[upstream_ut] RuntimeError: _histc_xpu does not have a deterministic implementation, but you set 'torch.use_deter #15
Draft
Stonepia wants to merge 1 commit into
Draft
[upstream_ut] RuntimeError: _histc_xpu does not have a deterministic implementation, but you set 'torch.use_deter
#15Stonepia wants to merge 1 commit into
Stonepia wants to merge 1 commit into
Conversation
[upstream_ut] RuntimeError: _histc_xpu does not have a deterministic implementation, but you set 'torch.use_deter
7 tasks
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
[upstream_ut] RuntimeError: _histc_xpu does not have a deterministic implementation, but you set 'torch.use_deter
Fixes intel/torch-xpu-ops#2512
Root Cause: The bundled third_party/torch-xpu-ops copy of SummaryOps.cpp (line 45) calls alertNotDeterministic("_histc_xpu") without the "with floating point input" qualifier, and also calls it unconditionally (no floating-point type check). The local torch-xpu-ops repo has been updated to guard the alert with
if (at::isFloatingType(self.scalar_type()))and use the message "_histc_xpu with floating point input", but this fix was not synced into pytorch/third_party/torch-xpu-ops. The test expects the message prefix "_histc_xpu with floating point input" which only matches the updated local version.Failed Tests:
test_torch_xpu.py::TestTorchDeviceTypeXPU::test_nondeterministic_alert_histc_xpu_float32Diff stat: