[benchmarks] Set matrix multiplication precision. #7748
Merged
Conversation
This file contains 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
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Outdated suggestions cannot be applied.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.
This PR modifies PyTorch/XLA benchmarking scripts so that we execute the benchmarks with the same precision as what we are setting for PyTorch.
Previously, we only called
torch.set_float32_matmul_precision('high'), leaving PyTorch/XLA precision to be the default one. Now, we are also callingtorch_xla._XLAC._xla_set_mat_mul_precision('high').Additionally, this PR also replaces
_xla_set_use_full_mat_mul_precisionby_xla_set_mat_mul_precision, making the precision set more explicit and translatable between PyTorch and PyTorch/XLA.cc @miladm @JackCaoG @zpcore