-
Notifications
You must be signed in to change notification settings - Fork 685
Bump torchao pin and use v2 torchao tensors #14171
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Conversation
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14171
Note: Links to docs will display an error until the docs builds have been completed. ✅ You can merge normally! (19 Unrelated Failures)As of commit 164f489 with merge base 56d5186 ( FLAKY - The following jobs failed but were likely due to flakiness present on trunk:
BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
This comment was automatically generated by Dr. CI and updates every 15 minutes. |
This PR needs a
|
38a2dc6
to
7339ce1
Compare
Summary: `quantize_()` modifies model in place, we need to make a copy to avoid making changes to user passed model. Fix a bug as discussed in pytorch#14171 (comment) Differential Revision: D82167495
…ge (pytorch#14186) Summary: `quantize_()` modifies model in place, we need to make a copy to avoid making changes to user passed model. Fix a bug as discussed in pytorch#14171 (comment) Differential Revision: D82167495
…ge (pytorch#14186) Summary: `quantize_()` modifies model in place, we need to make a copy to avoid making changes to user passed model. Fix a bug as discussed in pytorch#14171 (comment) Differential Revision: D82167495
164f489
to
46cb5b6
Compare
# Test with different group sizes | ||
for group_size in [8, 16, 32]: | ||
with self.subTest(group_size=group_size): | ||
model_to_export = copy.deepcopy(model) |
There was a problem hiding this comment.
Choose a reason for hiding this comment
The reason will be displayed to describe this comment to others. Learn more.
@metascroy can you try without a copy here, as the PR i landed should take care of this within the source transform stage.
This PR bumps the torchao pin in ExecuTorch, and adjusts the code in ExecuTorch to rely less on deprecated features. In particular, * torchao/experimental folder is being deprecated, so we switch embedding / tied embedding quantizers to their new home * v1 tensors based on AffineQuantizedTensor + QDQLayout are being deprecated. This switches ExecuTorch to use v2 tensors. See pytorch/ao#2967.
This PR bumps the torchao pin in ExecuTorch, and adjusts the code in ExecuTorch to rely less on deprecated features. In particular,