python - “utf-8”编解码器无法解码位置 54 中的字节 0xff：无效的起始字节
问题描述
我知道这类问题有很多答案，但由于我对编程的了解有限，我无法将它们应用到我的代码中。
from __future__ import absolute_import, division, print_function, unicode_literals
import copy
import glob
import imp
import os
import re
import setuptools
import subprocess
import sys
import sysconfig
import tempfile
import warnings
import torch
from .file_baton import FileBaton
from ._cpp_extension_versioner import ExtensionVersioner
from setuptools.command.build_ext import build_ext
IS_WINDOWS = sys.platform == 'win32'
def _find_cuda_home():
'''Finds the CUDA install path.'''
# Guess #1
cuda_home = os.environ.get('CUDA_HOME') or os.environ.get('CUDA_PATH')
if cuda_home is None:
# Guess #2
if IS_WINDOWS:
cuda_homes = glob.glob(
'C:/Program Files/NVIDIA GPU Computing Toolkit/CUDA/v*.*')
if len(cuda_homes) == 0:
cuda_home = ''
else:
cuda_home = cuda_homes[0]
else:
cuda_home = '/usr/local/cuda'
if not os.path.exists(cuda_home):
# Guess #3
try:
which = 'where' if IS_WINDOWS else 'which'
nvcc = subprocess.check_output(
[which, 'nvcc']).decode().rstrip('\r\n')
cuda_home = os.path.dirname(os.path.dirname(nvcc))
except Exception:
cuda_home = None
if cuda_home and not torch.cuda.is_available():
print("No CUDA runtime is found, using CUDA_HOME='{}'".format(cuda_home))
return cuda_home
MINIMUM_GCC_VERSION = (4, 9, 0)
MINIMUM_MSVC_VERSION = (19, 0, 24215)
ABI_INCOMPATIBILITY_WARNING =
WRONG_COMPILER_WARNING =
CUDA_HOME = _find_cuda_home()
CUDNN_HOME = os.environ.get('CUDNN_HOME') or os.environ.get('CUDNN_PATH')
BUILT_FROM_SOURCE_VERSION_PATTERN = re.compile(r'\d+\.\d+\.\d+\w+\+\w+')
COMMON_NVCC_FLAGS = [
'-D__CUDA_NO_HALF_OPERATORS__',
'-D__CUDA_NO_HALF_CONVERSIONS__',
'-D__CUDA_NO_HALF2_OPERATORS__',
]
JIT_EXTENSION_VERSIONER = ExtensionVersioner()
def _is_binary_build():
return not BUILT_FROM_SOURCE_VERSION_PATTERN.match(torch.version.__version__)
def _accepted_compilers_for_platform():
return ['clang++', 'clang'] if sys.platform.startswith('darwin') else ['g++', 'gcc']
def get_default_build_root():
return os.path.realpath(os.path.join(tempfile.gettempdir(), 'torch_extensions'))
def check_compiler_ok_for_platform(compiler):
if IS_WINDOWS:
return True
which = subprocess.check_output(['which', compiler], stderr=subprocess.STDOUT)
# Use os.path.realpath to resolve any symlinks, in particular from 'c++' to e.g. 'g++'.
compiler_path = os.path.realpath(which.decode().strip())
return any(name in compiler_path for name in _accepted_compilers_for_platform())
def check_compiler_abi_compatibility(compiler):
'''
Verifies that the given compiler is ABI-compatible with PyTorch.
