AIMET Release Notes

Release Notes for Qualcomm AI Model Efficiency ToolKit (AIMET)

1.22.2

Tensorflow

• Added support for supergroups : MatMul + Add

• Added support for TF-Slim BN name with backslash

• Added support for Depthwise + Conv in CLS

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.22.2

• User guide: https://quic.github.io/aimet-pages/releases/1.22.2/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.22.2/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.22.1

• Added support for QuantizableMultiHeadAttention for PyTorch nn.transformer layers by @quic-kyuykim

• Support functional conv2d in model preparer by @quic-kyuykim

• Enable qat with multi gpu by @quic-mangal

• Optimize forward pass logic of PyTorch QAT 2.0 by @quic-geunlee

• Fix functional depthwise conv support on model preparer by @quic-kyuykim

• Fix bug in model validator to correctly identify functional ops in leaf module by @quic-klhsieh

• Support dynamic functional conv2d in model preparer by @quic-kyuykim

• Added updated default runtime config, also a per-channel one. Fixed n… by @quic-akhobare

• Include residing module info in model validator by @quic-klhsieh

• Support for Keras MultiHeadAttention Layer by @quic-ashvkuma

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.22.1

• User guide: https://quic.github.io/aimet-pages/releases/1.22.1/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.22.1/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.22.0

• Support for simulation and QAT for PyTorch transformer models (including support for torch.nn mha and encoder layers)

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.22.0

• User guide: https://quic.github.io/aimet-pages/releases/1.22.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.22.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.21.0

• 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

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.21.0

• 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

1.20.0

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.20.0

• User guide: https://quic.github.io/aimet-pages/releases/1.20.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.20.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.19.1.py37

• PyTorch: Added CLE support for Conv1d, ConvTranspose1d and Depthwise Separable Conv1d layers

• PyTorch: Added High-Bias Fold support for Conv1D layer

• PyTorch: Modified Elementwise Concat Op to support any number of tensors

• Minor dependency fixes

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.19.1.py37

• User guide: https://quic.github.io/aimet-pages/releases/1.19.1/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.19.1/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.19.1

• PyTorch: Added CLE support for Conv1d, ConvTranspose1d and Depthwise Separable Conv1d layers

• PyTorch: Added High-Bias Fold support for Conv1D layer

• PyTorch: Modified Elementwise Concat Op to support any number of tensors

• Minor dependency fixes

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.19.1

• User guide: https://quic.github.io/aimet-pages/releases/1.19.1/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.19.1/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.18.0.py37

• Multiple bug fixes

• Additional feature examples for PyTorch and TensorFlow

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.18.0.py37

• User guide: https://quic.github.io/aimet-pages/releases/1.18.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.18.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.18.0

• Multiple bug fixes

• Additional feature examples for PyTorch and TensorFlow

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.18.0

• User guide: https://quic.github.io/aimet-pages/releases/1.18.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.18.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.17.0.py37

• Add Adaround TF feature

• Added Examples for Torch quantization, and Channel Pruning & Spatial SVD compression

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.17.0.py37

• User guide: https://quic.github.io/aimet-pages/releases/1.17.0.py37/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.17.0.py37/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.17.0

• Add Adaround TF feature

• Added Examples for Torch quantization, and Channel Pruning & Spatial SVD compression

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.17.0

• User guide: https://quic.github.io/aimet-pages/releases/1.17.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.17.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.16.2.py37

• Added a new post-training quantization feature called AdaRound, which stands for AdaptiveRounding

• Quantization simulation and QAT now also support recurrent layers (RNN, LSTM, GRU)

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.16.2.py37

• User guide: https://quic.github.io/aimet-pages/releases/1.16.2.py37/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.16.2.py37/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.16.2

• Added a new post-training quantization feature called AdaRound, which stands for AdaptiveRounding

• Quantization simulation and QAT now also support recurrent layers (RNN, LSTM, GRU)

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.16.2

• User guide: https://quic.github.io/aimet-pages/releases/1.16.2/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.16.2/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.16.1.py37

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.16.1.py37

• User guide: https://quic.github.io/aimet-pages/releases/1.16.1.py37/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.16.1.py37/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.16.1

• Added separate packages for CPU and GPU models. This allows users with CPU-only hosts to run AIMET.

• Added separate packages for PyTorch and TensorFlow. Reduces the number of dependencies that users would need to install.

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.16.1

• User guide: https://quic.github.io/aimet-pages/releases/1.16.1/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.16.1/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.16.0

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.16.0

• User guide: https://quic.github.io/aimet-pages/releases/1.16.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.16.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.14.0

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.14.0

• User guide: https://quic.github.io/aimet-pages/releases/1.14.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.14.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html

1.13.0

Documentation

• User guide: https://quic.github.io/aimet-pages/releases/1.13.0/user_guide/index.html

• API documentation: https://quic.github.io/aimet-pages/releases/1.13.0/api_docs/index.html

• Documentation main page: https://quic.github.io/aimet-pages/index.html