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SparseML v0.9.0
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@jeanniefinks jeanniefinks released this 01 Dec 16:07
· 1 commit to release/0.9 since this release
v0.9.0
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Learn about vigilant mode.

New Features:

  • dbolya/yolact integration added with recipes, tutorial, and performant models for the YOLACT segmentation model.
  • Automatic recipe creation API for pruning recipes added, create_pruning_recipe, along with base class implementations for future expansion of RecipeEditor and RecipeBuilder.
  • Structured pruning now supported for channels and filters with StructuredPruningModifier and LayerThinningModifier.
  • PyTorch QAT pipelines: added support for automatic fusing of Conv-ReLU blocks, FPN layers, and Convs with shared weights.
  • Analyzer implementations for evaluating a model's performance and loss sensitivity to pruning and other algorithms added for ONNX framework.
  • Up-to-date version check implemented for SparseML.

Changes:

  • Automatically unwrap PyTorch distributed modules so recipes do not need to be changed for distributed pipelines.
  • BERT recipes updated to use the distillation modifier.
  • References to num_sockets for the DeepSparse engine were removed following the deprecated support for DeepSparse 0.9.
  • Changed the block pruning flow to use FourBlockMaskCreator for block sparsity which will not impose any constraint on the divisibility of the channel's dimensions to be pruned on with the block size.
  • API docs recompiled.

Resolved Issues:

  • Improper variable names corrected that were causing crashes for specific flows in the WoodFisher pruning algorithm.

Known Issues:

  • None
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