'''
if not _is_binary_build():
return True
if os.environ.get('TORCH_DONT_CHECK_COMPILER_ABI') in ['ON', '1', 'YES', 'TRUE', 'Y']:
return True
# First check if the compiler is one of the expected ones for the particular platform.
if not check_compiler_ok_for_platform(compiler):
warnings.warn(WRONG_COMPILER_WARNING.format(
user_compiler=compiler,
pytorch_compiler=_accepted_compilers_for_platform()[0],
platform=sys.platform))
return False
if sys.platform.startswith('darwin'):
return True
try:
if sys.platform.startswith('linux'):
minimum_required_version = MINIMUM_GCC_VERSION
version = subprocess.check_output([compiler, '-dumpfullversion', '-dumpversion'])
version = version.decode().strip().split('.')
else:
minimum_required_version = MINIMUM_MSVC_VERSION
compiler_info = subprocess.check_output(compiler, stderr=subprocess.STDOUT)
match = re.search(r'(\d+)\.(\d+)\.(\d+)', compiler_info.decode().strip())
version = (0, 0, 0) if match is None else match.groups()
except Exception:
_, error, _ = sys.exc_info()
warnings.warn('Error checking compiler version for {}: {}'.format(compiler, error))
return False
if tuple(map(int, version)) >= minimum_required_version:
return True
compiler = '{} {}'.format(compiler, ".".join(version))
warnings.warn(ABI_INCOMPATIBILITY_WARNING.format(compiler))
return False
class BuildExtension(build_ext, object):
@classmethod
def with_options(cls, **options):
def init_with_options(*args, **kwargs):
kwargs = kwargs.copy()
kwargs.update(options)
return cls(*args, **kwargs)
return init_with_options
def __init__(self, *args, **kwargs):
super(BuildExtension, self).__init__(*args, **kwargs)
self.no_python_abi_suffix = kwargs.get("no_python_abi_suffix", False)
def build_extensions(self):
self._check_abi()
for extension in self.extensions:
self._add_compile_flag(extension, '-DTORCH_API_INCLUDE_EXTENSION_H')
self._define_torch_extension_name(extension)
self._add_gnu_abi_flag_if_binary(extension)
# Register .cu and .cuh as valid source extensions.
self.compiler.src_extensions += ['.cu', '.cuh']
# Save the original _compile method for later.
if self.compiler.compiler_type == 'msvc':
self.compiler._cpp_extensions += ['.cu', '.cuh']
original_compile = self.compiler.compile
original_spawn = self.compiler.spawn
else:
original_compile = self.compiler._compile
def unix_wrap_compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
# Copy before we make any modifications.
cflags = copy.deepcopy(extra_postargs)
try:
original_compiler = self.compiler.compiler_so
if _is_cuda_file(src):
nvcc = _join_cuda_home('bin', 'nvcc')
if not isinstance(nvcc, list):
nvcc = [nvcc]
self.compiler.set_executable('compiler_so', nvcc)
if isinstance(cflags, dict):
cflags = cflags['nvcc']
cflags = COMMON_NVCC_FLAGS + ['--compiler-options', "'-fPIC'"] + cflags
elif isinstance(cflags, dict):
cflags = cflags['cxx']
# NVCC does not allow multiple -std to be passed, so we avoid
# overriding the option if the user explicitly passed it.
if not any(flag.startswith('-std=') for flag in cflags):
cflags.append('-std=c++11')
original_compile(obj, src, ext, cc_args, cflags, pp_opts)
finally:
