Projekt_AI-Automatyczny_saper/venv/Lib/site-packages/torchvision/extension.py
2021-06-01 17:38:31 +02:00

102 lines
3.4 KiB
Python

_HAS_OPS = False
def _has_ops():
return False
def _register_extensions():
import os
import importlib
import torch
# load the custom_op_library and register the custom ops
lib_dir = os.path.dirname(__file__)
if os.name == 'nt':
# Register the main torchvision library location on the default DLL path
import ctypes
import sys
kernel32 = ctypes.WinDLL('kernel32.dll', use_last_error=True)
with_load_library_flags = hasattr(kernel32, 'AddDllDirectory')
prev_error_mode = kernel32.SetErrorMode(0x0001)
if with_load_library_flags:
kernel32.AddDllDirectory.restype = ctypes.c_void_p
if sys.version_info >= (3, 8):
os.add_dll_directory(lib_dir)
elif with_load_library_flags:
res = kernel32.AddDllDirectory(lib_dir)
if res is None:
err = ctypes.WinError(ctypes.get_last_error())
err.strerror += f' Error adding "{lib_dir}" to the DLL directories.'
raise err
kernel32.SetErrorMode(prev_error_mode)
loader_details = (
importlib.machinery.ExtensionFileLoader,
importlib.machinery.EXTENSION_SUFFIXES
)
extfinder = importlib.machinery.FileFinder(lib_dir, loader_details)
ext_specs = extfinder.find_spec("_C")
if ext_specs is None:
raise ImportError
torch.ops.load_library(ext_specs.origin)
try:
_register_extensions()
_HAS_OPS = True
def _has_ops(): # noqa: F811
return True
except (ImportError, OSError):
pass
def _assert_has_ops():
if not _has_ops():
raise RuntimeError(
"Couldn't load custom C++ ops. This can happen if your PyTorch and "
"torchvision versions are incompatible, or if you had errors while compiling "
"torchvision from source. For further information on the compatible versions, check "
"https://github.com/pytorch/vision#installation for the compatibility matrix. "
"Please check your PyTorch version with torch.__version__ and your torchvision "
"version with torchvision.__version__ and verify if they are compatible, and if not "
"please reinstall torchvision so that it matches your PyTorch install."
)
def _check_cuda_version():
"""
Make sure that CUDA versions match between the pytorch install and torchvision install
"""
if not _HAS_OPS:
return -1
import torch
_version = torch.ops.torchvision._cuda_version()
if _version != -1 and torch.version.cuda is not None:
tv_version = str(_version)
if int(tv_version) < 10000:
tv_major = int(tv_version[0])
tv_minor = int(tv_version[2])
else:
tv_major = int(tv_version[0:2])
tv_minor = int(tv_version[3])
t_version = torch.version.cuda
t_version = t_version.split('.')
t_major = int(t_version[0])
t_minor = int(t_version[1])
if t_major != tv_major or t_minor != tv_minor:
raise RuntimeError("Detected that PyTorch and torchvision were compiled with different CUDA versions. "
"PyTorch has CUDA Version={}.{} and torchvision has CUDA Version={}.{}. "
"Please reinstall the torchvision that matches your PyTorch install."
.format(t_major, t_minor, tv_major, tv_minor))
return _version
_check_cuda_version()