154 lines
4.8 KiB
Python
154 lines
4.8 KiB
Python
"""
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build is dependent on
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- compute capability
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- dependent on GPU family
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- CUDA version
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- Software:
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- CPU-only: only CPU quantization functions (no optimizer, no matrix multipl)
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- CuBLAS-LT: full-build 8-bit optimizer
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- no CuBLAS-LT: no 8-bit matrix multiplication (`nomatmul`)
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alle Binaries packagen
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evaluation:
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- if paths faulty, return meaningful error
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- else:
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- determine CUDA version
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- determine capabilities
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- based on that set the default path
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"""
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from os import environ as env
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from pathlib import Path
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from typing import Set, Union
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from .utils import warn_of_missing_prerequisite, print_err
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import ctypes
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import shlex
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import subprocess
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def execute_and_return(strCMD):
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proc = subprocess.Popen(shlex.split(strCMD), stdout=subprocess.PIPE, stderr=subprocess.PIPE)
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out, err = proc.communicate()
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out, err = out.decode("UTF-8").strip(), err.decode("UTF-8").strip()
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return out, err
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def check_cuda_result(cuda, result_val):
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if result_val != 0:
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cuda.cuGetErrorString(result_val, ctypes.byref(error_str))
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print(f"Count not initialize CUDA - failure!")
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raise Exception('CUDA excepion!')
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return result_val
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# taken from https://gist.github.com/f0k/63a664160d016a491b2cbea15913d549
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def get_compute_capability():
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libnames = ('libcuda.so', 'libcuda.dylib', 'cuda.dll')
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for libname in libnames:
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try:
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cuda = ctypes.CDLL(libname)
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except OSError:
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continue
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else:
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break
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else:
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raise OSError("could not load any of: " + ' '.join(libnames))
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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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result = ctypes.c_int()
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device = ctypes.c_int()
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context = ctypes.c_void_p()
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error_str = ctypes.c_char_p()
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result = check_cuda_result(cuda, cuda.cuInit(0))
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result = check_cuda_result(cuda, cuda.cuDeviceGetCount(ctypes.byref(nGpus)))
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ccs = []
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for i in range(nGpus.value):
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result = check_cuda_result(cuda, cuda.cuDeviceGet(ctypes.byref(device), i))
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result = check_cuda_result(cuda, cuda.cuDeviceComputeCapability(ctypes.byref(cc_major), ctypes.byref(cc_minor), device))
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ccs.append(f'{cc_major.value}.{cc_minor.value}')
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#TODO: handle different compute capabilities; for now, take the max
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ccs.sort()
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return ccs[-1]
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CUDA_RUNTIME_LIB: str = "libcudart.so"
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def tokenize_paths(paths: str) -> Set[Path]:
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return {
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Path(ld_path) for ld_path in paths.split(':')
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if ld_path
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}
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def get_cuda_runtime_lib_path(
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# TODO: replace this with logic for all paths in env vars
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LD_LIBRARY_PATH: Union[str, None] = env.get("LD_LIBRARY_PATH")
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) -> Union[Path, None]:
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""" # TODO: add doc-string
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"""
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if not LD_LIBRARY_PATH:
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warn_of_missing_prerequisite(
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'LD_LIBRARY_PATH is completely missing from environment!'
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)
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return None
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ld_library_paths: Set[Path] = tokenize_paths(LD_LIBRARY_PATH)
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non_existent_directories: Set[Path] = {
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path for path in ld_library_paths
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if not path.exists()
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}
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if non_existent_directories:
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print_err(
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"WARNING: The following directories listed your path were found to "
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f"be non-existent: {non_existent_directories}"
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)
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cuda_runtime_libs: Set[Path] = {
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path / CUDA_RUNTIME_LIB for path in ld_library_paths
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if (path / CUDA_RUNTIME_LIB).is_file()
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} - non_existent_directories
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if len(cuda_runtime_libs) > 1:
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err_msg = f"Found duplicate {CUDA_RUNTIME_LIB} files: {cuda_runtime_libs}.."
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raise FileNotFoundError(err_msg)
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elif len(cuda_runtime_libs) < 1:
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err_msg = f"Did not find {CUDA_RUNTIME_LIB} files: {cuda_runtime_libs}.."
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raise FileNotFoundError(err_msg)
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single_cuda_runtime_lib_dir = next(iter(cuda_runtime_libs))
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return single_cuda_runtime_lib_dir
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def evaluate_cuda_setup():
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cuda_path = get_cuda_runtime_lib_path()
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cc = get_compute_capability()
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binary_name = 'libbitsandbytes_cpu.so'
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has_gpu = cc != ''
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if not has_gpu:
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print('WARNING: No GPU detected! Check our CUDA paths. Processding to load CPU-only library...')
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return binary_name
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has_cublaslt = cc in ['7.5', '8.0', '8.6']
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# TODO:
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# (1) Model missing cases (no CUDA installed by CUDA driver (nvidia-smi accessible)
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# (2) Multiple CUDA versions installed
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cuda_home = str(Path(cuda_path).parent.parent)
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ls_output, err = execute_and_return(f'{cuda_home}/bin/nvcc --version')
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cuda_version = ls_output.split('\n')[3].split(',')[-1].strip().lower().replace('v', '')
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major, minor, revision = cuda_version.split('.')
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cuda_version_string = f'{major}{minor}'
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binary_name = f'libbitsandbytes_cuda{cuda_version_string}_{("cublaslt" if has_cublaslt else "")}.so'
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return binary_name
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