Test PARQ with torchao activation quantization #2370
Merged
Conversation
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
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/ao/2370
Note: Links to docs will display an error until the docs builds have been completed. ⏳ No Failures, 1 PendingAs of commit ec68ca9 with merge base 5bdc25d ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
facebook-github-bot
added
the
CLA Signed
lisjin
added
the
topic: improvement
andrewor14
approved these changes
Jun 16, 2025
| self._dequantize = dequantize_affine | ||
| elif zero_point_domain == ZeroPointDomain.NONE: | ||
| self._quantize = quantize_affine_no_zero_point | ||
| self._dequantize = dequantize_affine_no_zero_point |
There was a problem hiding this comment.
These changes aren't required to make the test pass right, just for clean ups? (we can keep them in this PR, just wanted to ask for my understanding)
There was a problem hiding this comment.
Yes, this is just for simplification!
metascroy
approved these changes
Jun 16, 2025
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Outdated suggestions cannot be applied.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.
Added a test case to show numerical equivalency between quantizing:
UnifTorchaoQuantizer+ int8 activations with torchao'sFakeQuantizeConfigInt8DynamicActivationIntxWeightConfigNext steps with target
EmbeddingQuantizerandPackedLinearInt8DynamicActivationIntxWeightLayout.