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SparseML v0.5.0
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@jeanniefinks jeanniefinks released this 28 Jun 18:06
· 1 commit to release/0.5 since this release
v0.5.0
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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
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