Fixed SVD interpreter test#1375
Merged
jlarson4 merged 2 commits intoJun 9, 2026
Merged
Conversation
Collaborator
|
@has9800 This looks great, I just need you to run If you see any CI runs that 429, just let me know and I can re-run them. |
Author
|
Hey I've ran |
Collaborator
|
Excellent! Merging now, thanks for tackling this |
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.
Description
This fixes the SVD interpreter tests that skipped due to the fixtures not always satisfying the test requirements.
I replaced the model fixtures with two distinct GPT2 models from
supported_models.json. The primary model is multi-layer and is compatible for the 4 vector SVD comparisons, and the secondary model is distinct so the cross-model test doesnt fall back to using the same model.The
pytest.skip(...)guards are also removed.Changes:
Intel/tiny-random-gpt2as the primary model so the comparison test uses a small multi-layer model.hyper-accel/tiny-random-gpt2as the secondary model so the cross model test uses a distinct model.pytest.skip(...)guards from the two tests.Result: 7 passed, 2 warnings (dependency deprecation warnings)
Fixes #1327
Type of change
Checklist: