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

• Windows: Must use WSL2.

• NVIDIA:

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

• AMD:

  • ROCm: Must be 5.6 or higher. Build from source

The package is available on PyPi with CUDA 12.4.1 wheels:

pip install autoawq-kernels

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

• 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.

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 .