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"""
This file must not depend on any other CuPy modules.
"""
import ctypes
import importlib.metadata
import json
import os
import os.path
import platform
import re
import shutil
import sys
from typing import Any, Dict, List, Optional, Tuple
import warnings
# '' for uninitialized, None for non-existing
_cuda_path = ''
_nvcc_path = ''
_rocm_path = ''
_hipcc_path = ''
_cub_path = ''
"""
Library Preloading
------------------
Wheel packages are built against specific versions of CUDA libraries
(cuTENSOR/NCCL/cuDNN).
To avoid loading wrong version, these shared libraries are manually
preloaded.
# TODO(kmaehashi): Support NCCL
Example of `_preload_config` is as follows:
{
# installation source
'packaging': 'pip',
# CUDA version string
'cuda': '11.0',
'cudnn': {
# cuDNN version string
'version': '8.0.0',
# names of the shared library
'filenames': ['libcudnn.so.X.Y.Z'] # or `cudnn64_X.dll` for Windows
}
}
The configuration file is intended solely for internal purposes and
not expected to be parsed by end-users.
"""
_preload_config = None
_preload_libs = {
'cudnn': None,
'nccl': None,
'cutensor': None,
}
_debug = os.environ.get('CUPY_DEBUG_LIBRARY_LOAD', '0') == '1'
def _log(msg: str) -> None:
if _debug:
sys.stderr.write(f'[CUPY_DEBUG_LIBRARY_LOAD] {msg}\n')
sys.stderr.flush()
def get_cuda_path():
# Returns the CUDA installation path or None if not found.
global _cuda_path
if _cuda_path == '':
_cuda_path = _get_cuda_path()
return _cuda_path
def get_nvcc_path():
# Returns the path to the nvcc command or None if not found.
global _nvcc_path
if _nvcc_path == '':
_nvcc_path = _get_nvcc_path()
return _nvcc_path
def get_rocm_path():
# Returns the ROCm installation path or None if not found.
global _rocm_path
if _rocm_path == '':
_rocm_path = _get_rocm_path()
return _rocm_path
def get_hipcc_path():
# Returns the path to the hipcc command or None if not found.
global _hipcc_path
if _hipcc_path == '':
_hipcc_path = _get_hipcc_path()
return _hipcc_path
def get_cub_path():
# Returns the CUB header path or None if not found.
global _cub_path
if _cub_path == '':
_cub_path = _get_cub_path()
return _cub_path
def _get_cuda_path():
# Use environment variable
cuda_path = os.environ.get('CUDA_PATH', '') # Nvidia default on Windows
if os.path.exists(cuda_path):
return cuda_path
# Use nvcc path
nvcc_path = shutil.which('nvcc')
if nvcc_path is not None:
return os.path.dirname(os.path.dirname(nvcc_path))
# Use typical path
if os.path.exists('/usr/local/cuda'):
return '/usr/local/cuda'
return None
def _get_nvcc_path():
# Honor the "NVCC" env var
nvcc_path = os.environ.get('NVCC', None)
if nvcc_path is not None:
return nvcc_path
# Lookup <CUDA>/bin
cuda_path = get_cuda_path()
if cuda_path is None:
return None
return shutil.which('nvcc', path=os.path.join(cuda_path, 'bin'))
def _get_rocm_path():
# Use environment variable
rocm_path = os.environ.get('ROCM_HOME', '')
if os.path.exists(rocm_path):
return rocm_path
# Use hipcc path
hipcc_path = shutil.which('hipcc')
if hipcc_path is not None:
return os.path.dirname(os.path.dirname(hipcc_path))
# Use typical path
if os.path.exists('/opt/rocm'):
return '/opt/rocm'
return None
def _get_hipcc_path():
# TODO(leofang): Introduce an env var HIPCC?
# Lookup <ROCM>/bin
rocm_path = get_rocm_path()
if rocm_path is None:
return None
return shutil.which('hipcc', path=os.path.join(rocm_path, 'bin'))
def _get_cub_path():
# runtime discovery of CUB headers
from cupy_backends.cuda.api import runtime
current_dir = os.path.dirname(os.path.abspath(__file__))
if not runtime.is_hip:
if os.path.isdir(
os.path.join(current_dir, '_core/include/cupy/_cccl/cub')):
_cub_path = '<bundle>'
else:
_cub_path = None
else:
# the bundled CUB does not work in ROCm
rocm_path = get_rocm_path()
if rocm_path is not None and os.path.isdir(
os.path.join(rocm_path, 'include/hipcub')):
# use hipCUB
_cub_path = '<ROCm>'
else:
_cub_path = None
return _cub_path
def _setup_win32_dll_directory():
# Setup DLL directory to load CUDA Toolkit libs and shared libraries
# added during the build process.
if sys.platform.startswith('win32'):
# see _can_attempt_preload()
config = get_preload_config()
is_conda = (config is not None and (config['packaging'] == 'conda'))
# Path to the CUDA Toolkit binaries
cuda_path = get_cuda_path()
if cuda_path is not None:
if is_conda:
cuda_bin_path = cuda_path
else:
cuda_bin_path = os.path.join(cuda_path, 'bin')
else:
cuda_bin_path = None
if not is_conda:
warnings.warn(
'CUDA path could not be detected.'
