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9477a5d9c80d96e588e2e0e80320efcccbe83414
pytorch/setup.py
Zachary DeVito 9477a5d9c8 Remove bash from build (#16289) 
Summary:
This commit removes the dependency on `build_pytorch_libs.sh` by moving the remaining functionality that is not expressible in cmake into python. Removing the indirection through bash also removes over 300 lines of environment munging code that is incredibly hard to understand because it passes a lot of secret parameters through `os.env`.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/16289

Reviewed By: ezyang

Differential Revision: D13821662

Pulled By: zdevito

fbshipit-source-id: d658d26925e3b1169ac1e3d44a159cf8a1f0d9b1
2019-01-25 16:03:53 -08:00

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# Welcome to the PyTorch setup.py.
#
# Environment variables you are probably interested in:
#
# DEBUG
# build with -O0 and -g (debug symbols)
#
# REL_WITH_DEB_INFO
# build with optimizations and -g (debug symbols)
#
# MAX_JOBS
# maximum number of compile jobs we should use to compile your code
#
# NO_CUDA
# disables CUDA build
#
# CFLAGS
# flags to apply to both C and C++ files to be compiled (a quirk of setup.py
# which we have faithfully adhered to in our build system is that CFLAGS
# also applies to C++ files, in contrast to the default behavior of autogoo
# and cmake build systems.)
#
# CC
# the C/C++ compiler to use (NB: the CXX flag has no effect for distutils
# compiles, because distutils always uses CC to compile, even for C++
# files.
#
# Environment variables for feature toggles:
#
# NO_CUDNN
# disables the cuDNN build
#
# NO_FBGEMM
# disables the FBGEMM build
#
# NO_TEST
# disables the test build
#
# NO_MIOPEN
# disables the MIOpen build
#
# NO_MKLDNN
# disables use of MKLDNN
#
# NO_NNPACK
# disables NNPACK build
#
# NO_QNNPACK
# disables QNNPACK build (quantized 8-bit operators)
#
# NO_DISTRIBUTED
# disables distributed (c10d, gloo, mpi, etc.) build
#
# NO_SYSTEM_NCCL
# disables use of system-wide nccl (we will use our submoduled
# copy in third_party/nccl)
#
# NO_CAFFE2_OPS
# disable Caffe2 operators build
#
# USE_GLOO_IBVERBS
# toggle features related to distributed support
#
# USE_OPENCV
# enables use of OpenCV for additional operators
#
# USE_FFMPEG
# enables use of ffmpeg for additional operators
#
# USE_LEVELDB
# enables use of LevelDB for storage
#
# USE_LMDB
# enables use of LMDB for storage
#
# BUILD_BINARY
# enables the additional binaries/ build
#
# PYTORCH_BUILD_VERSION
# PYTORCH_BUILD_NUMBER
# specify the version of PyTorch, rather than the hard-coded version
# in this file; used when we're building binaries for distribution
#
# TORCH_CUDA_ARCH_LIST
# specify which CUDA architectures to build for.
# ie `TORCH_CUDA_ARCH_LIST="6.0;7.0"`
# These are not CUDA versions, instead, they specify what
# classes of NVIDIA hardware we should generate PTX for.
#
# ONNX_NAMESPACE
# specify a namespace for ONNX built here rather than the hard-coded
# one in this file; needed to build with other frameworks that share ONNX.
#
# BLAS
# BLAS to be used by Caffe2. Can be MKL, Eigen, ATLAS, or OpenBLAS. If set
# then the build will fail if the requested BLAS is not found, otherwise
# the BLAS will be chosen based on what is found on your system.
#
# USE_FBGEMM
# Enables use of FBGEMM
#
# USE_REDIS
# Whether to use Redis for distributed workflows (Linux only)
#
# USE_ZSTD
# Enables use of ZSTD, if the libraries are found
#
# Environment variables we respect (these environment variables are
# conventional and are often understood/set by other software.)
#
# CUDA_HOME (Linux/OS X)
# CUDA_PATH (Windows)
# specify where CUDA is installed; usually /usr/local/cuda or
# /usr/local/cuda-x.y
# CUDAHOSTCXX
# specify a different compiler than the system one to use as the CUDA
# host compiler for nvcc.
#
# CUDA_NVCC_EXECUTABLE
# Specify a NVCC to use. This is used in our CI to point to a cached nvcc
#
# CUDNN_LIB_DIR
# CUDNN_INCLUDE_DIR
# CUDNN_LIBRARY
# specify where cuDNN is installed
#
# MIOPEN_LIB_DIR
# MIOPEN_INCLUDE_DIR
# MIOPEN_LIBRARY
# specify where MIOpen is installed
#
# NCCL_ROOT_DIR
# NCCL_LIB_DIR
# NCCL_INCLUDE_DIR
# specify where nccl is installed
#
# NVTOOLSEXT_PATH (Windows only)
# specify where nvtoolsext is installed
#
# LIBRARY_PATH
# LD_LIBRARY_PATH
# we will search for libraries in these paths
from __future__ import print_function
