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author | Tim Dettmers <TimDettmers@users.noreply.github.com> | 2022-09-05 16:29:25 -0700 |
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committer | GitHub <noreply@github.com> | 2022-09-05 16:29:25 -0700 |
commit | aca55881b9815a462142f42f3ff0dc917830d85c (patch) | |
tree | 75477acfbce2da2a753ee21d4cf0da64f3f50ea5 /bitsandbytes/cuda_setup | |
parent | 92a3363096e10ad6a5c4e944af898bd1186d806a (diff) | |
parent | eab4d8232d558f2e6bd7f7cc3d00e2e6e94f4e80 (diff) |
Merge branch 'main' into remove_unused_code
Diffstat (limited to 'bitsandbytes/cuda_setup')
-rw-r--r-- | bitsandbytes/cuda_setup/main.py | 8 |
1 files changed, 6 insertions, 2 deletions
diff --git a/bitsandbytes/cuda_setup/main.py b/bitsandbytes/cuda_setup/main.py index ba7e04c..78a2844 100644 --- a/bitsandbytes/cuda_setup/main.py +++ b/bitsandbytes/cuda_setup/main.py @@ -26,7 +26,7 @@ def check_cuda_result(cuda, result_val): if result_val != 0: error_str = ctypes.c_char_p() cuda.cuGetErrorString(result_val, ctypes.byref(error_str)) - raise Exception(f"CUDA exception! Error code: {error_str.value.decode()}") + print(f"CUDA exception! Error code: {error_str.value.decode()}") def get_cuda_version(cuda, cudart_path): # https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION @@ -55,7 +55,7 @@ def get_cuda_lib_handle(): cuda = ctypes.CDLL("libcuda.so") except OSError: # TODO: shouldn't we error or at least warn here? - raise Exception('CUDA SETUP: ERROR! libcuda.so not found! Do you have a CUDA driver installed? If you are on a cluster, make sure you are on a CUDA machine!') + print('CUDA SETUP: WARNING! libcuda.so not found! Do you have a CUDA driver installed? If you are on a cluster, make sure you are on a CUDA machine!') return None check_cuda_result(cuda, cuda.cuInit(0)) @@ -116,6 +116,10 @@ def evaluate_cuda_setup(): print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link') print('='*80) binary_name = "libbitsandbytes_cpu.so" + #if not torch.cuda.is_available(): + #print('No GPU detected. Loading CPU library...') + #return binary_name + cudart_path = determine_cuda_runtime_lib_path() if cudart_path is None: print( |