# Put the original compiler back in place.
self.compiler.set_executable('compiler_so', original_compiler)
def win_wrap_compile(sources,
output_dir=None,
macros=None,
include_dirs=None,
debug=0,
extra_preargs=None,
extra_postargs=None,
depends=None):
self.cflags = copy.deepcopy(extra_postargs)
extra_postargs = None
def spawn(cmd):
src_regex = re.compile('/T(p|c)(.*)')
src_list = [
m.group(2) for m in (src_regex.match(elem) for elem in cmd)
if m
]
obj_regex = re.compile('/Fo(.*)')
obj_list = [
m.group(1) for m in (obj_regex.match(elem) for elem in cmd)
if m
]
include_regex = re.compile(r'((\-|\/)I.*)')
include_list = [
m.group(1)
for m in (include_regex.match(elem) for elem in cmd) if m
]
if len(src_list) >= 1 and len(obj_list) >= 1:
src = src_list[0]
obj = obj_list[0]
if _is_cuda_file(src):
nvcc = _join_cuda_home('bin', 'nvcc')
if isinstance(self.cflags, dict):
cflags = self.cflags['nvcc']
elif isinstance(self.cflags, list):
cflags = self.cflags
else:
cflags = []
cmd = [
nvcc, '-c', src, '-o', obj, '-Xcompiler',
'/wd4819', '-Xcompiler', '/MD'
] + include_list + cflags
elif isinstance(self.cflags, dict):
cflags = self.cflags['cxx']
cmd += cflags
elif isinstance(self.cflags, list):
cflags = self.cflags
cmd += cflags
return original_spawn(cmd)
try:
self.compiler.spawn = spawn
return original_compile(sources, output_dir, macros,
include_dirs, debug, extra_preargs,
extra_postargs, depends)
finally:
self.compiler.spawn = original_spawn
if self.compiler.compiler_type == 'msvc':
self.compiler.compile = win_wrap_compile
else:
self.compiler._compile = unix_wrap_compile
build_ext.build_extensions(self)
def get_ext_filename(self, ext_name):
ext_filename = super(BuildExtension, self).get_ext_filename(ext_name)
if self.no_python_abi_suffix and sys.version_info >= (3, 0):
ext_filename_parts = ext_filename.split('.')
without_abi = ext_filename_parts[:-2] + ext_filename_parts[-1:]
ext_filename = '.'.join(without_abi)
return ext_filename
def _check_abi(self):
if hasattr(self.compiler, 'compiler_cxx'):
compiler = self.compiler.compiler_cxx[0]
elif IS_WINDOWS:
compiler = os.environ.get('CXX', 'cl')
else:
compiler = os.environ.get('CXX', 'c++')
check_compiler_abi_compatibility(compiler)
def _add_compile_flag(self, extension, flag):
extension.extra_compile_args = copy.copy(extension.extra_compile_args)
if isinstance(extension.extra_compile_args, dict):
for args in extension.extra_compile_args.values():
args.append(flag)
else:
extension.extra_compile_args.append(flag)
def _define_torch_extension_name(self, extension):
names = extension.name.split('.')
name = names[-1]
define = '-DTORCH_EXTENSION_NAME={}'.format(name)
self._add_compile_flag(extension, define)
def _add_gnu_abi_flag_if_binary(self, extension):
if _is_binary_build():
self._add_compile_flag(extension, '-D_GLIBCXX_USE_CXX11_ABI=0')
def CppExtension(name, sources, *args, **kwargs):
include_dirs = kwargs.get('include_dirs', [])
include_dirs += include_paths()
kwargs['include_dirs'] = include_dirs
if IS_WINDOWS:
library_dirs = kwargs.get('library_dirs', [])
library_dirs += library_paths()
kwargs['library_dirs'] = library_dirs
libraries = kwargs.get('libraries', [])
libraries.append('c10')
libraries.append('caffe2')
libraries.append('torch')
libraries.append('torch_python')
libraries.append('_C')
kwargs['libraries'] = libraries
kwargs['language'] = 'c++'
return setuptools.Extension(name, sources, *args, **kwargs)
def CUDAExtension(name, sources, *args, **kwargs):
library_dirs = kwargs.get('library_dirs', [])
