[MPS] Activation kernels: do compute at float precision #155735
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/155735
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (3 Unrelated Failures)As of commit a411222 with merge base d4d0ede ( BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
UNSTABLE - The following job is marked as unstable, possibly due to flakiness on trunk:
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| const T grad_output, | ||
| const T negative_slope) { | ||
| return self > T(0) ? grad_output : grad_output * negative_slope; | ||
| return float(self) > 0.0f |
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Just curious if there are every a situation when compiler will not be able to infer types here
| return float(self) > 0.0f | |
| return self > 0. |
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@pytorchbot merge -i |
Merge startedYour change will be merged while ignoring the following 2 checks: pull / linux-jammy-py3-clang12-executorch / test (executorch, 1, 1, linux.2xlarge), pull / cuda12.8-py3.10-gcc9-sm75 / test (pr_time_benchmarks, 1, 1, linux.g4dn.metal.nvidia.gpu) Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
Merge failedReason: 1 jobs have failed, first few of them are: trunk / linux-jammy-rocm-py3.10 / test (default, 1, 2, linux.rocm.gpu.2) Details for Dev Infra teamRaised by workflow job |
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@pytorchbot merge -f "This should be fine" |
Merge startedYour change will be merged immediately since you used the force (-f) flag, bypassing any CI checks (ETA: 1-5 minutes). Please use Learn more about merging in the wiki. Questions? Feedback? Please reach out to the PyTorch DevX Team |
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