.pytorch_version }}
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- name: Install dependencies
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run: |
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pip3 show torch
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pip3 install --no-build-isolation -U -e .
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python scripts/unsloth_install.py | sh
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python scripts/cutcrossentropy_install.py | sh
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pip3 install -r requirements-dev.txt -r requirements-tests.txt
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- name: Make sure PyTorch version wasn't clobbered
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run: |
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python -c "import torch; assert '${{ matrix.pytorch_version }}' in torch.__version__"
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- name: Ensure axolotl CLI was installed
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run: |
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axolotl --help
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- name: Pre-Download dataset fixture
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run: |
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huggingface-cli download --repo-type=dataset axolotl-ai-internal/axolotl-oss-dataset-fixtures
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- name: Run tests
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run: |
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pytest -v tests/conftest.py
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- name: Upload coverage to Codecov
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uses: codecov/codecov-action@v5
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with:
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token: ${{ secrets.CODECOV_TOKEN }}
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files: ./coverage.xml
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flags: unittests,pytorch-${{ matrix.pytorch_version }}
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fail_ci_if_error: false
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- name: cleanup pip cache
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run: |
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find "$(pip cache dir)/http-v2" -type f -mtime +14 -exec rm {} \;
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- name: Save HF cache
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id: hf-cache
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uses: actions/cache/save@v4
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with:
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path: |
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/home/runner/.cache/huggingface/hub/datasets--*
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/home/runner/.cache/huggingface/hub/models--*
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key: ${{ steps.hf-cache-restore.outputs.cache-primary-key }}
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# preload-cache:
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# name: Preload HF cache
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# runs-on: ubuntu-latest
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# strategy:
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# fail-fast: false
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# matrix:
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# python_version: ["3.11"]
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# pytorch_version: ["2.6.0"]
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# timeout-minutes: 20
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#
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# env:
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# AXOLOTL_IS_CI_CACHE_PRELOAD: "1"
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#
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# steps:
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# - name: Check out repository code
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# uses: actions/checkout@v4
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#
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# - name: Restore HF cache
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# id: hf-cache-restore
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# uses: actions/cache/restore@v4
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# with:
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# path: |
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# /home/runner/.cache/huggingface/hub/datasets--*
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# /home/runner/.cache/huggingface/hub/models--*
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# key: ${{ runner.os }}-hf-hub-cache-v2
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#
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# - name: Restore Cache from S3
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# id: hf-cache-restore-s3
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# run: |
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# mkdir -p /home/runner/.cache/huggingface/hub
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# curl -L https://d1dttdx32dkk5p.cloudfront.net/hf-cache.tar.zst | tar -xf - -C /home/runner/.cache/huggingface/hub/ --use-compress-program unzstd
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#
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# - name: Setup Python
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# uses: actions/setup-python@v5
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# with:
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# python-version: ${{ matrix.python_version }}
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# cache: 'pip' # caching pip dependencies
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#
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# - name: upgrade pip
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# run: |
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# pip3 install --upgrade pip
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# pip3 install --upgrade packaging==23.2 setuptools==75.8.0 wheel
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#
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# - name: Install PyTorch
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# run: |
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# pip3 install torch==${{ matrix.pytorch_version }}
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#
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# - name: Install dependencies
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# run: |
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# pip3 show torch
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# pip3 install --no-build-isolation -U -e .
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# python scripts/unsloth_install.py | sh
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# python scripts/cutcrossentropy_install.py | sh
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# pip3 install -r requirements-dev.txt -r requirements-tests.txt
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#
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# - name: Make sure PyTorch version wasn't clobbered
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# run: |
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# python -c "import torch; assert '${{ matrix.pytorch_version }}' in torch.__version__"
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#
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# - name: Ensure axolotl CLI was installed
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# run: |
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# axolotl --help
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#
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# - name: Pre-Download dataset fixture
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# run: |
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# huggingface-cli download --repo-type=dataset axolotl-ai-internal/axolotl-oss-dataset-fixtures
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#
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# - name: Run tests
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# run: |
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# pytest -v tests/conftest.py
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#
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# - name: Upload coverage to Codecov
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# uses: codecov/codecov-action@v5
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# with:
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# token: ${{ secrets.CODECOV_TOKEN }}
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# files: ./coverage.xml
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# flags: unittests,pytorch-${{ matrix.pytorch_version }}
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# fail_ci_if_error: false
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#
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# - name: cleanup pip cache
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# run: |
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# find "$(pip cache dir)/http-v2" -type f -mtime +14 -exec rm {} \;
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#
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# - name: Save HF cache
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# id: hf-cache
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# uses: actions/cache/save@v4
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# with:
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# path: |
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# /home/runner/.cache/huggingface/hub/datasets--*
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# /home/runner/.cache/huggingface/hub/models--*
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# key: ${{ steps.hf-cache-restore.outputs.cache-primary-key }}
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pytest:
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name: PyTest
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runs-on: ubuntu-latest
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needs: [preload-cache]
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# needs: [preload-cache]
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strategy:
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fail-fast: false
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matrix:
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- name: Check out repository code
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uses: actions/checkout@v4
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- name: Restore HF cache
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id: hf-cache-restore
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uses: actions/cache/restore@v4
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with:
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path: |
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/home/runner/.cache/huggingface/hub/datasets--*
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/home/runner/.cache/huggingface/hub/models--*
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key: ${{ runner.os }}-hf-hub-cache-v2
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# - name: Restore HF cache
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# id: hf-cache-restore
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# uses: actions/cache/restore@v4
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# with:
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# path: |
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# /home/runner/.cache/huggingface/hub/datasets--*
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# /home/runner/.cache/huggingface/hub/models--*
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# key: ${{ runner.os }}-hf-hub-cache-v2
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- name: Restore Cache from S3
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id: hf-cache-restore-s3
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run: |
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mkdir -p /home/runner/.cache/huggingface/hub
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curl -L https://d1dttdx32dkk5p.cloudfront.net/hf-cache.tar.zst | tar -xf - -C /home/runner/.cache/huggingface/hub/ --use-compress-program unzstd
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- name: Setup Python
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uses: actions/setup-python@v5
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pytest-sdist:
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name: PyTest from Source Dist
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runs-on: ubuntu-latest
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needs: [preload-cache]
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# needs: [preload-cache]
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strategy:
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fail-fast: false
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matrix:
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- name: Check out repository code
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uses: actions/checkout@v4
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- name: Restore HF cache
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id: hf-cache-restore
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uses: actions/cache/restore@v4
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with:
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path: |
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/home/runner/.cache/huggingface/hub/datasets--*
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/home/runner/.cache/huggingface/hub/models--*
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key: ${{ runner.os }}-hf-hub-cache-v2
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# - name: Restore HF cache
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# id: hf-cache-restore
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# uses: actions/cache/restore@v4
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# with:
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# path: |
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# /home/runner/.cache/huggingface/hub/datasets--*
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# /home/runner/.cache/huggingface/hub/models--*
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# key: ${{ runner.os }}-hf-hub-cache-v2
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- name: Restore Cache from S3
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id: hf-cache-restore-s3
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run: |
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mkdir -p /home/runner/.cache/huggingface/hub
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curl -L https://d1dttdx32dkk5p.cloudfront.net/hf-cache.tar.zst | tar -xf - -C /home/runner/.cache/huggingface/hub/ --use-compress-program unzstd
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- name: Setup Python
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uses: actions/setup-python@v5

