Skip to content
This repository was archived by the owner on Jun 3, 2025. It is now read-only.

SparseML v0.5.0

Choose a tag to compare

View all tags
@jeanniefinks jeanniefinks released this 28 Jun 18:06
· 1 commit to release/0.5 since this release
v0.5.0
8502988
This commit was created on GitHub.com and signed with GitHub’s verified signature. The key has expired.
GPG key ID: 4AEE18F83AFDEB23
Expired
Verified
Learn about vigilant mode.

New Features:

  • research folder added to root directory intended for research contributions.
  • First research contributions added for information retrieval.
  • Tutorial for sparsifying BERT on the SQuAD dataset created.
  • LayerPruningModifier and LearningRateFunctionModifier implementations added for PyTorch.

Changes:

  • Hugging Face transformers integration reworked to match new integration standards.
  • CIFAR data augmentations updated for PyTorch datasets.
  • Pruning algorithms using a pruning scorer object for better extensibility refactored with new pruning methods.

Resolved Issues:

  • If the source URL is down, tests no longer fail for VOC dataset.
  • Because the DeepSparse API includes more information for kernel sparsify performance analysis, previously failing tests have been updated to correctly check and return the updated info.
  • Models with more than 1 input can now complete the PyTorch ONNX export process.
  • Edge cases and better defaults improved with the WoodFisher/M-FAC algorithm for better recovery.
  • Deprecated use of torch.nonzero API call in the pruning modifiers to .nonzero(as_tuple=False).

Known Issues:

  • None
Assets 3
Loading