version 1.32.0

What's New

• PyTorch
  • Added MultiGPU support for Adaround.
  • Upgraded AIMET to support PyTorch version 2.1 as a new variant. AIMET with PyTorch version 1.13 remains the default.
• Keras
  • For models with SeparableConv2D layers, use model_preparer first before applying any quantization API.
• Common
  • Upgraded AIMET to support Ubuntu22 and Python3.10 for all AIMET variants.

Documentation

• Release main page: https://github.com/quic/aimet/releases/tag/1.32.0
• Installation guide: https://quic.github.io/aimet-pages/releases/1.32.0/install/index.html
• User guide: https://quic.github.io/aimet-pages/releases/1.32.0/user_guide/index.html
• API documentation: https://quic.github.io/aimet-pages/releases/1.32.0/api_docs/index.html

Packages

• aimet_torch_gpu_pt21-1.32.0.cu118-cp310-cp310-manylinux_2_34_x86_64.whl
  • PyTorch 2.1 GPU package with Python 3.10 and CUDA 11
• aimet_torch_gpu-1.32.0.cu117-cp310-cp310-manylinux_2_34_x86_64.whl
  • PyTorch 1.13 GPU package with Python 3.10 and CUDA 11.x
• aimet_torch_cpu_pt21-1.32.0.cpu-cp310-cp310-manylinux_2_34_x86_64.whl
  • PyTorch 2.1 CPU package with Python 3.10 - If installing on a machine without CUDA
• aimet_torch_cpu-1.32.0.cpu-cp310-cp310-manylinux_2_34_x86_64.whl
  • PyTorch 1.13 CPU package with Python 3.10 - If installing on a machine without CUDA
• aimet_onnx_gpu-1.32.0.cu117-cp310-cp310-manylinux_2_34_x86_64.whl
  • ONNX 1.14 GPU package with Python 3.10 - Recommended for use with ONNX models
• aimet_onnx_cpu-1.32.0.cpu-cp310-cp310-manylinux_2_34_x86_64.whl
  • ONNX 1.14 CPU package with Python 3.10 - If installing on a machine without CUDA
• aimet_tf_gpu-1.32.0.cu118-cp310-cp310-manylinux_2_34_x86_64.whl
  • TensorFlow 2.10 GPU package with Python 3.10 - Recommended for use with TensorFlow models
• aimet_tf_cpu-1.32.0.cpu-cp310-cp310-manylinux_2_34_x86_64.whl
  • TensorFlow 2.10 CPU package with Python 3.10 - If installing on a machine without CUDA