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SparseML v1.5.0
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@jeanniefinks jeanniefinks released this 07 Jun 05:57
· 424 commits to main since this release
v1.5.0
61a2097
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New Features:

  • PyTorch 1.13 support (#1143)
  • Enabled patch versions for torchvision 0.14.x (#1557)
  • YOLOv8 sparsification pipelines (view)
  • Per layer distillation support for PyTorch Distillation modifier (#1272)
  • Torchvision training pipelines:
    • Wandb, TensorBoard, and console logging (#1299)
    • DataParallel module (#1332)
    • Distillation (#1310)
  • Product usage analytics tracking; to disable, run the command export NM_DISABLE_ANALYTICS=True (#1487)

Changes:

  • Transformers and YOLOv5 integrations migrated from auto install to install from PyPI packages. Going forward, pip install sparseml[transformers] and pip install sparseml[yolov5] will need to be used.
  • Error message updated when utilizing wandb loggers and wandb is not installed in the environment, telling user to pip install wandb. (#1374)
  • Keras and TensorFlow tests have been removed; these are no longer actively supported pathways.
  • scikit-learn now replaced with sklearn to stay current with dependency name changes. (#1294)

Resolved Issues:

  • Using recipes that utilized the legacy PyTorch QuantizationModifier with DDP when restoring weights for sparse transfer no longer crashes. (#1490)
  • If labels were not being set correctly when utilizing a distillation teacher different from the student with token classification pipelines, training runs would crash. (#1414)
  • Q/DQ folding fixed on ONNX export for quantization nodes occurring before Softmax in transformer graphs; performance issues would result for some transformer models in DeepSparse. (#1343)
  • Inaccurate metrics calculations for torchvision training pipelines led to discrepancies in top1 and top5 accuracies by ~1%. (#1341)

Known Issues:

  • None
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