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AutoAWQ Kernels implements the AWQ kernels.

Project description

AutoAWQ Kernels

AutoAWQ Kernels is a new package that is split up from the main repository in order to avoid compilation times.

Requirements

  • Windows: Must use WSL2.

  • NVIDIA:

    • GPU: Must be compute capability 7.5 or higher.
    • CUDA Toolkit: Must be 11.8 or higher.
  • AMD:

Install

Install from PyPi

The package is available on PyPi with CUDA 12.4.1 wheels:

pip install autoawq-kernels

Build from source

To build the kernels from source, you first need to setup an environment containing the necessary dependencies.

Build Requirements

  • Python>=3.8.0
  • Numpy
  • Wheel
  • PyTorch
  • ROCm: You need to install the following packages rocsparse-dev hipsparse-dev rocthrust-dev rocblas-dev hipblas-dev.

Building process

pip install git+https://github.com/casper-hansen/AutoAWQ_kernels.git

Notes on environment variables:

  • TORCH_VERSION: By default, we build using the current version of torch by torch.__version__. You can override it with TORCH_VERSION.
    • CUDA_VERSION or ROCM_VERSION can also be used to build for a specific version of CUDA or ROCm.
  • CC and CXX: You can specify which build system to use for the C code, e.g. CC=g++-13 CXX=g++-13 pip install -e .
  • COMPUTE_CAPABILITIES: You can specify specific compute capabilities to compile for: COMPUTE_CAPABILITIES="75,80,86,87,89,90" pip install -e .

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