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import ctypes
import os
import sys
from warnings import warn
import torch
from ._internally_replaced_utils import _get_extension_path
_HAS_OPS = False
def _has_ops():
return False
try:
# On Windows Python-3.8.x has `os.add_dll_directory` call,
# which is called to configure dll search path.
# To find cuda related dlls we need to make sure the
# conda environment/bin path is configured Please take a look:
# https://stackoverflow.com/questions/59330863/cant-import-dll-module-in-python
# Please note: if some path can't be added using add_dll_directory we simply ignore this path
if os.name == "nt" and sys.version_info >= (3, 8) and sys.version_info < (3, 9):
env_path = os.environ["PATH"]
path_arr = env_path.split(";")
for path in path_arr:
if os.path.exists(path):
try:
os.add_dll_directory(path) # type: ignore[attr-defined]
except Exception:
pass
lib_path = _get_extension_path("_C")
torch.ops.load_library(lib_path)
_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
from torch.version import cuda as torch_version_cuda
_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.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. "
f"PyTorch has CUDA Version={t_major}.{t_minor} and torchvision has "
f"CUDA Version={tv_major}.{tv_minor}. "
"Please reinstall the torchvision that matches your PyTorch install."
)
return _version
def _load_library(lib_name):
lib_path = _get_extension_path(lib_name)
# On Windows Python-3.8+ has `os.add_dll_directory` call,
# which is called from _get_extension_path to configure dll search path
# Condition below adds a workaround for older versions by
# explicitly calling `LoadLibraryExW` with the following flags:
# - LOAD_LIBRARY_SEARCH_DEFAULT_DIRS (0x1000)
# - LOAD_LIBRARY_SEARCH_DLL_LOAD_DIR (0x100)
if os.name == "nt" and sys.version_info < (3, 8):
_kernel32 = ctypes.WinDLL("kernel32.dll", use_last_error=True)
if hasattr(_kernel32, "LoadLibraryExW"):
_kernel32.LoadLibraryExW(lib_path, None, 0x00001100)
else:
warn("LoadLibraryExW is missing in kernel32.dll")
torch.ops.load_library(lib_path)
_check_cuda_version()
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