This repository was archived by the owner on Jun 4, 2025. It is now read-only.
Temporary patch for quant transfer learning issues #76
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
This was referenced Jun 29, 2022
KSGulin
added a commit
that referenced
this pull request
Jun 29, 2022
KSGulin
added a commit
that referenced
this pull request
Jun 29, 2022
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
1 participant
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Outdated suggestions cannot be applied.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.
Currently, trying to run quant transfer learning will lead to errors, as the checkpoint recipe includes a QAT modifier.
The primary fix needs to implemented in SparseML and ZooModels. This PR provides a temporary patch which gets around the issue by removing the the QAT modifier from the checkpoint recipe when a model is loaded for training. Additional logic is added for handling model saving and one-shot sparsification in this regime.
In addition, a bug where using the "--resume" keyword would increase the total epochs is fixed.