Release version 0.8.0
What's Changed
- Add support for PyTorch 1.11-1.13.1. Brevitas 0.8 supports PyTorch 1.5.1 to 1.13.1, with 1.10+ suggested.
- Deprecate support for Python 3.6, 3.7+ is now required.
- Add support for export to ONNX QCDQ for <= int8 quantization, for out of the box execution with onnxruntime or similar backends.
- Extend support for export to ONNX QOps to <= int8 quantization, for out of the box execution with onnxruntime or similar backends.
- Add experimental support for export to torch QCDQ for <= int32 quantization, as an entry point for future MLIR integration with torch-mlir.
- Add support for QuantRNN, QuantLSTM, w/ support for CIFG, bidirectional layers, shared input-hidden gates, shared quantizers, training-time JIT compilation, and partial export support to ONNX (QONNX and QCDQ).
- Improve support for zero-point for both weights and activations quantization.
- New default asymmetric activation quantizer based on percentile rather than min/max.
- Add more built-in quantizers (symmetric per-channel, asymmetric per-channel, symmetric decoupled per-channel).
- Simplify interface for activation calibration.
- Simplify interface for bias correction.
- Initial support for QuantEmbedding.
- Deprecate support for XIR and PyXIR export flows.
- Many bug fixes and minor improvements.
New Contributors
- @fd0r made their first contribution in #434
- @omarperacha made their first contribution in #483
- @andrei-stoian-zama made their first contribution #470
Full Changelog: v0.7.1...v0.8.0