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SparseML v1.4.0
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@jeanniefinks jeanniefinks released this 17 Feb 20:06
· 13 commits to release/1.4 since this release
v1.4.0
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New Features:

  • OpenPifPaf training prototype support (#1171)
  • Layerwise distillation support for the PyTorch DistillationModifier (#1272)
  • Recipe template API added in PyTorch for simple creation of default recipes (#1147)
  • Ability to create sample inputs and outputs on export for transformers, YOLOv5, and image classification pathways (#1180)
  • Loggers and one-shot support for torchvision training script (#1299, #1300)

Changes:

  • Refactored the ONNX Export pipeline to standardize implementations, adding functionality for more complicated models, and adding better debugging support. (#1192)
  • Refactored the PyTorch QuantizationModifier to expand supported models and operators and simplify the interface. (#1183)
  • YOLOv5 integration upgraded to the latest upstream. (#1322)

Resolved Issues:

  • recipe_template CLI no longer has improper code documentation, impairing operability. (#1170)
  • ONNX export now enforces that all quantized graphs will have unit8 values. fixing issues for some quantized models that were crashing in DeepSparse. (#1181)
  • Changed over to vector_norm for PyTorch pruning modifiers that were leading to crashes in older PyTorch versions. (#1167)
  • Model loading for torchvision script fixed where models were failing on load unless a recipe was supplied. (#1281)

Known Issues:

  • None
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