Weekly compatibility tests against oldest supported PyTorch - #745
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Implements the weekly testing regime documented in docs/installation.rst (Notes on Testing, Compatibility, and Distribution): build and test main against the oldest PyTorch version that publishes wheels for the lowest CUDA version implied by the stable-PyTorch policy. For the PyTorch 2.13 matrix that is PyTorch 2.9.1 with CUDA 13.0. - .github/versions.json: record the tested versions under weekly_compat so they are updated alongside the rest of the version matrix. - load-versions.yml: expose compat-torch-version, compat-torch-full-version, compat-cuda-version, compat-cuda-tag, and compat-cuda-patch outputs. - weekly-compat.yml: new scheduled workflow (Saturdays 8am UTC, plus manual dispatch) mirroring the cu130 build/test pipeline without the PR-merge plumbing: EC2 CPU runner builds the wheel and gtests against the compat PyTorch/CUDA pin, then an EC2 GPU runner runs gtests and the Python unit tests. Doc tests are omitted since the documentation examples target the current in-development versions. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Signed-off-by: Jonathan Swartz <jonathan@jswartz.info>
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Implements the weekly testing regime described in the installation docs (Notes on Testing, Compatibility, and Distribution): test fvdb-core weekly against the oldest PyTorch version that publishes wheels for the lowest CUDA version implied by the "stable PyTorch's latest two CUDA versions" policy. For the PyTorch 2.13 matrix (#738) that is PyTorch 2.9.1 with CUDA 13.0 (verified against the versions published on download.pytorch.org/whl/cu130).
Changes:
.github/versions.json: newweekly_compatblock recording the tested torch/cuda versions, so they get reviewed and updated alongside the rest of the version matrix each cycle..github/workflows/load-versions.yml: new outputscompat-torch-version,compat-torch-full-version,compat-cuda-version,compat-cuda-tag, andcompat-cuda-patch(the container-image patch is looked up from the existingcuda.versionsmap, so the compat CUDA must be one of the supported versions — which the policy guarantees)..github/workflows/weekly-compat.yml: new scheduled workflow (Saturdays 8am UTC +workflow_dispatch) mirroring thecu130.ymlpipeline without thepull_request_targetmerge plumbing: provision EC2 CPU runner → build wheel/gtests against the compat PyTorch/CUDA pin → provision EC2 GPU runner → run gtests and Python unit tests → tear down runners.CHANGES.md: note the new weekly compatibility testing under 0.6.0.Notes:
pytest --markdown-docs) are intentionally omitted: the documentation examples pin the current in-development versions, not the compat versions.actionlint,zizmor --persona=regular, and the repo's EC2 runner-token policy check locally.weekly_compatvalues are a deliberate second source of truth fromtorch.version: at each new dev cycle (like PyTorch 2.13 #738), whoever bumps the matrix consults PyTorch's release compatibility matrix and updatesweekly_compatper the policy.🤖 Generated with Claude Code