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# python3.7
# Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
"""Utility functions to setup customized operators.
Please refer to https://github.com/NVlabs/stylegan2-ada-pytorch
"""
# pylint: disable=line-too-long
# pylint: disable=missing-function-docstring
# pylint: disable=useless-suppression
# pylint: disable=inconsistent-quotes
import os
import glob
import importlib
import hashlib
import shutil
from pathlib import Path
import torch
from torch.utils.file_baton import FileBaton
import torch.utils.cpp_extension
#----------------------------------------------------------------------------
# Global options.
verbosity = 'none' # Verbosity level: 'none', 'brief', 'full'
#----------------------------------------------------------------------------
# Internal helper funcs.
def _find_compiler_bindir():
patterns = [
'C:/Program Files (x86)/Microsoft Visual Studio/*/Professional/VC/Tools/MSVC/*/bin/Hostx64/x64',
'C:/Program Files (x86)/Microsoft Visual Studio/*/BuildTools/VC/Tools/MSVC/*/bin/Hostx64/x64',
'C:/Program Files (x86)/Microsoft Visual Studio/*/Community/VC/Tools/MSVC/*/bin/Hostx64/x64',
'C:/Program Files (x86)/Microsoft Visual Studio */vc/bin',
]
for pattern in patterns:
matches = sorted(glob.glob(pattern))
if len(matches):
return matches[-1]
return None
def _find_compiler_bindir_posix():
patterns = [
'/usr/local/cuda/bin'
]
for pattern in patterns:
matches = sorted(glob.glob(pattern))
if len(matches):
return matches[-1]
return None
#----------------------------------------------------------------------------
# Main entry point for compiling and loading C++/CUDA plugins.
_cached_plugins = dict()
def get_plugin(module_name, sources, **build_kwargs):
assert verbosity in ['none', 'brief', 'full']
# Already cached?
if module_name in _cached_plugins:
return _cached_plugins[module_name]
# Print status.
if verbosity == 'full':
print(f'Setting up PyTorch plugin "{module_name}"...')
elif verbosity == 'brief':
print(f'Setting up PyTorch plugin "{module_name}"... ', end='', flush=True)
try: # pylint: disable=too-many-nested-blocks
# Make sure we can find the necessary compiler binaries.
if os.name == 'nt' and os.system("where cl.exe >nul 2>nul") != 0:
compiler_bindir = _find_compiler_bindir()
if compiler_bindir is None:
raise RuntimeError(f'Could not find MSVC/GCC/CLANG installation on this computer. Check _find_compiler_bindir() in "{__file__}".')
os.environ['PATH'] += ';' + compiler_bindir
elif os.name == 'posix':
compiler_bindir = _find_compiler_bindir_posix()
if compiler_bindir is None:
raise RuntimeError(f'Could not find NVCC installation on this computer. Check _find_compiler_bindir_posix() in "{__file__}".')
os.environ['PATH'] += ';' + compiler_bindir
# Compile and load.
verbose_build = (verbosity == 'full')
# Incremental build md5sum trickery. Copies all the input source files
# into a cached build directory under a combined md5 digest of the input
# source files. Copying is done only if the combined digest has changed.
# This keeps input file timestamps and filenames the same as in previous
# extension builds, allowing for fast incremental rebuilds.
#
# This optimization is done only in case all the source files reside in
# a single directory (just for simplicity) and if the TORCH_EXTENSIONS_DIR
# environment variable is set (we take this as a signal that the user
# actually cares about this.)
source_dirs_set = set(os.path.dirname(source) for source in sources)
if len(source_dirs_set) == 1 and ('TORCH_EXTENSIONS_DIR' in os.environ):
all_source_files = sorted(list(x for x in Path(list(source_dirs_set)[0]).iterdir() if x.is_file()))
# Compute a combined hash digest for all source files in the same
# custom op directory (usually .cu, .cpp, .py and .h files).
hash_md5 = hashlib.md5()
for src in all_source_files:
with open(src, 'rb') as f:
hash_md5.update(f.read())
build_dir = torch.utils.cpp_extension._get_build_directory(module_name, verbose=verbose_build) # pylint: disable=protected-access
digest_build_dir = os.path.join(build_dir, hash_md5.hexdigest())
if not os.path.isdir(digest_build_dir):
os.makedirs(digest_build_dir, exist_ok=True)
baton = FileBaton(os.path.join(digest_build_dir, 'lock'))
if baton.try_acquire():
try:
for src in all_source_files:
shutil.copyfile(src, os.path.join(digest_build_dir, os.path.basename(src)))
finally:
baton.release()
else:
# Someone else is copying source files under the digest dir,
# wait until done and continue.
baton.wait()
digest_sources = [os.path.join(digest_build_dir, os.path.basename(x)) for x in sources]
torch.utils.cpp_extension.load(name=module_name, build_directory=build_dir,
verbose=verbose_build, sources=digest_sources, **build_kwargs)
else:
torch.utils.cpp_extension.load(name=module_name, verbose=verbose_build, sources=sources, **build_kwargs)
module = importlib.import_module(module_name)
except:
if verbosity == 'brief':
print('Failed!')
raise
# Print status and add to cache.
if verbosity == 'full':
print(f'Done setting up PyTorch plugin "{module_name}".')
elif verbosity == 'brief':
print('Done.')
_cached_plugins[module_name] = module
return module
#----------------------------------------------------------------------------
# pylint: enable=line-too-long
# pylint: enable=missing-function-docstring
# pylint: enable=useless-suppression
# pylint: enable=inconsistent-quotes
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