SparseML v0.3.1 Patch Release
This is a patch release for 0.3.0 that contains the following changes:
- DeepSparse APIs now properly referencing VNNI check
- Block sparse masks now applied for pruning modifiers
- Some tests marked as flaky to make tests more consistent
- Docs updated for new Discourse and Slack links
- Modifier code refactored to better support Automatic Mixed Precision Training (AMP) in PyTorch
- Emulated_step added to manager for inconsistent steps_per_epoch in PyTorch
- Serialization of block sparse-enabled pruning modifiers no longer fail on reload