library_dirs += library_paths(cuda=True)
kwargs['library_dirs'] = library_dirs
libraries = kwargs.get('libraries', [])
libraries.append('cudart')
if IS_WINDOWS:
libraries.append('c10')
libraries.append('caffe2')
libraries.append('torch')
libraries.append('torch_python')
libraries.append('caffe2_gpu')
libraries.append('_C')
kwargs['libraries'] = libraries
include_dirs = kwargs.get('include_dirs', [])
include_dirs += include_paths(cuda=True)
kwargs['include_dirs'] = include_dirs
kwargs['language'] = 'c++'
return setuptools.Extension(name, sources, *args, **kwargs)
def include_paths(cuda=False):
here = os.path.abspath(__file__)
torch_path = os.path.dirname(os.path.dirname(here))
lib_include = os.path.join(torch_path, 'lib', 'include')
paths = [
lib_include,
os.path.join(lib_include, 'torch', 'csrc', 'api', 'include'),
os.path.join(lib_include, 'TH'),
os.path.join(lib_include, 'THC')
]
if cuda:
paths.append(_join_cuda_home('include'))
if CUDNN_HOME is not None:
paths.append(os.path.join(CUDNN_HOME, 'include'))
return paths
def library_paths(cuda=False):
paths = []
if IS_WINDOWS:
here = os.path.abspath(__file__)
torch_path = os.path.dirname(os.path.dirname(here))
lib_path = os.path.join(torch_path, 'lib')
paths.append(lib_path)
if cuda:
lib_dir = 'lib/x64' if IS_WINDOWS else 'lib64'
paths.append(_join_cuda_home(lib_dir))
if CUDNN_HOME is not None:
paths.append(os.path.join(CUDNN_HOME, lib_dir))
return paths
def load(name,
sources,
extra_cflags=None,
extra_cuda_cflags=None,
extra_ldflags=None,
extra_include_paths=None,
build_directory=None,
verbose=False,
with_cuda=None,
is_python_module=True):
return _jit_compile(
name,
[sources] if isinstance(sources, str) else sources,
extra_cflags,
extra_cuda_cflags,
extra_ldflags,
extra_include_paths,
build_directory or _get_build_directory(name, verbose),
verbose,
with_cuda,
is_python_module)
def load_inline(name,
cpp_sources,
cuda_sources=None,
functions=None,
extra_cflags=None,
extra_cuda_cflags=None,
extra_ldflags=None,
extra_include_paths=None,
build_directory=None,
verbose=False,
with_cuda=None,
is_python_module=True):
build_directory = build_directory or _get_build_directory(name, verbose)
if isinstance(cpp_sources, str):
cpp_sources = [cpp_sources]
cuda_sources = cuda_sources or []
if isinstance(cuda_sources, str):
cuda_sources = [cuda_sources]
cpp_sources.insert(0, '#include ')
if functions is not None:
cpp_sources.append('PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {')
if isinstance(functions, str):
functions = [functions]
if isinstance(functions, list):
# Make the function docstring the same as the function name.
functions = dict((f, f) for f in functions)
elif not isinstance(functions, dict):
raise ValueError(
"Expected 'functions' to be a list or dict, but was {}".format(
type(functions)))
for function_name, docstring in functions.items():
cpp_sources.append('m.def("{0}", &{0}, "{1}");'.format(
function_name, docstring))
cpp_sources.append('}')
cpp_source_path = os.path.join(build_directory, 'main.cpp')
with open(cpp_source_path, 'w') as cpp_source_file:
cpp_source_file.write('\n'.join(cpp_sources))
sources = [cpp_source_path]
if cuda_sources:
cuda_sources.insert(0, '#include ')
cuda_sources.insert(1, '#include ')
cuda_sources.insert(2, '#include ')
cuda_source_path = os.path.join(build_directory, 'cuda.cu')
with open(cuda_source_path, 'w') as cuda_source_file:
cuda_source_file.write('\n'.join(cuda_sources))
sources.append(cuda_source_path)
return _jit_compile(
name,
sources,