' Set CUDA_PATH environment variable if CuPy '
'fails to load.')
_log('CUDA_PATH: {}'.format(cuda_path))
# Path to shared libraries in wheel
wheel_libdir = os.path.join(
get_cupy_install_path(), 'cupy', '.data', 'lib')
if os.path.isdir(wheel_libdir):
_log('Wheel shared libraries: {}'.format(wheel_libdir))
else:
_log('Not wheel distribution ({} not found)'.format(
wheel_libdir))
wheel_libdir = None
if (3, 8) <= sys.version_info:
if cuda_bin_path is not None:
_log('Adding DLL search path: {}'.format(cuda_bin_path))
os.add_dll_directory(cuda_bin_path)
if wheel_libdir is not None:
_log('Adding DLL search path: {}'.format(wheel_libdir))
os.add_dll_directory(wheel_libdir)
else:
# Users are responsible for adding `%CUDA_PATH%/bin` to PATH.
if wheel_libdir is not None:
_log('Adding to PATH: {}'.format(wheel_libdir))
path = os.environ.get('PATH', '')
os.environ['PATH'] = wheel_libdir + os.pathsep + path
def get_cupy_install_path():
# Path to the directory where the package is installed.
return os.path.abspath(
os.path.join(os.path.dirname(__file__), '..'))
def get_cupy_cuda_lib_path():
"""Returns the directory where CUDA external libraries are installed.
This environment variable only affects wheel installations.
Shared libraries are looked up from
`$CUPY_CUDA_LIB_PATH/$CUDA_VER/$LIB_NAME/$LIB_VER/{lib,lib64,bin}`,
e.g., `~/.cupy/cuda_lib/11.2/cudnn/8.1.1/lib64/libcudnn.so.8.1.1`.
The default $CUPY_CUDA_LIB_PATH is `~/.cupy/cuda_lib`.
"""
cupy_cuda_lib_path = os.environ.get('CUPY_CUDA_LIB_PATH', None)
if cupy_cuda_lib_path is None:
return os.path.expanduser('~/.cupy/cuda_lib')
return os.path.abspath(cupy_cuda_lib_path)
def get_preload_config() -> Optional[Dict[str, Any]]:
global _preload_config
if _preload_config is None:
_preload_config = _get_json_data('_wheel.json')
return _preload_config
def _get_json_data(name: str) -> Optional[Dict[str, Any]]:
config_path = os.path.join(
get_cupy_install_path(), 'cupy', '.data', name)
if not os.path.exists(config_path):
return None
with open(config_path) as f:
return json.load(f)
def _can_attempt_preload(lib: str) -> bool:
"""Returns if the preload can be attempted."""
config = get_preload_config()
if (config is None) or (config['packaging'] == 'conda'):
# We don't do preload if CuPy is installed from Conda-Forge, as we
# cannot guarantee the version pinned in _wheel.json, which is
# encoded in config[lib]['filenames'], is always available on
# Conda-Forge. See here for the configuration files used in
# Conda-Forge distributions.
# https://github.com/conda-forge/cupy-feedstock/blob/master/recipe/preload_config/
_log(f'Not preloading {lib} as this is not a pip wheel installation')
return False
if lib not in _preload_libs:
raise AssertionError(f'Unknown preload library: {lib}')
if lib not in config:
_log(f'Preload {lib} not configured in wheel')
return False
if _preload_libs[lib] is not None:
_log(f'Preload already attempted: {lib}')
return False
return True
def _preload_library(lib):
"""Preload dependent shared libraries.
The preload configuration file (cupy/.data/_wheel.json) will be added
during the wheel build process.