from setuptools import setup, Extension, distutils, Command, find_packages
from distutils import dir_util
import setuptools.command.build_ext
import setuptools.command.install
import distutils.command.clean
import distutils.sysconfig
import filecmp
import platform
import subprocess
import shutil
import sys
import os
import json
import glob
import importlib
from tools.build_pytorch_libs import build_caffe2
from tools.setup_helpers.env import (IS_WINDOWS, IS_DARWIN, IS_LINUX,
check_env_flag,
DEBUG, REL_WITH_DEB_INFO, USE_MKLDNN)
from tools.setup_helpers.cuda import USE_CUDA, CUDA_HOME, CUDA_VERSION
from tools.setup_helpers.cudnn import USE_CUDNN, CUDNN_LIBRARY, CUDNN_INCLUDE_DIR
from tools.setup_helpers.rocm import USE_ROCM
from tools.setup_helpers.miopen import USE_MIOPEN, MIOPEN_LIBRARY, MIOPEN_INCLUDE_DIR
from tools.setup_helpers.nccl import USE_NCCL, USE_SYSTEM_NCCL, NCCL_SYSTEM_LIB, NCCL_INCLUDE_DIR
from tools.setup_helpers.dist_check import USE_DISTRIBUTED
################################################################################
# Parameters parsed from environment
################################################################################
VERBOSE_SCRIPT = True
RUN_BUILD_DEPS = True
# see if the user passed a quiet flag to setup.py arguments and respect
# that in our parts of the build
EMIT_BUILD_WARNING = False
RERUN_CMAKE = False
filtered_args = []
for i, arg in enumerate(sys.argv):
if arg == '--cmake':
RERUN_CMAKE = True
continue
if arg == 'rebuild' or arg == 'build':
arg = 'build' # rebuild is gone, make it build
EMIT_BUILD_WARNING = True
if arg == "--":
filtered_args += sys.argv[i:]
break
if arg == '-q' or arg == '--quiet':
VERBOSE_SCRIPT = False
if arg == 'clean':
RUN_BUILD_DEPS = False
filtered_args.append(arg)
sys.argv = filtered_args
if VERBOSE_SCRIPT:
def report(*args):
print(*args)
else:
def report(*args):
pass
# Constant known variables used throughout this file
cwd = os.path.dirname(os.path.abspath(__file__))
lib_path = os.path.join(cwd, "torch", "lib")
third_party_path = os.path.join(cwd, "third_party")
tmp_install_path = lib_path + "/tmp_install"
caffe2_build_dir = os.path.join(cwd, "build")
# lib/pythonx.x/site-packages
rel_site_packages = distutils.sysconfig.get_python_lib(prefix='')
# full absolute path to the dir above
full_site_packages = distutils.sysconfig.get_python_lib()
# CMAKE: full path to python library
if IS_WINDOWS:
cmake_python_library = "{}/libs/python{}.lib".format(
distutils.sysconfig.get_config_var("prefix"),
distutils.sysconfig.get_config_var("VERSION"))
else:
cmake_python_library = "{}/{}".format(
distutils.sysconfig.get_config_var("LIBDIR"),
distutils.sysconfig.get_config_var("INSTSONAME"))
cmake_python_include_dir = distutils.sysconfig.get_python_inc()
################################################################################
# Version, create_version_file, and package_name
################################################################################
package_name = os.getenv('TORCH_PACKAGE_NAME', 'torch')
version = '1.1.0a0'
if os.getenv('PYTORCH_BUILD_VERSION'):
assert os.getenv('PYTORCH_BUILD_NUMBER') is not None
build_number = int(os.getenv('PYTORCH_BUILD_NUMBER'))
version = os.getenv('PYTORCH_BUILD_VERSION')
if build_number > 1:
version += '.post' + str(build_number)
else:
try:
sha = subprocess.check_output(['git', 'rev-parse', 'HEAD'], cwd=cwd).decode('ascii').strip()
version += '+' + sha[:7]
except Exception:
pass
report("Building wheel {}-{}".format(package_name, version))
# all the work we need to do _before_ setup runs
def build_deps():
report('-- Building version ' + version)
version_path = os.path.join(cwd, 'torch', 'version.py')
with open(version_path, 'w') as f:
f.write("__version__ = '{}'\n".format(version))