extra_cflags,
extra_cuda_cflags,
extra_ldflags,
extra_include_paths,
build_directory,
verbose,
with_cuda,
is_python_module)
def _jit_compile(name,
sources,
extra_cflags,
extra_cuda_cflags,
extra_ldflags,
extra_include_paths,
build_directory,
verbose,
with_cuda,
is_python_module):
old_version = JIT_EXTENSION_VERSIONER.get_version(name)
version = JIT_EXTENSION_VERSIONER.bump_version_if_changed(
name,
sources,
build_arguments=[extra_cflags, extra_cuda_cflags, extra_ldflags, extra_include_paths],
build_directory=build_directory,
with_cuda=with_cuda
)
if version > 0:
if version != old_version and verbose:
print('The input conditions for extension module {} have changed. '.format(name) +
'Bumping to version {0} and re-building as {1}_v{0}...'.format(version, name))
name = '{}_v{}'.format(name, version)
if version != old_version:
baton = FileBaton(os.path.join(build_directory, 'lock'))
if baton.try_acquire():
try:
_write_ninja_file_and_build(
name=name,
sources=sources,
extra_cflags=extra_cflags or [],
extra_cuda_cflags=extra_cuda_cflags or [],
extra_ldflags=extra_ldflags or [],
extra_include_paths=extra_include_paths or [],
build_directory=build_directory,
verbose=verbose,
with_cuda=with_cuda)
finally:
baton.release()
else:
baton.wait()
elif verbose:
print('No modifications detected for re-loaded extension '
'module {}, skipping build step...'.format(name))
if verbose:
print('Loading extension module {}...'.format(name))
return _import_module_from_library(name, build_directory, is_python_module)
def _write_ninja_file_and_build(name,
sources,
extra_cflags,
extra_cuda_cflags,
extra_ldflags,
extra_include_paths,
build_directory,
verbose,
with_cuda):
verify_ninja_availability()
check_compiler_abi_compatibility(os.environ.get('CXX', 'c++'))
if with_cuda is None:
with_cuda = any(map(_is_cuda_file, sources))
extra_ldflags = _prepare_ldflags(
extra_ldflags or [],
with_cuda,
verbose)
build_file_path = os.path.join(build_directory, 'build.ninja')
if verbose:
print(
'Emitting ninja build file {}...'.format(build_file_path))
_write_ninja_file(
path=build_file_path,
name=name,
sources=sources,
extra_cflags=extra_cflags or [],
extra_cuda_cflags=extra_cuda_cflags or [],
extra_ldflags=extra_ldflags or [],
extra_include_paths=extra_include_paths or [],
with_cuda=with_cuda)
if verbose:
print('Building extension module {}...'.format(name))
_build_extension_module(name, build_directory, verbose)
def verify_ninja_availability():
with open(os.devnull, 'wb') as devnull:
try:
subprocess.check_call('ninja --version'.split(), stdout=devnull)
except OSError:
raise RuntimeError("Ninja is required to load C++ extensions")
else:
return True
def _prepare_ldflags(extra_ldflags, with_cuda, verbose):
if IS_WINDOWS:
python_path = os.path.dirname(sys.executable)
python_lib_path = os.path.join(python_path, 'libs')
here = os.path.abspath(__file__)
torch_path = os.path.dirname(os.path.dirname(here))
lib_path = os.path.join(torch_path, 'lib')
extra_ldflags.append('c10.lib')
extra_ldflags.append('caffe2.lib')
extra_ldflags.append('torch.lib')
extra_ldflags.append('torch_python.lib')
if with_cuda:
extra_ldflags.append('caffe2_gpu.lib')
extra_ldflags.append('_C.lib')
extra_ldflags.append('/LIBPATH:{}'.format(python_lib_path))
extra_ldflags.append('/LIBPATH:{}'.format(lib_path))
if with_cuda:
if verbose:
print('Detected CUDA files, patching ldflags')
if IS_WINDOWS:
extra_ldflags.append('/LIBPATH:{}'.format(
_join_cuda_home('lib/x64')))
extra_ldflags.append('cudart.lib')
if CUDNN_HOME is not None:
