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version 1.24.0

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@aimetci aimetci released this 20 Jan 00:18
· 782 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