Problem
The repository-wide GPU CI environment currently pins PyTorch 2.10, while the supported torch.compile releases are PyTorch 2.11 and 2.12, with PyTorch 2.13 support added by #5910. Consequently, pt_expt compile-only tests cannot run on GPU CI under a supported PyTorch release.
This supported-version GPU coverage gap predates #5913. That PR only makes the existing contract explicit by using the shared compile-version gate, so the PyTorch 2.10 CUDA job now skips compile-only tests instead of exercising an unsupported configuration.
The compile path has been manually validated on CUDA with PyTorch 2.11, 2.12, and 2.13. The repository-wide GPU pin cannot currently be raised because of unrelated CI compatibility issues, and changing that pin is outside the scope of #5913.
Desired coverage
- Run the focused pt_expt compile tests on a GPU with at least one supported PyTorch release.
- Exercise CUDA-specific compile safeguards such as forced int64 indexing and the constrained Triton tiling configuration.
- Preserve the existing PyTorch 2.10 eager CUDA coverage until the unrelated CI blockers allow the global GPU pin to move.
Related
Problem
The repository-wide GPU CI environment currently pins PyTorch 2.10, while the supported
torch.compilereleases are PyTorch 2.11 and 2.12, with PyTorch 2.13 support added by #5910. Consequently, pt_expt compile-only tests cannot run on GPU CI under a supported PyTorch release.This supported-version GPU coverage gap predates #5913. That PR only makes the existing contract explicit by using the shared compile-version gate, so the PyTorch 2.10 CUDA job now skips compile-only tests instead of exercising an unsupported configuration.
The compile path has been manually validated on CUDA with PyTorch 2.11, 2.12, and 2.13. The repository-wide GPU pin cannot currently be raised because of unrelated CI compatibility issues, and changing that pin is outside the scope of #5913.
Desired coverage
Related