o oiS @s ddlZddlZddlZddlmZddlZddlZddlm Z m Z ddl m Z m Z eeZde defddZGd d d ZGd d d eZdefd dZzeZWdSeyZz$dZejdeddejryedWYdZ[dSWYdZ[dSdZ[ww)N)Path)DYNAMIC_LIBRARY_SUFFIX PACKAGE_DIR) CUDASpecsget_cuda_specs cuda_specsreturncCsXd|jt}tjd}|r(tjdd||dd}td|d|d t |S) z Get the disk path to the CUDA BNB native library specified by the given CUDA specs, taking into account the `BNB_CUDA_VERSION` override environment variable. The library is not guaranteed to exist at the returned path. libbitsandbytes_cudaBNB_CUDA_VERSIONzcuda\d+cuda)countzWARNING: BNB_CUDA_VERSION=z( environment variable detected; loading a. This can be used to load a bitsandbytes version that is different from the PyTorch CUDA version. If this was unintended set the BNB_CUDA_VERSION variable to an empty string: export BNB_CUDA_VERSION= If you use the manual override make sure the right libcudart.so is in your LD_LIBRARY_PATH For example by adding the following to your .bashrc: export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:s  rEz,Could not load bitsandbytes native library: T)exc_infoa CUDA Setup failed despite CUDA being available. Please run the following command to get more information: python -m bitsandbytes Inspect the output of the command and see if you can locate CUDA libraries. You might need to add them to your LD_LIBRARY_PATH. If you suspect a bug, please take the information from python -m bitsandbytes and open an issue at: https://github.com/bitsandbytes-foundation/bitsandbytes/issues )ctypesr-loggingrpathlibrrtorchbitsandbytes.constsrrbitsandbytes.cuda_specsrr getLoggerr*rrrr1rEr Exceptioneerrorr is_availablerrrrrs2