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_LIBRARY + ', ' +
CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_MKLDNN:
print('-- Detected MKLDNN at ' + MKLDNN_LIBRARY + ', ' +
MKLDNN_INCLUDE_DIR)
else:
print('-- Not using MKLDNN')
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 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)
# 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 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 not os.path.exists("torch/csrc/generated"):
os.mkdir("torch/csrc/generated")
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)
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_LIBRARY + ', ' + CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_MKLDNN:
print('-- Detected MKLDNN at ' + MKLDNN_LIBRARY + ', ' + MKLDNN_INCLUDE_DIR)
else:
print('-- Not using MKLDNN')
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 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)
# 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 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_LIBRARY + ', ' + 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 not os.path.exists("torch/csrc/generated"):
os.mkdir("torch/csrc/generated")
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)
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_LIBRARY + ', ' +
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')
# Copy headers necessary to compile C++ extensions.
self.copy_tree('torch/csrc', 'torch/lib/include/torch/csrc/')
self.copy_tree('torch/lib/pybind11/include/pybind11/',
'torch/lib/include/pybind11')
self.copy_file('torch/torch.h', 'torch/lib/include/torch/torch.h')
generate_code(ninja_global)
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)
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_LIBRARY + ', ' +
CUDNN_INCLUDE_DIR)
else:
print('-- Not using cuDNN')
if WITH_CUDA:
print('-- Detected CUDA at ' + CUDA_HOME)
else:
print('-- Not using CUDA')
if WITH_MKLDNN:
print('-- Detected MKLDNN at ' + MKLDNN_LIBRARY + ', ' +
MKLDNN_INCLUDE_DIR)
else:
print('-- Not using MKLDNN')
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 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)
