def run(self):
# cwrap depends on pyyaml, so we can't import it earlier
from tools.cwrap import cwrap
from tools.cwrap.plugins.THPPlugin import THPPlugin
from tools.cwrap.plugins.ArgcountSortPlugin import ArgcountSortPlugin
from tools.cwrap.plugins.AutoGPU import AutoGPU
from tools.cwrap.plugins.BoolOption import BoolOption
from tools.cwrap.plugins.KwargsPlugin import KwargsPlugin
from tools.cwrap.plugins.NullableArguments import NullableArguments
from tools.cwrap.plugins.CuDNNPlugin import CuDNNPlugin
cwrap('torch/csrc/generic/TensorMethods.cwrap', plugins=[
BoolOption(), THPPlugin(), AutoGPU(condition='IS_CUDA'),
ArgcountSortPlugin(), KwargsPlugin(),
])
cwrap('torch/csrc/cudnn/cuDNN.cwrap', plugins=[
CuDNNPlugin(), NullableArguments()
])
# It's an old-style class in Python 2.7...
setuptools.command.build_ext.build_ext.run(self)
python类build_ext()的实例源码
def run(self):
self.run_command('build_py')
self.run_command('build_ext')
def run(self):
self.run_command('build_py')
self.run_command('build_ext')
def run(self):
# Print build options
if WITH_NUMPY:
print('-- Building with NumPy bindings')
else:
print('-- NumPy not found')
if WITH_CUDNN:
print('-- Detected cuDNN at ' + CUDNN_LIB_DIR + ', ' + CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_NCCL and SYSTEM_NCCL:
print('-- Using system provided NCCL library')
elif WITH_NCCL:
print('-- Building NCCL library')
else:
print('-- Not using NCCL')
# cwrap depends on pyyaml, so we can't import it earlier
from tools.cwrap import cwrap
from tools.cwrap.plugins.THPPlugin import THPPlugin
from tools.cwrap.plugins.ArgcountSortPlugin import ArgcountSortPlugin
from tools.cwrap.plugins.AutoGPU import AutoGPU
from tools.cwrap.plugins.BoolOption import BoolOption
from tools.cwrap.plugins.KwargsPlugin import KwargsPlugin
from tools.cwrap.plugins.NullableArguments import NullableArguments
from tools.cwrap.plugins.CuDNNPlugin import CuDNNPlugin
from tools.cwrap.plugins.WrapDim import WrapDim
thp_plugin = THPPlugin()
cwrap('torch/csrc/generic/TensorMethods.cwrap', plugins=[
BoolOption(), thp_plugin, AutoGPU(condition='IS_CUDA'),
ArgcountSortPlugin(), KwargsPlugin(), WrapDim()
])
cwrap('torch/csrc/cudnn/cuDNN.cwrap', plugins=[
CuDNNPlugin(), NullableArguments()
])
# It's an old-style class in Python 2.7...
setuptools.command.build_ext.build_ext.run(self)
def install(self):
self.build_dir = 'build/lib'
setuptools.command.install_lib.install_lib.install(self)
################################################################################
# Setup pykaldi
################################################################################
# We add a 'dummy' extension so that setuptools runs the build_ext step.
def run(self):
self.run_command('build_py')
self.run_command('build_ext')
def run(self):
# Print build options
if WITH_NUMPY:
print('-- Building with NumPy bindings')
else:
print('-- NumPy not found')
if WITH_CUDNN:
print('-- Detected cuDNN at ' + CUDNN_LIB_DIR + ', ' + CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_NCCL and SYSTEM_NCCL:
print('-- Using system provided NCCL library')
elif WITH_NCCL:
print('-- Building NCCL library')
else:
print('-- Not using NCCL')
# cwrap depends on pyyaml, so we can't import it earlier
from tools.cwrap import cwrap
from tools.cwrap.plugins.THPPlugin import THPPlugin
from tools.cwrap.plugins.ArgcountSortPlugin import ArgcountSortPlugin
from tools.cwrap.plugins.AutoGPU import AutoGPU
from tools.cwrap.plugins.BoolOption import BoolOption
from tools.cwrap.plugins.KwargsPlugin import KwargsPlugin
from tools.cwrap.plugins.NullableArguments import NullableArguments
from tools.cwrap.plugins.CuDNNPlugin import CuDNNPlugin
from tools.cwrap.plugins.WrapDim import WrapDim
thp_plugin = THPPlugin()
cwrap('torch/csrc/generic/TensorMethods.cwrap', plugins=[
BoolOption(), thp_plugin, AutoGPU(condition='IS_CUDA'),
ArgcountSortPlugin(), KwargsPlugin(), WrapDim()
])
cwrap('torch/csrc/cudnn/cuDNN.cwrap', plugins=[
CuDNNPlugin(), NullableArguments()
])
