mirror of
https://github.com/pytorch/pytorch.git
synced 2025-10-20 21:14:14 +08:00
8fbefa06f6
Summary: Move the resolution of conflict between `USE_CUDA` and `USE_ROCM` to CMake as to effectuate: - `USE_CUDA=ON` and CUDA is found, `USE_ROCM=ON` and ROCM is found --> fatal error - Either `USE_CUDA=ON` and CUDA is found or `USE_ROCM=ON` and ROCM is found --> The respective GPU feature is ON - Otherwise no GPU support Pull Request resolved: https://github.com/pytorch/pytorch/pull/26910 Differential Revision: D17738652 Pulled By: ezyang fbshipit-source-id: 8e07cc7e922e0abda24a6518119c28952276064e
83 lines
2.9 KiB
Python
83 lines
2.9 KiB
Python
import os
|
|
import glob
|
|
import re
|
|
import ctypes.util
|
|
from subprocess import Popen, PIPE
|
|
|
|
from . import which
|
|
from .env import IS_WINDOWS, IS_LINUX, IS_DARWIN, check_negative_env_flag
|
|
|
|
LINUX_HOME = '/usr/local/cuda'
|
|
WINDOWS_HOME = glob.glob('C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*')
|
|
|
|
|
|
def find_nvcc():
|
|
nvcc = which('nvcc')
|
|
if nvcc is not None:
|
|
return os.path.dirname(nvcc)
|
|
else:
|
|
return None
|
|
|
|
|
|
def find_cuda_version(cuda_home):
|
|
if cuda_home is None:
|
|
return None
|
|
if IS_WINDOWS:
|
|
candidate_names = [os.path.basename(cuda_home)]
|
|
else:
|
|
# get CUDA lib folder
|
|
cuda_lib_dirs = ['lib64', 'lib']
|
|
for lib_dir in cuda_lib_dirs:
|
|
cuda_lib_path = os.path.join(cuda_home, lib_dir)
|
|
if os.path.exists(cuda_lib_path):
|
|
break
|
|
# get a list of candidates for the version number
|
|
# which are files containing cudart
|
|
candidate_names = list(glob.glob(os.path.join(cuda_lib_path, '*cudart*')))
|
|
candidate_names = [os.path.basename(c) for c in candidate_names]
|
|
# if we didn't find any cudart, ask nvcc
|
|
if len(candidate_names) == 0:
|
|
proc = Popen(['nvcc', '--version'], stdout=PIPE, stderr=PIPE)
|
|
out, err = proc.communicate()
|
|
candidate_names = [out.decode().rsplit('V')[-1]]
|
|
|
|
# suppose version is MAJOR.MINOR.PATCH, all numbers
|
|
version_regex = re.compile(r'[0-9]+\.[0-9]+\.[0-9]+')
|
|
candidates = [c.group() for c in map(version_regex.search, candidate_names) if c]
|
|
if len(candidates) > 0:
|
|
# normally only one will be retrieved, take the first result
|
|
return candidates[0]
|
|
# if no candidates were found, try MAJOR.MINOR
|
|
version_regex = re.compile(r'[0-9]+\.[0-9]+')
|
|
candidates = [c.group() for c in map(version_regex.search, candidate_names) if c]
|
|
if len(candidates) > 0:
|
|
return candidates[0]
|
|
|
|
if check_negative_env_flag('USE_CUDA'):
|
|
USE_CUDA = False
|
|
CUDA_HOME = None
|
|
CUDA_VERSION = None
|
|
else:
|
|
if IS_LINUX or IS_DARWIN:
|
|
CUDA_HOME = os.getenv('CUDA_HOME', LINUX_HOME)
|
|
else:
|
|
CUDA_HOME = os.getenv('CUDA_PATH', '').replace('\\', '/')
|
|
if CUDA_HOME == '' and len(WINDOWS_HOME) > 0:
|
|
CUDA_HOME = WINDOWS_HOME[0].replace('\\', '/')
|
|
if not os.path.exists(CUDA_HOME):
|
|
# We use nvcc path on Linux and cudart path on macOS
|
|
if IS_LINUX or IS_WINDOWS:
|
|
cuda_path = find_nvcc()
|
|
else:
|
|
cudart_path = ctypes.util.find_library('cudart')
|
|
if cudart_path is not None:
|
|
cuda_path = os.path.dirname(cudart_path)
|
|
else:
|
|
cuda_path = None
|
|
if cuda_path is not None:
|
|
CUDA_HOME = os.path.dirname(cuda_path)
|
|
else:
|
|
CUDA_HOME = None
|
|
CUDA_VERSION = find_cuda_version(CUDA_HOME)
|
|
USE_CUDA = CUDA_HOME is not None
|