# NB: This is not 100% accurate, because you could have built the
# library code with DEBUG, but csrc without DEBUG (in which case
# this would claim to be a release build when it's not.)
f.write("debug = {}\n".format(repr(DEBUG)))
f.write("cuda = {}\n".format(repr(CUDA_VERSION)))
def check_file(f):
if not os.path.exists(f):
report("Could not find {}".format(f))
report("Did you run 'git submodule update --init --recursive'?")
sys.exit(1)
check_file(os.path.join(third_party_path, "gloo", "CMakeLists.txt"))
check_file(os.path.join(third_party_path, "pybind11", "CMakeLists.txt"))
check_file(os.path.join(third_party_path, 'cpuinfo', 'CMakeLists.txt'))
check_file(os.path.join(third_party_path, 'onnx', 'CMakeLists.txt'))
check_file(os.path.join(third_party_path, 'QNNPACK', 'CMakeLists.txt'))
check_file(os.path.join(third_party_path, 'fbgemm', 'CMakeLists.txt'))
check_pydep('yaml', 'pyyaml')
check_pydep('typing', 'typing')
build_caffe2(version=version,
cmake_python_library=cmake_python_library,
build_python=True,
rerun_cmake=RERUN_CMAKE,
build_dir='build')
# Use copies instead of symbolic files.
# Windows has very poor support for them.
sym_files = ['tools/shared/cwrap_common.py', 'tools/shared/_utils_internal.py']
orig_files = ['aten/src/ATen/common_with_cwrap.py', 'torch/_utils_internal.py']
for sym_file, orig_file in zip(sym_files, orig_files):
same = False
if os.path.exists(sym_file):
if filecmp.cmp(sym_file, orig_file):
same = True
else:
os.remove(sym_file)
if not same:
shutil.copyfile(orig_file, sym_file)
dir_util.copy_tree('torch/lib/tmp_install/share', 'torch/share')
dir_util.copy_tree('third_party/pybind11/include/pybind11/',
'torch/lib/include/pybind11')
################################################################################
# Building dependent libraries
################################################################################
missing_pydep = '''
Missing build dependency: Unable to `import {importname}`.
Please install it via `conda install {module}` or `pip install {module}`
'''.strip()
def check_pydep(importname, module):
try:
importlib.import_module(importname)
except ImportError:
raise RuntimeError(missing_pydep.format(importname=importname, module=module))
class build_ext(setuptools.command.build_ext.build_ext):
def run(self):
# report build options
if USE_NUMPY:
report('-- Building with NumPy bindings')
else:
report('-- NumPy not found')
if USE_CUDNN:
report('-- Detected cuDNN at ' + CUDNN_LIBRARY + ', ' + CUDNN_INCLUDE_DIR)
else:
report('-- Not using cuDNN')
if USE_MIOPEN:
report('-- Detected MIOpen at ' + MIOPEN_LIBRARY + ', ' + MIOPEN_INCLUDE_DIR)
else:
report('-- Not using MIOpen')
if USE_CUDA:
report('-- Detected CUDA at ' + CUDA_HOME)
else:
report('-- Not using CUDA')
if USE_MKLDNN:
report('-- Using MKLDNN')
else:
report('-- Not using MKLDNN')
if USE_NCCL and USE_SYSTEM_NCCL:
report('-- Using system provided NCCL library at ' + NCCL_SYSTEM_LIB + ', ' + NCCL_INCLUDE_DIR)
elif USE_NCCL:
report('-- Building NCCL library')
else:
report('-- Not using NCCL')
if USE_DISTRIBUTED:
report('-- Building with THD distributed package ')
if IS_LINUX:
report('-- Building with c10d distributed package ')
else:
report('-- Building without c10d distributed package')
else:
report('-- Building without distributed package')