"""
_log(f'Preloading triggered for library: {lib}')
if not _can_attempt_preload(lib):
return
_preload_libs[lib] = {}
config = get_preload_config()
cuda_version = config['cuda']
_log('CuPy wheel package built for CUDA {}'.format(cuda_version))
cupy_cuda_lib_path = get_cupy_cuda_lib_path()
_log('CuPy CUDA library directory: {}'.format(cupy_cuda_lib_path))
version = config[lib]['version']
filenames = config[lib]['filenames']
for filename in filenames:
_log(f'Looking for {lib} version {version} ({filename})')
# "lib": cuTENSOR (Linux/Windows) / NCCL (Linux)
# "lib64": cuDNN (Linux)
# "bin": cuDNN (Windows)
libpath_cands = [
os.path.join(
cupy_cuda_lib_path, config['cuda'], lib, version, x,
filename)
for x in ['lib', 'lib64', 'bin']]
if lib == 'cutensor':
libpath_cands = (
_get_cutensor_from_wheel(version, config['cuda']) +
libpath_cands)
for libpath in libpath_cands:
if not os.path.exists(libpath):
_log('Rejected candidate (not found): {}'.format(libpath))
continue
try:
_log(f'Trying to load {libpath}')
# Keep reference to the preloaded module.
_preload_libs[lib][libpath] = ctypes.CDLL(libpath)
_log('Loaded')
break
except Exception as e:
e_type = type(e).__name__ # NOQA
msg = (
f'CuPy failed to preload library ({libpath}): '
f'{e_type} ({e})')
_log(msg)
warnings.warn(msg)
else:
_log('File {} could not be found'.format(filename))
# Lookup library with fully-qualified version (e.g.,
# `libcudnn.so.X.Y.Z`).
_log(f'Trying to load {filename} from default search path')
try:
_preload_libs[lib][filename] = ctypes.CDLL(filename)
_log('Loaded')
except Exception as e:
# Fallback to the standard shared library lookup which only
# uses the major version (e.g., `libcudnn.so.X`).
_log(f'Library {lib} could not be preloaded: {e}')
def _parse_version(version: str) -> Tuple[int, int, int]:
parts = re.split(r'[^\d]', version, maxsplit=3)
major = int(parts[0])
minor = int(parts[1]) if len(parts) >= 2 else 0
patch = int(parts[2]) if len(parts) >= 3 else 0
return major, minor, patch
def _get_cutensor_from_wheel(version: str, cuda: str) -> List[str]:
"""
Returns the list of shared library path candidates for cuTENSOR
installed via Pip (cutensor-cuXX package).
"""
cuda_major_ver, _ = cuda.split('.')
cutensor_pkg = f'cutensor-cu{cuda_major_ver}'
try:
cutensor_dist = importlib.metadata.distribution(cutensor_pkg)
except importlib.metadata.PackageNotFoundError:
_log(f'cuTENSOR wheel package not installed: {cutensor_pkg}')
return []
actual = _parse_version(cutensor_dist.version)
expected = _parse_version(version)
is_compatible = (
actual[0] == expected[0] and
actual[1] >= expected[1] and
actual[2] >= expected[2]
)
if not is_compatible:
_log('cuTENSOR wheel incompatible: '
f'expected {version}, found {cutensor_dist.version}')
return []
if sys.platform == 'linux':
shared_lib = cutensor_dist.locate_file(
f'cutensor/lib/libcutensor.so.{version.split(".")[0]}'
)
else:
shared_lib = cutensor_dist.locate_file('cutensor\\bin\\cutensor.dll')
return [str(shared_lib)]
def _preload_warning(lib, exc):
config = get_preload_config()
if config is None or lib not in config:
return
if config['packaging'] == 'pip':
cuda = config['cuda']
if lib == 'cutensor':
cuda_major = cuda.split('.')[0]
version = config['cutensor']['version']
cmd = f'pip install "cutensor-cu{cuda_major}~={version}"'
else:
cmd = f'python -m cupyx.tools.install_library --library {lib} --cuda {cuda}' # NOQA
elif config['packaging'] == 'conda':
cmd = f'conda install -c conda-forge {lib}'
else:
raise AssertionError
warnings.warn(f'''
{lib} library could not be loaded.
Reason: {type(exc).__name__} ({str(exc)})
You can install the library by:
$ {cmd}
''')
def _get_include_dir_from_conda_or_wheel(major: int, minor: int) -> List[str]:
# FP16 headers from CUDA 12.2+ depends on headers from CUDA Runtime.
# See https://github.com/cupy/cupy/issues/8466.
if major < 12 or (major == 12 and minor < 2):
return []
config = get_preload_config()
if config is not None and config['packaging'] == 'conda':
if sys.platform.startswith('linux'):
arch = platform.machine()
if arch == "aarch64":
arch = "sbsa"
assert arch, "platform.machine() returned an empty string"
target_dir = f"{arch}-linux"
return [
os.path.join(sys.prefix, "targets", target_dir, "include"),
os.path.join(sys.prefix, "include"),
]
elif sys.platform.startswith('win'):
return [
os.path.join(sys.prefix, "Library", "include"),
]
else:
# No idea what this platform is. Do nothing?
return []
# Look for headers in wheels
pkg_name = f'nvidia-cuda-runtime-cu{major}'
ver_str = f'{major}.{minor}'
_log(f'Looking for {pkg_name}=={ver_str}.*')
try:
dist = importlib.metadata.distribution(pkg_name)
except importlib.metadata.PackageNotFoundError:
_log('The package could not be found')
return []
if dist.version == ver_str or dist.version.startswith(f'{ver_str}.'):
include_dir = dist.locate_file('nvidia/cuda_runtime/include')
if not include_dir.exists():
_log('The include directory could not be found')
return []
return [str(include_dir)]
else:
_log(f'Found incompatible version ({dist.version})')
return []
def _detect_duplicate_installation():
# List of all CuPy packages, including out-dated ones.
known = {
'cupy',
'cupy-cuda80',
'cupy-cuda90',
'cupy-cuda91',
'cupy-cuda92',
'cupy-cuda100',
'cupy-cuda101',
'cupy-cuda102',
'cupy-cuda110',
'cupy-cuda111',
'cupy-cuda112',
'cupy-cuda113',
'cupy-cuda114',
'cupy-cuda115',
'cupy-cuda116',
'cupy-cuda117',
'cupy-cuda118',
'cupy-cuda11x',
'cupy-cuda12x',
'cupy-rocm-4-0',
'cupy-rocm-4-1',
'cupy-rocm-4-2',
'cupy-rocm-4-3',
'cupy-rocm-5-0',
}
# use metadata.get to be resilient to namespace packages
# that may be leftover in the user's path???
# something else might be triggering "Name" not existing
# But without a safe ".get" a KeyError might be raised
# not allowing us to get through the setup
# https://github.com/cupy/cupy/issues/8440
installed_names = {d.metadata.get("Name", None)
for d in importlib.metadata.distributions()}
cupy_installed = known & installed_names
if 1 < len(cupy_installed):
cupy_packages_list = ', '.join(sorted(cupy_installed))
warnings.warn(f'''
--------------------------------------------------------------------------------
CuPy may not function correctly because multiple CuPy packages are installed
in your environment:
{cupy_packages_list}
Follow these steps to resolve this issue:
1. For all packages listed above, run the following command to remove all
existing CuPy installations:
$ pip uninstall <package_name>
If you previously installed CuPy via conda, also run the following:
$ conda uninstall cupy
2. Install the appropriate CuPy package.
Refer to the Installation Guide for detailed instructions.
https://docs.cupy.dev/en/stable/install.html
--------------------------------------------------------------------------------
''')
def _diagnose_import_error() -> str:
# TODO(kmaehashi): provide better diagnostics.
msg = '''\
Failed to import CuPy.
If you installed CuPy via wheels (cupy-cudaXXX or cupy-rocm-X-X), make sure that the package matches with the version of CUDA or ROCm installed.
On Linux, you may need to set LD_LIBRARY_PATH environment variable depending on how you installed CUDA/ROCm.
On Windows, try setting CUDA_PATH environment variable.
Check the Installation Guide for details:
https://docs.cupy.dev/en/latest/install.html''' # NOQA
if sys.platform == 'win32':
try:
msg += _diagnose_win32_dll_load()
except Exception as e:
msg += (
'\n\nThe cause could not be identified: '
f'{type(e).__name__}: {e}'
)
return msg
def _diagnose_win32_dll_load() -> str:
depends = _get_json_data('_depends.json')
if depends is None:
return ''
from ctypes import wintypes
kernel32 = ctypes.CDLL('kernel32')
kernel32.GetModuleFileNameW.argtypes = [
wintypes.HANDLE, wintypes.LPWSTR, wintypes.DWORD]
kernel32.GetModuleFileNameW.restype = wintypes.DWORD
# Show dependents in similar form of ldd on Linux.
lines = [
'',
'',
f'CUDA Path: {get_cuda_path()}',
'DLL dependencies:'
]
filepath = ctypes.create_unicode_buffer(2**15)
for name in depends['depends']:
try:
dll = ctypes.CDLL(name)
kernel32.GetModuleFileNameW(dll._handle, filepath, len(filepath))
lines.append(f' {name} -> {filepath.value}')
except FileNotFoundError:
lines.append(f' {name} -> not found')
except Exception as e:
lines.append(f' {name} -> error ({type(e).__name__}: {e})')
return '\n'.join(lines)
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