version 1.31.0

What's New

• ONNX
  • Added support for custom ops in QuantSim, CLE, AdaRound and AMP.
  • Added support for Quant Analyzer.
• Keras
  • Added support for unrolled quantized LSTM with only Quantsim in PTQ mode.
  • Fix for ReLU Encoding min going past 0 for QAT.
  • Fixes Input Quantizers for TFOpLambda Layers (kwargs)
  • Fixes logic for placing input quantizers

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.31.0
• Installation guide: https://quic.github.io/aimet-pages/releases/1.31.0/install/index.html
• User guide: https://quic.github.io/aimet-pages/releases/1.31.0/user_guide/index.html
• API documentation: https://quic.github.io/aimet-pages/releases/1.31.0/api_docs/index.html

Packages

• aimet_torch-torch_gpu_1.31.0-cp38-cp38-linux_x86_64.whl
  • PyTorch 1.13 GPU package with Python 3.8 and CUDA 11.x - Recommended for use with PyTorch models
• aimet_torch-torch_cpu_1.31.0-cp38-cp38-linux_x86_64.whl
  • PyTorch 1.13 CPU package with Python 3.8 - If installing on a machine without CUDA
• aimet_torch-torch_cpu_pt19_1.31.0-cp38-cp38-linux_x86_64.whl
  • PyTorch 1.9 CPU package with Python 3.8 - If installing on a machine without CUDA
• aimet_tensorflow-tf_gpu_1.31.0-cp38-cp38-linux_x86_64.whl
  • TensorFlow 2.10 GPU package with Python 3.8 - Recommended for use with TensorFlow models
• aimet_tensorflow-tf_cpu_1.31.0-cp38-cp38-linux_x86_64.whl
  • TensorFlow 2.10 CPU package with Python 3.8 - If installing on a machine without CUDA
• aimet_onnx-onnx_gpu_1.31.0-cp38-cp38-linux_x86_64.whl
  • ONNX 1.11.0 GPU package with Python 3.8 - Recommended for use with ONNX models
• aimet_onnx-onnx_cpu_1.31.0-cp38-cp38-linux_x86_64.whl
  • ONNX 1.11.0 CPU package with Python 3.8 - If installing on a machine without CUDA