# It's an old-style class in Python 2.7...
setuptools.command.build_ext.build_ext.run(self)
# Copy the essential export library to compile C++ extensions.
if IS_WINDOWS:
build_temp = self.build_temp
ext_filename = self.get_ext_filename('_C')
lib_filename = '.'.join(ext_filename.split('.')[:-1]) + '.lib'
export_lib = os.path.join(
build_temp, 'torch', 'csrc', lib_filename).replace('\\', '/')
build_lib = self.build_lib
target_lib = os.path.join(
build_lib, 'torch', 'lib', '_C.lib').replace('\\', '/')
self.copy_file(export_lib, target_lib)
def build_extensions(self):
self.create_compile_commands()
# The caffe2 extensions are created in
# tmp_install/lib/pythonM.m/site-packages/caffe2/python/
# and need to be copied to build/lib.linux.... , which will be a
# platform dependent build folder created by the "build" command of
# setuptools. Only the contents of this folder are installed in the
# "install" command by default.
# We only make this copy for Caffe2's pybind extensions
caffe2_pybind_exts = [
'caffe2.python.caffe2_pybind11_state',
'caffe2.python.caffe2_pybind11_state_gpu',
'caffe2.python.caffe2_pybind11_state_hip',
]
i = 0
while i < len(self.extensions):
ext = self.extensions[i]
if ext.name not in caffe2_pybind_exts:
i += 1
continue
fullname = self.get_ext_fullname(ext.name)
filename = self.get_ext_filename(fullname)
report("\nCopying extension {}".format(ext.name))
src = os.path.join(tmp_install_path, rel_site_packages, filename)
if not os.path.exists(src):
report("{} does not exist".format(src))
del self.extensions[i]
else:
dst = os.path.join(os.path.realpath(self.build_lib), filename)
report("Copying {} from {} to {}".format(ext.name, src, dst))
dst_dir = os.path.dirname(dst)
if not os.path.exists(dst_dir):
os.makedirs(dst_dir)
self.copy_file(src, dst)
i += 1
distutils.command.build_ext.build_ext.build_extensions(self)
def get_outputs(self):
outputs = distutils.command.build_ext.build_ext.get_outputs(self)
outputs.append(os.path.join(self.build_lib, "caffe2"))
report("setup.py::get_outputs returning {}".format(outputs))
return outputs
def create_compile_commands(self):
def load(filename):
with open(filename) as f:
return json.load(f)
ninja_files = glob.glob('build/*compile_commands.json')
cmake_files = glob.glob('torch/lib/build/*/compile_commands.json')
all_commands = [entry
for f in ninja_files + cmake_files
for entry in load(f)]
# cquery does not like c++ compiles that start with gcc.
# It forgets to include the c++ header directories.
# We can work around this by replacing the gcc calls that python
# setup.py generates with g++ calls instead
for command in all_commands:
if command['command'].startswith("gcc "):
command['command'] = "g++ " + command['command'][4:]
new_contents = json.dumps(all_commands, indent=2)
contents = ''
if os.path.exists('compile_commands.json'):
with open('compile_commands.json', 'r') as f:
contents = f.read()
if contents != new_contents:
with open('compile_commands.json', 'w') as f:
f.write(new_contents)
class install(setuptools.command.install.install):
def run(self):
setuptools.command.install.install.run(self)
class clean(distutils.command.clean.clean):
def run(self):
import glob
import re
with open('.gitignore', 'r') as f:
ignores = f.read()
pat = re.compile(r'^#( BEGIN NOT-CLEAN-FILES )?')
