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INSTALLATION_SUPPORT.md

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Installation Support

difflogic is a Python 3.6+ and PyTorch 1.9.0+ based library for training and inference with logic gate networks. The library can be installed with:

pip install difflogic

⚠️ Note that difflogic requires CUDA, the CUDA Toolkit (for compilation), and torch>=1.9.0 (matching the CUDA version).

It is very important that the installed version of PyTorch was compiled with a CUDA version that is compatible with the CUDA version of the locally installed CUDA Toolkit.

You can check your CUDA version by running nvidia-smi.

You can install PyTorch and torchvision of a specific version, e.g., via

pip install torch==1.9.0+cu111 torchvision==0.10.0+cu111  -f https://download.pytorch.org/whl/torch_stable.html  # CUDA version 11.1
pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA version 11.3
pip install torch==1.13.0+cu117 torchvision==0.14.0+cu117 -f https://download.pytorch.org/whl/torch_stable.html  # CUDA version 11.7

If you get the following error message:

Failed to build difflogic
 
...

RuntimeError:
    The detected CUDA version (11.2) mismatches the version that was used to compile
    PyTorch (11.7). Please make sure to use the same CUDA versions.

You need to make sure that the versions match, typically by installing a different PyTorch version. Note that there are some versions of PyTorch that have been compiled with CUDA versions different from the advertised versions, so in case it should match but doesn't, a quick fix can be to try some other (e.g., older) PyTorch versions.

difflogic has been tested with PyTorch versions between 1.9 and 1.13.

For the experiments, please make sure all dependencies in experiments/requirements.txt are installed in the Python environment.