fix precision of fp8 moe#737
Open
devalshahamd wants to merge 4 commits into
Open
Conversation
Contributor
There was a problem hiding this comment.
Pull request overview
This PR updates the MoE performance model’s compute-precision selection logic to special-case certain input dtypes, aiming to treat "fp8" and "bf16" inputs as "fp8" compute precision for the fused blockscale MoE model.
Changes:
- Adjusted
get_compute_precision()in the AITER FP8 block-scale fused MoE extension to return"fp8"for"fp8"/"bf16"input dtypes instead of always usingtorch_dtype_map().
💡 Add Copilot custom instructions for smarter, more guided reviews. Learn how to get started.
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
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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 pull request makes a targeted change to the
get_compute_precisionmethod inmoe_perf_model_extensions.pyto ensure that when the input data type is either"fp8"or"bf16", the method returns"fp8"instead of mapping the type usingtorch_dtype_map. This likely addresses a specific requirement for handling these data types in the performance model.get_compute_precisionmethod inmoe_perf_model_extensions.pyto return"fp8"when the input data type is"fp8"or"bf16", otherwise it falls back totorch_dtype_map(dtype)