93 lines
3.1 KiB
Python
93 lines
3.1 KiB
Python
import os
|
|
import sys
|
|
|
|
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, 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:
|
|
raise RuntimeError(
|
|
"Detected that PyTorch and torchvision were compiled with different CUDA major 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)
|
|
torch.ops.load_library(lib_path)
|
|
|
|
|
|
_check_cuda_version()
|