# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import six import copy import re import setuptools from setuptools.command.easy_install import easy_install from setuptools.command.build_ext import build_ext from distutils.command.build import build from .extension_utils import ( find_cuda_home, find_rocm_home, normalize_extension_kwargs, add_compile_flag, run_cmd, ) from .extension_utils import ( is_cuda_file, prepare_unix_cudaflags, prepare_win_cudaflags, ) from .extension_utils import ( _import_module_from_library, _write_setup_file, _jit_compile, ) from .extension_utils import ( check_abi_compatibility, log_v, CustomOpInfo, parse_op_name_from, ) from .extension_utils import ( clean_object_if_change_cflags, _reset_so_rpath, _get_fluid_path, ) from .extension_utils import ( bootstrap_context, get_build_directory, add_std_without_repeat, ) from .extension_utils import ( IS_WINDOWS, OS_NAME, MSVC_COMPILE_FLAGS, MSVC_COMPILE_FLAGS, ) from .extension_utils import CLANG_COMPILE_FLAGS, CLANG_LINK_FLAGS from ...fluid import core # Note(zhouwei): On windows, it will export function 'PyInit_[name]' by default, # The solution is: 1.User add function PyInit_[name] 2. set not to export # refer to https://stackoverflow.com/questions/34689210/error-exporting-symbol-when-building-python-c-extension-in-windows if IS_WINDOWS and six.PY3: from distutils.command.build_ext import build_ext as _du_build_ext from unittest.mock import Mock _du_build_ext.get_export_symbols = Mock(return_value=None) CUDA_HOME = find_cuda_home() if core.is_compiled_with_rocm(): ROCM_HOME = find_rocm_home() CUDA_HOME = ROCM_HOME def setup(**attr): """ The interface is used to config the process of compiling customized operators, mainly includes how to compile shared library, automatically generate python API and install it into site-package. It supports using customized operators directly with ``import`` statement. It encapsulates the python built-in ``setuptools.setup`` function and keeps arguments and usage same as the native interface. Meanwhile, it hiddens Paddle inner framework concepts, such as necessary compiling flags, included paths of head files, and linking flags. It also will automatically search and valid local environment and versions of ``cc(Linux)`` , ``cl.exe(Windows)`` and ``nvcc`` , then compiles customized operators supporting CPU or GPU device according to the specified Extension type. Moreover, `ABI compatibility `_ will be checked to ensure that compiler version from ``cc(Linux)`` , ``cl.exe(Windows)`` on local machine is compatible with pre-installed Paddle whl in python site-packages. For Linux, GCC version will be checked . For example if Paddle with CUDA 10.1 is built with GCC 8.2, then the version of user's local machine should satisfy GCC >= 8.2. For Windows, Visual Studio version will be checked, and it should be greater than or equal to that of PaddlePaddle (Visual Studio 2017). If the above conditions are not met, the corresponding warning will be printed, and a fatal error may occur because of ABI compatibility. Note: 1. Currently we support Linux, MacOS and Windows platfrom. 2. On Linux platform, we recommend to use GCC 8.2 as soft linking condidate of ``/usr/bin/cc`` . Then, Use ``which cc`` to ensure location of ``cc`` and using ``cc --version`` to ensure linking GCC version. 3. On Windows platform, we recommend to install `` Visual Studio`` (>=2017). Compared with Just-In-Time ``load`` interface, it only compiles once by executing ``python setup.py install`` . Then customized operators API will be available everywhere after importing it. A simple example of ``setup.py`` as followed: .. code-block:: text # setup.py # Case 1: Compiling customized operators supporting CPU and GPU devices from paddle.utils.cpp_extension import CUDAExtension, setup setup( name='custom_op', # name of package used by "import" ext_modules=CUDAExtension( sources=['relu_op.cc', 'relu_op.cu', 'tanh_op.cc', 'tanh_op.cu'] # Support for compilation of multiple OPs ) ) # Case 2: Compiling customized operators supporting only CPU device from paddle.utils.cpp_extension import CppExtension, setup setup( name='custom_op', # name of package used by "import" ext_modules=CppExtension( sources=['relu_op.cc', 'tanh_op.cc'] # Support for compilation of multiple OPs ) ) Applying compilation and installation by executing ``python setup.py install`` under source files directory. Then we can use the layer api as followed: .. code-block:: text import paddle from custom_op import relu, tanh x = paddle.randn([4, 10], dtype='float32') relu_out = relu(x) tanh_out = tanh(x) Args: name(str): Specify the name of shared library file and installed python package. ext_modules(Extension): Specify the Extension instance including customized operator source files, compiling flags et.al. If only compile operator supporting CPU device, please use ``CppExtension`` ; If compile operator supporting CPU and GPU devices, please use ``CUDAExtension`` . include_dirs(list[str], optional): Specify the extra include directories to search head files. The interface will automatically add ``site-package/paddle/include`` . Please add the corresponding directory path if including third-party head files. Default is None. extra_compile_args(list[str] | dict, optional): Specify the extra compiling flags such as ``-O3`` . If set ``list[str]`` , all these flags will be applied for ``cc`` and ``nvcc`` compiler. It support specify flags only applied ``cc`` or ``nvcc`` compiler using dict type with ``{'cxx': [...], 'nvcc': [...]}`` . Default is None. **attr(dict, optional): Specify other arguments same as ``setuptools.setup`` . Returns: None """ cmdclass = attr.get('cmdclass', {}) assert isinstance(cmdclass, dict) # if not specific cmdclass in setup, add it automatically. if 'build_ext' not in cmdclass: cmdclass['build_ext'] = BuildExtension.with_options( no_python_abi_suffix=True ) attr['cmdclass'] = cmdclass error_msg = """ Required to specific `name` argument in paddle.utils.cpp_extension.setup. It's used as `import XXX` when you want install and import your custom operators.\n For Example: # setup.py file from paddle.utils.cpp_extension import CUDAExtension, setup setup(name='custom_module', ext_modules=CUDAExtension( sources=['relu_op.cc', 'relu_op.cu']) # After running `python setup.py install` from custom_module import relu """ # name argument is required if 'name' not in attr: raise ValueError(error_msg) assert not attr['name'].endswith( 'module' ), "Please don't use 'module' as suffix in `name` argument, " "it will be stripped in setuptools.bdist_egg and cause import error." ext_modules = attr.get('ext_modules', []) if not isinstance(ext_modules, list): ext_modules = [ext_modules] assert ( len(ext_modules) == 1 ), "Required only one Extension, but received {}. If you want to compile multi operators, you can include all necessary source files in one Extension.".format( len(ext_modules) ) # replace Extension.name with attr['name] to keep consistant with Package name. for ext_module in ext_modules: ext_module.name = attr['name'] attr['ext_modules'] = ext_modules # Add rename .so hook in easy_install assert 'easy_install' not in cmdclass cmdclass['easy_install'] = EasyInstallCommand # Note(Aurelius84): Add rename build_base directory hook in build command. # To avoid using same build directory that will lead to remove the directory # by mistake while parallelling execute setup.py, for example on CI. assert 'build' not in cmdclass build_base = os.path.join('build', attr['name']) cmdclass['build'] = BuildCommand.with_options(build_base=build_base) # Always set zip_safe=False to make compatible in PY2 and PY3 # See http://peak.telecommunity.com/DevCenter/setuptools#setting-the-zip-safe-flag attr['zip_safe'] = False # switch `write_stub` to inject paddle api in .egg with bootstrap_context(): setuptools.setup(**attr) def CppExtension(sources, *args, **kwargs): """ The interface is used to config source files of customized operators and complies Op Kernel only supporting CPU device. Please use ``CUDAExtension`` if you want to compile Op Kernel that supports both CPU and GPU devices. It further encapsulates python built-in ``setuptools.Extension`` .The arguments and usage are same as the native interface, except for no need to explicitly specify ``name`` . **A simple example:** .. code-block:: text # setup.py # Compiling customized operators supporting only CPU device from paddle.utils.cpp_extension import CppExtension, setup setup( name='custom_op', ext_modules=CppExtension(sources=['relu_op.cc']) ) Note: It is mainly used in ``setup`` and the nama of built shared library keeps same as ``name`` argument specified in ``setup`` interface. Args: sources(list[str]): Specify the C++/CUDA source files of customized operators. *args(list[options], optional): Specify