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SparseML v1.2.0
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@jeanniefinks jeanniefinks released this 28 Oct 00:46
v1.2.0
8bf07ea
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New Features:

  • Document classification training and export pipelines added for transformers integration.

Changes:

  • Refactor of transformers training and export integration code now enables more code reuse across use cases.
  • List of supported quantized nodes expanded to enable more complex quantization patterns for ResNet-50 and MobileBERT enabling better performance for similar models.
  • Transformers integration expanded to enable saving and reloading of optimizer state from trained checkpoints.
  • Deployment folder added for image classification integration which will export to deployment.
  • Gradient accumulation support added for image classification integration.
  • Minimum Python version changed to 3.7 as 3.6 as reached EOL.

Resolved Issues:

  • Quantized checkpoints for image classification models now instantiates correctly, no longer leading to random initialization of weights rather than restore.
  • TraininableParamsModifier for PyTorch now enables and disables params properly so weights are frozen while training.
  • Quantized embeddings no longer causes crashes while training with distributed data parallel.
  • Improper EfficientNet definitions fixed that would lead to accuracy issues due to convolutional strides being duplicated.
  • Protobuf version for ONNX 1.12 compatibility pinned to prevent install failures on some systems.

Known Issues:

  • None
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