version 1.21.0
This release has the following changes
- New feature: PyTorch QuantAnalyzer - Visualize per-layer sensitivity and per-quantizer PDF histograms
- New feature: TensorFlow AutoQuant - Automatically apply various AIMET post-training quantization techniques
- PyTorch QAT with Range Learning: Added support for Per Channel Quantization
- PyTorch: Enabled exporting of encodings for multi-output leaf module
- TensorFlow Adaround
- Added ability to use configuration file in API to adapt to a specific runtime target
- Added Per-Channel Quantization support
- TensorFlow QuantSim: Added support for FP16 inference and QAT
- TensorFlow Per Channel Quantization
- Fixed speed and accuracy issues
- Fixed zero accuracy for 16-bits per channel quantization
- Added support for DepthWise Conv2d Op
- Multiple other bug fixes
User guide: https://quic.github.io/aimet-pages/releases/1.21.0/user_guide/index.html
API documentation: https://quic.github.io/aimet-pages/releases/1.21.0/api_docs/index.html
Documentation main page: https://quic.github.io/aimet-pages/index.html