cicd/e2e_tests.py

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@app.function(
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image=cicd_image,
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gpu=GPU_CONFIG,
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timeout=60 * 60,
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timeout=90 * 60, # 90 min
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cpu=8.0,
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memory=131072,
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volumes=VOLUME_CONFIG,

codecov.yml

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if_no_uploads: error
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if_not_found: success
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if_ci_failed: error
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only_pulls: false
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only_pulls: true
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flags: null
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paths: null
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patch:

docs/config.qmd

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@@ -505,6 +505,7 @@ save_strategy: # Set to `"no"` to skip checkpoint saves, `"epoch"` at end of eac
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save_steps: # Leave empty to save at each epoch, integer for every N steps. float for fraction of total steps
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saves_per_epoch: # number of times per epoch to save a checkpoint, mutually exclusive with save_steps
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save_total_limit: # Checkpoints saved at a time
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save_only_model: # Save only the model weights, skipping the optimizer. Using this means you can't resume from checkpoints.
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# Maximum number of iterations to train for. It precedes num_epochs which means that
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# if both are set, num_epochs will not be guaranteed.
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# e.g., when 1 epoch is 1000 steps => `num_epochs: 2` and `max_steps: 100` will train for 100 steps

tests/e2e/multigpu/solo/test_grpo.py

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"""
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)
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@pytest.mark.skip(reason="flaky test")
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@pytest.mark.parametrize(
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"num_gpus",
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[1, 2],
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current_env = os.environ.copy()
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env = {
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"NCCL_P2P_LEVEL": "NVL",
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"NCCL_P2P_LEVEL": "LOC",
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**current_env,
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"CUDA_VISIBLE_DEVICES": "1",
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"VLLM_DISABLE_COMPILE_CACHE": "1",
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f"{get_torch_dist_unique_port()}",
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],
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env={
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"NCCL_P2P_LEVEL": "NVL",
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"NCCL_P2P_LEVEL": "LOC",
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"NCCL_DEBUG": "INFO",
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**current_env,
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},
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)
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finally:
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recursive_kill(vllm_process)
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269+
@pytest.mark.skip(reason="flaky test")
268270
@pytest.mark.parametrize(
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"num_gpus",
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[1, 2],
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current_env = os.environ.copy()
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env = {
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"NCCL_P2P_LEVEL": "NVL", # nccl can be brittle, assume P2P isn't reliable
325+
"NCCL_P2P_LEVEL": "LOC", # nccl can be brittle, assume P2P isn't reliable
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**current_env,
325327
"CUDA_VISIBLE_DEVICES": "1",
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"VLLM_DISABLE_COMPILE_CACHE": "1",
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f"{get_torch_dist_unique_port()}",
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],
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env={
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"NCCL_P2P_LEVEL": "NVL",
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"NCCL_P2P_LEVEL": "LOC",
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"NCCL_DEBUG": "INFO",
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**current_env,
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},

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