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SparseML v0.3.0
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@jeanniefinks jeanniefinks released this 30 Apr 23:52
· 13 commits to release/0.3 since this release
v0.3.0
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New Features:

  • YOLO integration with Ultralytics deployed including DeepSparse examples for benchmarking and running detection over videos.
  • Framework and Sparsification Info APIs now available for all supported ML frameworks.
  • Properties added to the ScheduledManager class to allow for lookup of contained modifiers such as pruning and quantization.
  • ALL_PRUNABLE token added for pruning modifiers.
  • PyTorch global magnitude pruning support implemented.
  • QAT support added for BERT.

Changes:

  • Version changed to be loaded from version.py file, default build on branches is now nightly.
  • Additional unit tests added in for Keras integration.
  • PyTorch max supported version updated to 1.7.
  • Improved performance for parsing and fixing QAT ONNX graphs from PyTorch.

Resolved Issues:

  • Docs typos and broken links addressed.
  • Pickling models with PyTorch pruning hooks work as expected.
  • Incorrect loss scaling for DDP in PyTorch vision.py script addressed.

Known Issues:

  • None
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