Fixed CUDA setup bugs, including #81.
This commit is contained in:
Tim Dettmers
parent
4844aef4ff
commit
8d87c0b852
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@ -149,3 +149,9 @@ Bug fixes:
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Bug fixes:
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- Fixed a bug in the CUDA Setup which led to an incomprehensible error if no GPU was detected.
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### 0.35.4
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Bug fixes:
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- Fixed a bug in the CUDA Setup failed with the cuda runtime was found, but not the cuda library.
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- Fixed a bug where not finding the cuda runtime led to an incomprehensible error.
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@ -116,7 +116,7 @@ try:
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CUDASetup.get_instance().generate_instructions()
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CUDASetup.get_instance().print_log_stack()
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raise RuntimeError('''
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CUDA Setup failed despite GPU being available. Inspect the CUDA SETUP outputs to fix your environment!
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CUDA Setup failed despite GPU being available. Inspect the CUDA SETUP outputs aboveto fix your environment!
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If you cannot find any issues and suspect a bug, please open an issue with detals about your environment:
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https://github.com/TimDettmers/bitsandbytes/issues''')
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lib.cadam32bit_g32
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@ -124,8 +124,6 @@ try:
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lib.get_cusparse.restype = ct.c_void_p
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COMPILED_WITH_CUDA = True
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except AttributeError:
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warn(
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"The installed version of bitsandbytes was compiled without GPU support. "
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"8-bit optimizers and GPU quantization are unavailable."
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)
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warn("The installed version of bitsandbytes was compiled without GPU support. "
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"8-bit optimizers and GPU quantization are unavailable.")
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COMPILED_WITH_CUDA = False
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@ -17,6 +17,7 @@ evaluation:
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"""
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import ctypes
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import torch
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from .paths import determine_cuda_runtime_lib_path
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from bitsandbytes.cextension import CUDASetup
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@ -29,8 +30,11 @@ def check_cuda_result(cuda, result_val):
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cuda.cuGetErrorString(result_val, ctypes.byref(error_str))
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CUDASetup.get_instance().add_log_entry(f"CUDA exception! Error code: {error_str.value.decode()}")
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# https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION
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def get_cuda_version(cuda, cudart_path):
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# https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART____VERSION.html#group__CUDART____VERSION
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if cuda is None: return None
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try:
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cudart = ctypes.CDLL(cudart_path)
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except OSError:
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@ -72,7 +76,6 @@ def get_compute_capabilities(cuda):
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# bits taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
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"""
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nGpus = ctypes.c_int()
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cc_major = ctypes.c_int()
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cc_minor = ctypes.c_int()
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@ -99,11 +102,11 @@ def get_compute_capability(cuda):
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capabilities are downwards compatible. If no GPUs are detected, it returns
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None.
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"""
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if cuda is None: return None
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# TODO: handle different compute capabilities; for now, take the max
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ccs = get_compute_capabilities(cuda)
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if ccs:
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# TODO: handle different compute capabilities; for now, take the max
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return ccs[-1]
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return None
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if ccs: return ccs[-1]
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def evaluate_cuda_setup():
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@ -113,28 +116,31 @@ def evaluate_cuda_setup():
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#print('Welcome to bitsandbytes. For bug reports, please submit your error trace to: https://github.com/TimDettmers/bitsandbytes/issues')
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#print('For effortless bug reporting copy-paste your error into this form: https://docs.google.com/forms/d/e/1FAIpQLScPB8emS3Thkp66nvqwmjTEgxp8Y9ufuWTzFyr9kJ5AoI47dQ/viewform?usp=sf_link')
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#print('='*80)
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#if not torch.cuda.is_available():
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#print('No GPU detected. Loading CPU library...')
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#return binary_name
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binary_name = "libbitsandbytes_cpu.so"
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if not torch.cuda.is_available(): return 'libsbitsandbytes_cpu.so', None, None, None, None
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cuda_setup = CUDASetup.get_instance()
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cudart_path = determine_cuda_runtime_lib_path()
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if cudart_path is None:
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cuda_setup.add_log_entry("WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!", is_warning=True)
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return binary_name
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cuda_setup.add_log_entry((f"CUDA SETUP: CUDA runtime path found: {cudart_path}"))
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cuda = get_cuda_lib_handle()
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cc = get_compute_capability(cuda)
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cuda_setup.add_log_entry(f"CUDA SETUP: Highest compute capability among GPUs detected: {cc}")
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cuda_version_string = get_cuda_version(cuda, cudart_path)
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failure = False
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if cudart_path is None:
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failure = True
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cuda_setup.add_log_entry("WARNING: No libcudart.so found! Install CUDA or the cudatoolkit package (anaconda)!", is_warning=True)
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else:
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cuda_setup.add_log_entry((f"CUDA SETUP: CUDA runtime path found: {cudart_path}"))
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if cc == '' or cc is None:
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cuda_setup.add_log_entry("WARNING: No GPU detected! Check your CUDA paths. Processing to load CPU-only library...", is_warning=True)
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return binary_name, cudart_path, cuda, cc, cuda_version_string
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failure = True
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cuda_setup.add_log_entry("WARNING: No GPU detected! Check your CUDA paths. Proceeding to load CPU-only library...", is_warning=True)
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else:
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cuda_setup.add_log_entry(f"CUDA SETUP: Highest compute capability among GPUs detected: {cc}")
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if cuda is None:
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failure = True
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else:
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cuda_setup.add_log_entry(f'CUDA SETUP: Detected CUDA version {cuda_version_string}')
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# 7.5 is the minimum CC vor cublaslt
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has_cublaslt = cc in ["7.5", "8.0", "8.6"]
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@ -145,16 +151,13 @@ def evaluate_cuda_setup():
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# we use ls -l instead of nvcc to determine the cuda version
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# since most installations will have the libcudart.so installed, but not the compiler
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cuda_setup.add_log_entry(f'CUDA SETUP: Detected CUDA version {cuda_version_string}')
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def get_binary_name():
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if failure:
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binary_name = "libbitsandbytes_cpu.so"
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elif has_cublaslt:
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binary_name = f"libbitsandbytes_cuda{cuda_version_string}.so"
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else:
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"if not has_cublaslt (CC < 7.5), then we have to choose _nocublaslt.so"
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bin_base_name = "libbitsandbytes_cuda"
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if has_cublaslt:
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return f"{bin_base_name}{cuda_version_string}.so"
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else:
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return f"{bin_base_name}{cuda_version_string}_nocublaslt.so"
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binary_name = get_binary_name()
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binary_name = f"libbitsandbytes_cuda{cuda_version_string}_nocublaslt.so"
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return binary_name, cudart_path, cuda, cc, cuda_version_string
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