Merge pull request #1 from TimDettmers/main

Update main branch

1 files changed, 6 insertions, 5 deletions

diff --git a/bitsandbytes/cuda_setup/main.py b/bitsandbytes/cuda_setup/main.py
index 975b772..78a2844 100644
--- a/bitsandbytes/cuda_setup/main.py
+++ b/bitsandbytes/cuda_setup/main.py
@@ -17,9 +17,7 @@ evaluation:
 """
 
 import ctypes
-from pathlib import Path
 
-from ..utils import execute_and_return
 from .paths import determine_cuda_runtime_lib_path
 
 
@@ -28,7 +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
@@ -57,7 +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))
 
@@ -80,7 +78,6 @@ def get_compute_capabilities(cuda):
     cc_major = ctypes.c_int()
     cc_minor = ctypes.c_int()
 
-    result = ctypes.c_int()
     device = ctypes.c_int()
 
     check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus)))
@@ -119,6 +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(