extra_ldflags.append(os.path.join(CUDNN_HOME, 'lib/x64'))
else:
extra_ldflags.append('-L{}'.format(_join_cuda_home('lib64')))
extra_ldflags.append('-lcudart')
if CUDNN_HOME is not None:
extra_ldflags.append('-L{}'.format(os.path.join(CUDNN_HOME, 'lib64')))
return extra_ldflags
def _get_build_directory(name, verbose):
root_extensions_directory = os.environ.get('TORCH_EXTENSIONS_DIR')
if root_extensions_directory is None:
root_extensions_directory = get_default_build_root()
if verbose:
print('Using {} as PyTorch extensions root...'.format(
root_extensions_directory))
build_directory = os.path.join(root_extensions_directory, name)
if not os.path.exists(build_directory):
if verbose:
print('Creating extension directory {}...'.format(build_directory))
os.makedirs(build_directory)
return build_directory
def _build_extension_module(name, build_directory, verbose):
try:
sys.stdout.flush()
sys.stderr.flush()
if sys.version_info >= (3, 5):
subprocess.run(
['ninja', '-v'],
stdout=None if verbose else subprocess.PIPE,
stderr=subprocess.STDOUT,
cwd=build_directory,
check=True)
else:
subprocess.check_output(
['ninja', '-v'],
stderr=subprocess.STDOUT,
cwd=build_directory)
except subprocess.CalledProcessError:
_, error, _ = sys.exc_info()
message = "Error building extension '{}'".format(name)
if hasattr(error, 'output') and error.output:
message += ": {}".format(error.output.decode())
raise RuntimeError(message)
def _import_module_from_library(module_name, path, is_python_module):
file, path, description = imp.find_module(module_name, [path])
with file:
if is_python_module:
return imp.load_module(module_name, file, path, description)
else:
return torch.ops.load_library(path)
def _write_ninja_file(path,
name,
sources,
extra_cflags,
extra_cuda_cflags,
extra_ldflags,
extra_include_paths,
with_cuda):
extra_cflags = [flag.strip() for flag in extra_cflags]
extra_cuda_cflags = [flag.strip() for flag in extra_cuda_cflags]
extra_ldflags = [flag.strip() for flag in extra_ldflags]
extra_include_paths = [flag.strip() for flag in extra_include_paths]
config = ['ninja_required_version = 1.3']
config.append('cxx = {}'.format(os.environ.get('CXX', 'c++')))
if with_cuda:
config.append('nvcc = {}'.format(_join_cuda_home('bin', 'nvcc')))
sources = [os.path.abspath(file) for file in sources]
user_includes = [os.path.abspath(file) for file in extra_include_paths]
system_includes = include_paths(with_cuda)
system_includes.append(sysconfig.get_paths()['include'])
if IS_WINDOWS:
user_includes += system_includes
system_includes.clear()
common_cflags = ['-DTORCH_EXTENSION_NAME={}'.format(name)]
common_cflags.append('-DTORCH_API_INCLUDE_EXTENSION_H')
common_cflags += ['-I{}'.format(include) for include in user_includes]
common_cflags += ['-isystem {}'.format(include) for include in system_includes]
if _is_binary_build():
common_cflags += ['-D_GLIBCXX_USE_CXX11_ABI=0']
cflags = common_cflags + ['-fPIC', '-std=c++11'] + extra_cflags
if IS_WINDOWS:
from distutils.spawn import _nt_quote_args
cflags = _nt_quote_args(cflags)
flags = ['cflags = {}'.format(' '.join(cflags))]
if with_cuda:
cuda_flags = common_cflags + COMMON_NVCC_FLAGS
if IS_WINDOWS:
cuda_flags = _nt_quote_args(cuda_flags)
else:
cuda_flags += ['--compiler-options', "'-fPIC'"]
cuda_flags += extra_cuda_cflags
if not any(flag.startswith('-std=') for flag in cuda_flags):
cuda_flags.append('-std=c++11')
flags.append('cuda_flags = {}'.format(' '.join(cuda_flags)))
if IS_WINDOWS:
ldflags = ['/DLL'] + extra_ldflags
else:
ldflags = ['-shared'] + extra_ldflags
# The darwin linker needs explicit consent to ignore unresolved symbols.
if sys.platform.startswith('darwin'):
ldflags.append('-undefined dynamic_lookup')
elif IS_WINDOWS:
ldflags = _nt_quote_args(ldflags)
flags.append('ldflags = {}'.format(' '.join(ldflags)))
compile_rule = ['rule compile']
if IS_WINDOWS:
compile_rule.append(
' command = cl /showIncludes $cflags -c $in /Fo$out')
compile_rule.append(' deps = msvc')
else:
compile_rule.append(
' command = $cxx -MMD -MF $out.d $cflags -c $in -o $out')
compile_rule.append(' depfile = $out.d')
compile_rule.append(' deps = gcc')
if with_cuda:
cuda_compile_rule = ['rule cuda_compile']
cuda_compile_rule.append(
' command = $nvcc $cuda_flags -c $in -o $out')
link_rule = ['rule link']
if IS_WINDOWS:
cl_paths = subprocess.check_output(['where',
'cl']).decode().split('\r\n')
if len(cl_paths) >= 1:
cl_path = os.path.dirname(cl_paths[0]).replace(':', '$:')
else:
raise RuntimeError("MSVC is required to load C++ extensions")
link_rule.append(
' command = "{}/link.exe" $in /nologo $ldflags /out:$out'.format(
cl_path))
else:
link_rule.append(' command = $cxx $in $ldflags -o $out')
object_files = []
build = []
for source_file in sources:
file_name = os.path.splitext(os.path.basename(source_file))[0]
if _is_cuda_file(source_file) and with_cuda:
rule = 'cuda_compile'
target = '{}.cuda.o'.format(file_name)
else:
rule = 'compile'
target = '{}.o'.format(file_name)
object_files.append(target)
if IS_WINDOWS:
source_file = source_file.replace(':', '$:')
source_file = source_file.replace(" ", "$ ")
build.append('build {}: {} {}'.format(target, rule, source_file))
ext = 'pyd' if IS_WINDOWS else 'so'
library_target = '{}.{}'.format(name, ext)
link = ['build {}: link {}'.format(library_target, ' '.join(object_files))]
default = ['default {}'.format(library_target)]
blocks = [config, flags, compile_rule]
if with_cuda:
blocks.append(cuda_compile_rule)
blocks += [link_rule, build, link, default]
with open(path, 'w') as build_file:
for block in blocks:
lines = '\n'.join(block)
build_file.write('{}\n\n'.format(lines))
def _join_cuda_home(*paths):
if CUDA_HOME is None:
raise EnvironmentError('CUDA_HOME environment variable is not set. '
'Please set it to your CUDA install root.')
return os.path.join(CUDA_HOME, *paths)
def _is_cuda_file(path):
return os.path.splitext(path)[1] in ['.cu', '.cuh']
这是错误消息：
用户警告：检查 cl 的编译器版本时出错：“utf-8”编解码器无法解码位置 54 中的字节 0xff：起始字节无效
任何帮助将不胜感激！
谢谢！
解决方案
如果您使用的是 Linux，那么通常可以解决此类解码问题的解决方案是执行以下操作：
export LC_ALL=C.UTF-8
推荐阅读
- python - 如何从数据框中的日期时间列中查找日期范围？
- c++ - 在迭代容器时更改容器元素的惯用方式
- python - Python：排列
- sql - 如何解决 SQL Server 数据库连接字符串 (ASP.NET) 中的 proivder 错误
- matlab - 在现有 CSV 文件的末尾追加新行
- python - dnspython：如何以字节形式获得响应
- javascript - 单击按钮时清除输入文本
- c++ - 如何在 C++ 程序中的 2 个特定字符之间比较 2 个文件中的文本行
- outlook - 全天事件的 originalStartTimeZone 不一致
- java - 如何确定两个方法调用层次结构相交的位置？