for wildcard in filter(None, ignores.split('\n')):
match = pat.match(wildcard)
if match:
if match.group(1):
# Marker is found and stop reading .gitignore.
break
# Ignore lines which begin with '#'.
else:
for filename in glob.glob(wildcard):
try:
os.remove(filename)
except OSError:
shutil.rmtree(filename, ignore_errors=True)
# It's an old-style class in Python 2.7...
distutils.command.clean.clean.run(self)
################################################################################
# Configure compile flags
################################################################################
library_dirs = []
if IS_WINDOWS:
# /NODEFAULTLIB makes sure we only link to DLL runtime
# and matches the flags set for protobuf and ONNX
extra_link_args = ['/NODEFAULTLIB:LIBCMT.LIB']
# /MD links against DLL runtime
# and matches the flags set for protobuf and ONNX
# /Z7 turns on symbolic debugging information in .obj files
# /EHa is about native C++ catch support for asynchronous
# structured exception handling (SEH)
# /DNOMINMAX removes builtin min/max functions
# /wdXXXX disables warning no. XXXX
extra_compile_args = ['/MD', '/Z7',
'/EHa', '/DNOMINMAX',
'/wd4267', '/wd4251', '/wd4522', '/wd4522', '/wd4838',
'/wd4305', '/wd4244', '/wd4190', '/wd4101', '/wd4996',
'/wd4275']
if sys.version_info[0] == 2:
if not check_env_flag('FORCE_PY27_BUILD'):
report('The support for PyTorch with Python 2.7 on Windows is very experimental.')
report('Please set the flag `FORCE_PY27_BUILD` to 1 to continue build.')
sys.exit(1)
# /bigobj increases number of sections in .obj file, which is needed to link
# against libaries in Python 2.7 under Windows
extra_compile_args.append('/bigobj')
else:
extra_link_args = []
extra_compile_args = [
'-std=c++11',
'-Wall',
'-Wextra',
'-Wno-strict-overflow',
'-Wno-unused-parameter',
'-Wno-missing-field-initializers',
'-Wno-write-strings',
'-Wno-unknown-pragmas',
# This is required for Python 2 declarations that are deprecated in 3.
'-Wno-deprecated-declarations',
# Python 2.6 requires -fno-strict-aliasing, see
# http://legacy.python.org/dev/peps/pep-3123/
# We also depend on it in our code (even Python 3).
'-fno-strict-aliasing',
# Clang has an unfixed bug leading to spurious missing
# braces warnings, see
# https://bugs.llvm.org/show_bug.cgi?id=21629
'-Wno-missing-braces',
]
if check_env_flag('WERROR'):
extra_compile_args.append('-Werror')
library_dirs.append(lib_path)
# we specify exact lib names to avoid conflict with lua-torch installs
CAFFE2_LIBS = []
if USE_CUDA:
CAFFE2_LIBS.extend(['-Wl,--no-as-needed', os.path.join(lib_path, 'libcaffe2_gpu.so'), '-Wl,--as-needed'])
if USE_ROCM:
CAFFE2_LIBS.extend(['-Wl,--no-as-needed', os.path.join(lib_path, 'libcaffe2_hip.so'), '-Wl,--as-needed'])
# static library only
if IS_DARWIN:
CAFFE2_LIBS = []
if USE_CUDA:
CAFFE2_LIBS.append(os.path.join(lib_path, 'libcaffe2_gpu.dylib'))
if USE_ROCM:
CAFFE2_LIBS.append(os.path.join(lib_path, 'libcaffe2_hip.dylib'))
if IS_WINDOWS:
CAFFE2_LIBS = []
if USE_CUDA:
CAFFE2_LIBS.append(os.path.join(lib_path, 'caffe2_gpu.lib'))
if USE_ROCM:
CAFFE2_LIBS.append(os.path.join(lib_path, 'caffe2_hip.lib'))
main_compile_args = []
main_libraries = ['shm', 'torch_python']
main_link_args = []
main_sources = ["torch/csrc/stub.cpp"]
