diff options
Diffstat (limited to 'bitsandbytes')
| -rw-r--r-- | bitsandbytes/cextension.py | 8 | ||||
| -rw-r--r-- | bitsandbytes/cuda_setup/main.py | 59 |
2 files changed, 34 insertions, 33 deletions
diff --git a/bitsandbytes/cextension.py b/bitsandbytes/cextension.py index 4f791e2..8125202 100644 --- a/bitsandbytes/cextension.py +++ b/bitsandbytes/cextension.py @@ -116,7 +116,7 @@ try: CUDASetup.get_instance().generate_instructions() CUDASetup.get_instance().print_log_stack() raise RuntimeError(''' - CUDA Setup failed despite GPU being available. Inspect the CUDA SETUP outputs to fix your environment! + CUDA Setup failed despite GPU being available. Inspect the CUDA SETUP outputs aboveto fix your environment! If you cannot find any issues and suspect a bug, please open an issue with detals about your environment: https://github.com/TimDettmers/bitsandbytes/issues''') lib.cadam32bit_g32 @@ -124,8 +124,6 @@ try: lib.get_cusparse.restype = ct.c_void_p COMPILED_WITH_CUDA = True except AttributeError: - warn( - "The installed version of bitsandbytes was compiled without GPU support. " - "8-bit optimizers and GPU quantization are unavailable." - ) + warn("The installed version of bitsandbytes was compiled without GPU support. " + "8-bit optimizers and GPU quantization are unavailable.") COMPILED_WITH_CUDA = False diff --git a/bitsandbytes/cuda_setup/main.py b/bitsandbytes/cuda_setup/main.py index 0fc813b..6a6bc74 100644 --- a/bitsandbytes/cuda_setup/main.py +++ b/bitsandbytes/cuda_setup/main.py @@ -17,6 +17,7 @@ evaluation: """ import ctypes +import torch from .paths import determine_cuda_runtime_lib_path from bitsandbytes.cextension import CUDASetup @@ -29,8 +30,11 @@ def check_cuda_result(cuda, result_val): cuda.cuGetErrorString(result_val, ctypes.byref(error_str)) CUDASetup.get_instance().add_log_entry(f"CUDA exception! Error code: {error_str.value.decode()}") + +# https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION def get_cuda_version(cuda, cudart_path): - # https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION + if cuda is None: return None + try: cudart = ctypes.CDLL(cudart_path) except OSError: @@ -72,7 +76,6 @@ def get_compute_capabilities(cuda): # bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549 """ - nGpus = ctypes.c_int() cc_major = ctypes.c_int() cc_minor = ctypes.c_int() @@ -99,11 +102,11 @@ def get_compute_capability(cuda): capabilities are downwards compatible. If no GPUs are detected, it returns None. """ + if cuda is None: return None + + # TODO: handle different compute capabilities; for now, take the max ccs = get_compute_capabilities(cuda) - if ccs: - # TODO: handle different compute capabilities; for now, take the max - return ccs[-1] - return None + if ccs: return ccs[-1] def evaluate_cuda_setup(): @@ -113,28 +116,31 @@ def evaluate_cuda_setup(): #print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues') #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) - #if not torch.cuda.is_available(): - #print('No GPU detected. Loading CPU library...') - #return binary_name - - binary_name = "libbitsandbytes_cpu.so" + if not torch.cuda.is_available(): return 'libsbitsandbytes_cpu.so', None, None, None, None cuda_setup = CUDASetup.get_instance() cudart_path = determine_cuda_runtime_lib_path() - if cudart_path is None: - cuda_setup.add_log_entry("WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!", is_warning=True) - return binary_name - - cuda_setup.add_log_entry((f"CUDA SETUP: CUDA runtime path found: {cudart_path}")) cuda = get_cuda_lib_handle() cc = get_compute_capability(cuda) - cuda_setup.add_log_entry(f"CUDA SETUP: Highest compute capability among GPUs detected: {cc}") cuda_version_string = get_cuda_version(cuda, cudart_path) + failure = False + if cudart_path is None: + failure = True + cuda_setup.add_log_entry("WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!", is_warning=True) + else: + cuda_setup.add_log_entry((f"CUDA SETUP: CUDA runtime path found: {cudart_path}")) if cc == '' or cc is None: - cuda_setup.add_log_entry("WARNING: No GPU detected! Check your CUDA paths. Processing to load CPU-only library...", is_warning=True) - return binary_name, cudart_path, cuda, cc, cuda_version_string + failure = True + cuda_setup.add_log_entry("WARNING: No GPU detected! Check your CUDA paths. Proceeding to load CPU-only library...", is_warning=True) + else: + cuda_setup.add_log_entry(f"CUDA SETUP: Highest compute capability among GPUs detected: {cc}") + + if cuda is None: + failure = True + else: + cuda_setup.add_log_entry(f'CUDA SETUP: Detected CUDA version {cuda_version_string}') # 7.5 is the minimum CC vor cublaslt has_cublaslt = cc in ["7.5", "8.0", "8.6"] @@ -145,16 +151,13 @@ def evaluate_cuda_setup(): # we use ls -l instead of nvcc to determine the cuda version # since most installations will have the libcudart.so installed, but not the compiler - cuda_setup.add_log_entry(f'CUDA SETUP: Detected CUDA version {cuda_version_string}') - def get_binary_name(): + if failure: + binary_name = "libbitsandbytes_cpu.so" + elif has_cublaslt: + binary_name = f"libbitsandbytes_cuda{cuda_version_string}.so" + else: "if not has_cublaslt (CC < 7.5), then we have to choose _nocublaslt.so" - bin_base_name = "libbitsandbytes_cuda" - if has_cublaslt: - return f"{bin_base_name}{cuda_version_string}.so" - else: - return f"{bin_base_name}{cuda_version_string}_nocublaslt.so" - - binary_name = get_binary_name() + binary_name = f"libbitsandbytes_cuda{cuda_version_string}_nocublaslt.so" return binary_name, cudart_path, cuda, cc, cuda_version_string |