version 1.24.0

aimetci released this 20 Jan 00:18

· 1414 commits to develop since this release

eda99b2

What's New

Export quantsim configuration for configuring downstream target quantization

PyTorch

Fixes to resolve minor accuracy diffs in the learnedGrid quantizer for per-channel quantization
Added support for AMP 2.0 which enables faster automatic mixed precision
Added support for QAT for INT4 quantized models – includes a feature for performing BN Re-estimation after QAT

Keras

Added support for AMP 2.0 which enables faster automatic mixed precision
Support for basic transformer networks
Added support for subclassed models. The current subclassing feature includes support for only a single level of subclassing and does not support lambdas.
Added QAT per-channel gradient support
Minor updates to the quantization configuration
Fixed QuantSim bug where layers using dtypes other than float were incorrectly quantized

TensorFlow

Added an additional prelu mapping pattern to ensure proper folding and quantsim node placement
Fixed per-channel encoding representation to align with Pytorch and Keras

Documentation

Release main page: https://github.com/quic/aimet/releases/tag/1.24.0
Installation guide: https://quic.github.io/aimet-pages/releases/1.24.0/install/index.html
User guide: https://quic.github.io/aimet-pages/releases/1.24.0/user_guide/index.html
API documentation: https://quic.github.io/aimet-pages/releases/1.24.0/api_docs/index.html
Documentation main page: https://quic.github.io/aimet-pages/index.html

Assets 16