# Before the introduction of stub.cpp, _C.so and libcaffe2.so defined
# some of the same symbols, and it was important for _C.so to be
# loaded before libcaffe2.so so that the versions in _C.so got
# used. This happened automatically because we loaded _C.so directly,
# and libcaffe2.so was brought in as a dependency (though I suspect it
# may have been possible to break by importing caffe2 first in the
# same process).
#
# Now, libtorch_python.so and libcaffe2.so define some of the same
# symbols. We directly load the _C.so stub, which brings both of these
# in as dependencies. We have to make sure that symbols continue to be
# looked up in libtorch_python.so first, by making sure it comes
# before libcaffe2.so in the linker command.
main_link_args.extend(CAFFE2_LIBS)
try:
import numpy as np
NUMPY_INCLUDE_DIR = np.get_include()
USE_NUMPY = True
except ImportError:
USE_NUMPY = False
if USE_CUDA:
if IS_WINDOWS:
cuda_lib_path = CUDA_HOME + '/lib/x64/'
else:
cuda_lib_dirs = ['lib64', 'lib']
for lib_dir in cuda_lib_dirs:
cuda_lib_path = os.path.join(CUDA_HOME, lib_dir)
if os.path.exists(cuda_lib_path):
break
library_dirs.append(cuda_lib_path)
if DEBUG:
if IS_WINDOWS:
extra_link_args.append('/DEBUG:FULL')
else:
extra_compile_args += ['-O0', '-g']
extra_link_args += ['-O0', '-g']
if REL_WITH_DEB_INFO:
if IS_WINDOWS:
extra_link_args.append('/DEBUG:FULL')
else:
extra_compile_args += ['-g']
extra_link_args += ['-g']
def make_relative_rpath(path):
if IS_DARWIN:
return '-Wl,-rpath,@loader_path/' + path
elif IS_WINDOWS:
return ''
else:
return '-Wl,-rpath,$ORIGIN/' + path
################################################################################
# Declare extensions and package
################################################################################
extensions = []
packages = find_packages(exclude=('tools', 'tools.*'))
C = Extension("torch._C",
libraries=main_libraries,
sources=main_sources,
language='c++',
extra_compile_args=main_compile_args + extra_compile_args,
include_dirs=[],
library_dirs=library_dirs,
extra_link_args=extra_link_args + main_link_args + [make_relative_rpath('lib')],
)
extensions.append(C)
if not IS_WINDOWS:
DL = Extension("torch._dl",
sources=["torch/csrc/dl.c"],
language='c'
)
extensions.append(DL)
if USE_CUDA:
thnvrtc_link_flags = extra_link_args + [make_relative_rpath('lib')]
if IS_LINUX:
thnvrtc_link_flags = thnvrtc_link_flags + ['-Wl,--no-as-needed']
# these have to be specified as -lcuda in link_flags because they
# have to come right after the `no-as-needed` option
if IS_WINDOWS:
thnvrtc_link_flags += ['cuda.lib', 'nvrtc.lib']
else:
thnvrtc_link_flags += ['-lcuda', '-lnvrtc']
cuda_stub_path = [cuda_lib_path + '/stubs']
if IS_DARWIN:
# on macOS this is where the CUDA stub is installed according to the manual
cuda_stub_path = ["/usr/local/cuda/lib"]
THNVRTC = Extension("torch._nvrtc",
sources=['torch/csrc/nvrtc.cpp'],
language='c++',
extra_compile_args=main_compile_args + extra_compile_args,
include_dirs=[cwd],
library_dirs=library_dirs + cuda_stub_path,
extra_link_args=thnvrtc_link_flags,
)
extensions.append(THNVRTC)
# These extensions are built by cmake and copied manually in build_extensions()
# inside the build_ext implementaiton
extensions.append(
Extension(
name=str('caffe2.python.caffe2_pybind11_state'),
sources=[]),
)
if USE_CUDA:
extensions.append(
Extension(
name=str('caffe2.python.caffe2_pybind11_state_gpu'),
sources=[]),
)
if USE_ROCM:
extensions.append(
Extension(
name=str('caffe2.python.caffe2_pybind11_state_hip'),
sources=[]),
)
cmdclass = {
'build_ext': build_ext,
'clean': clean,
'install': install,
}
entry_points = {
'console_scripts': [
