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SparseML v0.7.0
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@jeanniefinks jeanniefinks released this 13 Sep 16:47
v0.7.0
8dda5e7

New Features:

  • Support added for
    • PyTorch 1.9.0.
    • Python 3.9.
    • ONNX versions 1.8 - 1.10.
  • PyTorch QATWrapper class to support quantization of custom modules through recipes added.
  • PyTorch image classification sparse transfer learning recipe and tutorial created.
  • Generic benchmarking API provided that can be overwritten for specific framework implementations.
  • M-FAC (WoodFisher) pruning implemented along with relat3ed documentation, and tutorials for one-shot and training-aware: https://arxiv.org/abs/2004.14340

Changes:

  • Performance sensitivity analysis tests updated to respect new information coming from a change in the DeepSparse analysis API.

Resolved Issues:

  • Repeated apply calls no longer occur for PyTorch pruning masks.
  • Neural Magic dependencies no longer require only matching major.minor versions (allow any bug version).
  • Support added for getting nightly versions if installed for framework info and Neural Magic package versions.

Known Issues:

  • Hugging Face transformers integrations with num_epochs override from recipes is not currently working. The workaround is to set the num_epochs argument to the maximum number of epochs in the recipe.
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