# It's an old-style class in Python 2.7...
setuptools.command.build_ext.build_ext.run(self)
def __init__(self, *args, **kwargs):
setuptools.command.build_ext.build_ext.__init__(self, *args, **kwargs)
self.journal_file = os.environ.get(JOURNAL_ENV)
self.commands = []
def run(self):
self.set_f90_compiler()
self.start_journaling()
self.compile_fortran_obj_files()
result = setuptools.command.build_ext.build_ext.run(self)
self.save_journal()
self.cleanup()
return result
def run(self):
self.run_command('build_py')
self.run_command('build_ext')
def __init__(self, libdest, *args, **kwargs):
self.libdest = libdest
setuptools.Extension.__init__(self, *args, **kwargs)
# Subclass setuptools build_ext to put the compiled shared library in the
# appropriate place in the source tree.
def run(self):
self.run_command('build_py')
self.run_command('build_ext')
def run(self):
# Print build options
if WITH_NUMPY:
print('-- Building with NumPy bindings')
else:
print('-- NumPy not found')
if WITH_CUDNN:
print('-- Detected cuDNN at ' + CUDNN_LIB_DIR + ', ' + CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_NCCL and WITH_SYSTEM_NCCL:
print('-- Using system provided NCCL library at ' +
NCCL_LIB_DIR + ', ' + NCCL_INCLUDE_DIR)
elif WITH_NCCL:
print('-- Building NCCL library')
else:
print('-- Not using NCCL')
if WITH_DISTRIBUTED:
print('-- Building with distributed package ')
monkey_patch_THD_link_flags()
else:
print('-- Building without distributed package')
# cwrap depends on pyyaml, so we can't import it earlier
from tools.cwrap import cwrap
from tools.cwrap.plugins.THPPlugin import THPPlugin
from tools.cwrap.plugins.ArgcountSortPlugin import ArgcountSortPlugin
from tools.cwrap.plugins.AutoGPU import AutoGPU
from tools.cwrap.plugins.BoolOption import BoolOption
from tools.cwrap.plugins.KwargsPlugin import KwargsPlugin
from tools.cwrap.plugins.NullableArguments import NullableArguments
from tools.cwrap.plugins.CuDNNPlugin import CuDNNPlugin
from tools.cwrap.plugins.WrapDim import WrapDim
from tools.cwrap.plugins.AssertNDim import AssertNDim
from tools.cwrap.plugins.Broadcast import Broadcast
from tools.cwrap.plugins.ProcessorSpecificPlugin import ProcessorSpecificPlugin
from tools.autograd.gen_variable_type import gen_variable_type
thp_plugin = THPPlugin()
cwrap('torch/csrc/generic/TensorMethods.cwrap', plugins=[
ProcessorSpecificPlugin(), BoolOption(), thp_plugin,
AutoGPU(condition='IS_CUDA'), ArgcountSortPlugin(), KwargsPlugin(),
AssertNDim(), WrapDim(), Broadcast()
])
cwrap('torch/csrc/cudnn/cuDNN.cwrap', plugins=[
CuDNNPlugin(), NullableArguments()
])
# Build ATen based Variable classes
autograd_gen_dir = 'torch/csrc/autograd/generated'
if not os.path.exists(autograd_gen_dir):
os.mkdir(autograd_gen_dir)
gen_variable_type(
'torch/lib/build/ATen/ATen/Declarations.yaml',
autograd_gen_dir)
# It's an old-style class in Python 2.7...
setuptools.command.build_ext.build_ext.run(self)
def run(self):
# Print build options
if WITH_NUMPY:
print('-- Building with NumPy bindings')
else:
print('-- NumPy not found')
if WITH_CUDNN:
print('-- Detected cuDNN at ' + CUDNN_LIB_DIR + ', ' + CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_NCCL and WITH_SYSTEM_NCCL:
print('-- Using system provided NCCL library at ' +
NCCL_SYSTEM_LIB + ', ' + NCCL_INCLUDE_DIR)
elif WITH_NCCL:
print('-- Building NCCL library')
else:
print('-- Not using NCCL')
if WITH_DISTRIBUTED:
print('-- Building with distributed package ')
monkey_patch_THD_link_flags()
else:
print('-- Building without distributed package')
generate_code(ninja_global)
if IS_WINDOWS:
build_temp = self.build_temp
build_dir = 'torch/csrc'
ext_filename = self.get_ext_filename('_C')
lib_filename = '.'.join(ext_filename.split('.')[:-1]) + '.lib'
_C_LIB = os.path.join(build_temp, build_dir, lib_filename).replace('\\', '/')
THNN.extra_link_args += [_C_LIB]
if WITH_CUDA:
THCUNN.extra_link_args += [_C_LIB]
else:
# To generate .obj files for AutoGPU for the export class
# a header file cannot build, so it has to be copied to someplace as a source file
if os.path.exists("torch/csrc/generated/AutoGPU_cpu_win.cpp"):
os.remove("torch/csrc/generated/AutoGPU_cpu_win.cpp")
shutil.copyfile("torch/csrc/cuda/AutoGPU.h", "torch/csrc/generated/AutoGPU_cpu_win.cpp")
if WITH_NINJA:
# before we start the normal build make sure all generated code
# gets built
ninja_global.run()
# It's an old-style class in Python 2.7...
setuptools.command.build_ext.build_ext.run(self)