'convert-caffe2-to-onnx = caffe2.python.onnx.bin.conversion:caffe2_to_onnx',
'convert-onnx-to-caffe2 = caffe2.python.onnx.bin.conversion:onnx_to_caffe2',
]
}
# post run, warnings, printed at the end to make them more visible
build_update_message = """
It is no longer necessary to use the 'build' or 'rebuild' targets
To install:
$ python setup.py install
To develop locally:
$ python setup.py develop
To force cmake to re-run (off by default):
$ python setup.py develop --cmake
"""
def print_box(msg):
lines = msg.split('\n')
size = max(len(l) + 1 for l in lines)
print('-' * (size + 2))
for l in lines:
print('|{}{}|'.format(l, ' ' * (size - len(l))))
print('-' * (size + 2))
if __name__ == '__main__':
if RUN_BUILD_DEPS:
build_deps()
setup(
name=package_name,
version=version,
description=("Tensors and Dynamic neural networks in "
"Python with strong GPU acceleration"),
ext_modules=extensions,
cmdclass=cmdclass,
packages=packages,
entry_points=entry_points,
package_data={
'torch': [
'lib/*.so*',
'lib/*.dylib*',
'lib/*.dll',
'lib/*.lib',
'lib/*.pdb',
'lib/torch_shm_manager',
'lib/*.h',
'lib/include/ATen/*.h',
'lib/include/ATen/cpu/*.h',
'lib/include/ATen/core/*.h',
'lib/include/ATen/cuda/*.cuh',
'lib/include/ATen/cuda/*.h',
'lib/include/ATen/cuda/detail/*.cuh',
'lib/include/ATen/cuda/detail/*.h',
'lib/include/ATen/cudnn/*.h',
'lib/include/ATen/detail/*.h',
'lib/include/caffe2/utils/*.h',
'lib/include/c10/*.h',
'lib/include/c10/macros/*.h',
'lib/include/c10/core/*.h',
'lib/include/ATen/core/dispatch/*.h',
'lib/include/c10/core/impl/*.h',
'lib/include/ATen/core/opschema/*.h',
'lib/include/c10/util/*.h',
'lib/include/c10/cuda/*.h',
'lib/include/c10/cuda/impl/*.h',
'lib/include/c10/hip/*.h',
'lib/include/c10/hip/impl/*.h',
'lib/include/caffe2/**/*.h',
'lib/include/torch/*.h',
'lib/include/torch/csrc/*.h',
'lib/include/torch/csrc/api/include/torch/*.h',
'lib/include/torch/csrc/api/include/torch/data/*.h',
'lib/include/torch/csrc/api/include/torch/data/dataloader/*.h',
'lib/include/torch/csrc/api/include/torch/data/datasets/*.h',
'lib/include/torch/csrc/api/include/torch/data/detail/*.h',
'lib/include/torch/csrc/api/include/torch/data/samplers/*.h',
'lib/include/torch/csrc/api/include/torch/data/transforms/*.h',
'lib/include/torch/csrc/api/include/torch/detail/*.h',
'lib/include/torch/csrc/api/include/torch/detail/ordered_dict.h',
'lib/include/torch/csrc/api/include/torch/nn/*.h',
'lib/include/torch/csrc/api/include/torch/nn/modules/*.h',
'lib/include/torch/csrc/api/include/torch/nn/parallel/*.h',
'lib/include/torch/csrc/api/include/torch/optim/*.h',
'lib/include/torch/csrc/api/include/torch/serialize/*.h',
'lib/include/torch/csrc/autograd/*.h',
'lib/include/torch/csrc/autograd/generated/*.h',
'lib/include/torch/csrc/cuda/*.h',
'lib/include/torch/csrc/jit/*.h',
'lib/include/torch/csrc/jit/generated/*.h',
'lib/include/torch/csrc/jit/passes/*.h',
'lib/include/torch/csrc/jit/script/*.h',
'lib/include/torch/csrc/utils/*.h',
'lib/include/pybind11/*.h',
'lib/include/pybind11/detail/*.h',
'lib/include/TH/*.h*',
'lib/include/TH/generic/*.h*',
'lib/include/THC/*.cuh',
'lib/include/THC/*.h*',
'lib/include/THC/generic/*.h',
'lib/include/THCUNN/*.cuh',
'lib/include/THNN/*.h',
'share/cmake/ATen/*.cmake',
'share/cmake/Caffe2/*.cmake',
'share/cmake/Caffe2/public/*.cmake',
'share/cmake/Caffe2/Modules_CUDA_fix/*.cmake',
'share/cmake/Caffe2/Modules_CUDA_fix/upstream/*.cmake',
'share/cmake/Caffe2/Modules_CUDA_fix/upstream/FindCUDA/*.cmake',
'share/cmake/Gloo/*.cmake',
'share/cmake/Torch/*.cmake',
],
'caffe2': [
'cpp_test/*',
'python/serialized_test/data/operator_test/*.zip',
]
},
)
if EMIT_BUILD_WARNING:
print_box(build_update_message)
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