other arguments same as ``setuptools.Extension`` . **kwargs(dict[option], optional): Specify other arguments same as ``setuptools.Extension`` . Returns: setuptools.Extension: An instance of ``setuptools.Extension`` """ kwargs = normalize_extension_kwargs(kwargs, use_cuda=False) # Note(Aurelius84): While using `setup` and `jit`, the Extension `name` will # be replaced as `setup.name` to keep consistant with package. Because we allow # users can not specific name in Extension. # See `paddle.utils.cpp_extension.setup` for details. name = kwargs.get('name', None) if name is None: name = _generate_extension_name(sources) return setuptools.Extension(name, sources, *args, **kwargs) def CUDAExtension(sources, *args, **kwargs): """ The interface is used to config source files of customized operators and complies Op Kernel supporting both CPU and GPU devices. Please use ``CppExtension`` if you want to compile Op Kernel that supports only CPU device. It further encapsulates python built-in ``setuptools.Extension`` .The arguments and usage are same as the native interface, except for no need to explicitly specify ``name`` . **A simple example:** .. code-block:: text # setup.py # Compiling customized operators supporting CPU and GPU devices from paddle.utils.cpp_extension import CUDAExtension, setup setup( name='custom_op', ext_modules=CUDAExtension( sources=['relu_op.cc', 'relu_op.cu'] ) ) Note: It is mainly used in ``setup`` and the nama of built shared library keeps same as ``name`` argument specified in ``setup`` interface. Args: sources(list[str]): Specify the C++/CUDA source files of customized operators. *args(list[options], optional): Specify other arguments same as ``setuptools.Extension`` . **kwargs(dict[option], optional): Specify other arguments same as ``setuptools.Extension`` . Returns: setuptools.Extension: An instance of setuptools.Extension. """ kwargs = normalize_extension_kwargs(kwargs, use_cuda=True) # Note(Aurelius84): While using `setup` and `jit`, the Extension `name` will # be replaced as `setup.name` to keep consistant with package. Because we allow # users can not specific name in Extension. # See `paddle.utils.cpp_extension.setup` for details. name = kwargs.get('name', None) if name is None: name = _generate_extension_name(sources) return setuptools.Extension(name, sources, *args, **kwargs) def _generate_extension_name(sources): """ Generate extension name by source files. """ assert len(sources) > 0, "source files is empty" file_prefix = [] for source in sources: source = os.path.basename(source) filename, _ = os.path.splitext(source) # Use list to generate same order. if filename not in file_prefix: file_prefix.append(filename) return '_'.join(file_prefix) class BuildExtension(build_ext, object): """ Inherited from setuptools.command.build_ext to customize how to apply compilation process with share library. """ @classmethod def with_options(cls, **options): """ Returns a BuildExtension subclass containing use-defined options. """ class cls_with_options(cls): def __init__(self, *args, **kwargs): kwargs.update(options) cls.__init__(self, *args, **kwargs) return cls_with_options def __init__(self, *args, **kwargs): """ Attributes is initialized with following oreder: 1. super(self).__init__() 2. initialize_options(self) 3. the reset of current __init__() 4. finalize_options(self) So, it is recommended to set attribute value in `finalize_options`. """ super(BuildExtension, self).__init__(*args, **kwargs) self.no_python_abi_suffix = kwargs.get("no_python_abi_suffix", True) self.output_dir = kwargs.get("output_dir", None) # whether containing cuda source file in Extensions self.contain_cuda_file = False def initialize_options(self): super(BuildExtension, self).initialize_options() def finalize_options(self): super(BuildExtension, self).finalize_options() # NOTE(Aurelius84): Set location of compiled shared library. # Carefully to modify this because `setup.py build/install` # and `load` interface rely on this attribute. if self.output_dir is not None: self.build_lib = self.output_dir def build_extensions(self): if OS_NAME.startswith("darwin"): self._valid_clang_compiler() self._check_abi() # Note(Aurelius84): If already compiling source before, we should check whether # cflags have changed and delete the built shared library to re-compile the source # even though source file content keep unchanged. so_name = self.get_ext_fullpath(self.extensions[0].name) clean_object_if_change_cflags( os.path.abspath(so_name), self.extensions[0] ) # Consider .cu, .cu.cc as valid source extensions. self.compiler.src_extensions += ['.cu', '.cu.cc'] # 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_custom_single_compiler( obj, src, ext, cc_args, extra_postargs, pp_opts ): """ Monkey patch machanism to replace inner compiler to custom complie process on Unix platform. """ # use abspath to ensure no warning and don't remove deecopy because modify params # with dict type is dangerous. src = os.path.abspath(src) cflags = copy.deepcopy(extra_postargs) try: original_compiler = self.compiler.compiler_so # nvcc or hipcc compile CUDA source if is_cuda_file(src): if core.is_compiled_with_rocm(): assert ( ROCM_HOME is not None ), "Not found ROCM runtime, \ please use `export ROCM_PATH= XXX` to specify it." hipcc_cmd = os.path.join(ROCM_HOME, 'bin', 'hipcc') self.compiler.set_executable('compiler_so', hipcc_cmd) # {'nvcc': {}, 'cxx: {}} if isinstance(cflags, dict): cflags = cflags['hipcc'] else: assert ( CUDA_HOME is not None ), "Not found CUDA runtime, \ please use `export CUDA_HOME= XXX` to specify it." nvcc_cmd = os.path.join(CUDA_HOME, 'bin', 'nvcc') self.compiler.set_executable('compiler_so', nvcc_cmd) # {'nvcc': {}, 'cxx: {}} if isinstance(cflags, dict): cflags = cflags['nvcc'] cflags = prepare_unix_cudaflags(cflags) # cxx compile Cpp source elif isinstance(cflags, dict): cflags = cflags['cxx'] # Note(qili93): HIP require some additional flags for CMAKE_C_FLAGS if core.is_compiled_with_rocm(): cflags.append('-D__HIP_PLATFORM_HCC__') cflags.append('-D__HIP_NO_HALF_CONVERSIONS__=1') cflags.append( '-DTHRUST_DEVICE_SYSTEM=THRUST_DEVICE_SYSTEM_HIP' ) # NOTE(Aurelius84): Since Paddle 2.0, we require gcc version > 5.x, # so we add this flag to ensure the symbol names from user compiled # shared library have same ABI suffix with libpaddle.so. # See https://stackoverflow.com/questions/34571583/understanding-gcc-5s-glibcxx-use-cxx11-abi-or-the-new-abi add_compile_flag(cflags, ['-D_GLIBCXX_USE_CXX11_ABI=1']) # Append this macor only when jointly compiling .cc with .cu if not is_cuda_file(src) and self.contain_cuda_file: if core.is_compiled_with_rocm(): cflags.append('-DPADDLE_WITH_HIP') else: cflags.append('-DPADDLE_WITH_CUDA') add_std_without_repeat( cflags, self.compiler.compiler_type, use_std14=True ) original_compile(obj, src, ext, cc_args, cflags, pp_opts) finally: # restore original_compiler self.compiler.set_executable('compiler_so', original_compiler) def win_custom_single_compiler( 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 win_custom_spawn(cmd): # Using regex to modify compile options compile_options = self.compiler.compile_options for i in range(len(cmd)): if re.search('/MD', cmd[i]) is not None: cmd[i] = '/MT' if re.search('/W[1-4]', cmd[i]) is not None: cmd[i] = '/W0' # Using regex to match src, obj and include files 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 ] assert len(src_list) == 1 and len(obj_list) == 1 src = src_list[0] obj = obj_list[0] if is_cuda_file(src): assert ( CUDA_HOME is not None ), "Not found CUDA runtime, \ please use `export CUDA_HOME= XXX` to specify it." nvcc_cmd = os.path.join(CUDA_HOME, 'bin', 'nvcc') if isinstance(self.cflags, dict): cflags = self.cflags['nvcc'] elif isinstance(self.cflags, list): cflags = self.cflags else: cflags = [] cflags = prepare_win_cudaflags(cflags) + ['--use-local-env'] for flag in MSVC_COMPILE_FLAGS: cflags = ['-Xcompiler', flag] + cflags cmd = ( [nvcc_cmd, '-c', src, '-o', obj] + include_list + cflags ) elif isinstance(self.cflags, dict): cflags = MSVC_COMPILE_FLAGS + self.cflags['cxx'] cmd += cflags elif isinstance(self.cflags, list): cflags = MSVC_COMPILE_FLAGS + self.cflags cmd += cflags # Append this macor only when jointly compiling .cc with .cu if not is_cuda_file(src) and self.contain_cuda_file: cmd.append('-DPADDLE_WITH_CUDA') return original_spawn(cmd) try: self.compiler.spawn = win_custom_spawn return original_compile( sources, output_dir, macros, include_dirs, debug, extra_preargs, extra_postargs, depends, ) finally: self.compiler.spawn = original_spawn def object_filenames_with_cuda(origina_func, build_directory): """ Decorated the function to add customized naming machanism. Originally, both .cc/.cu will have .o object output that will bring file override problem. Use .cu.o as CUDA object suffix. """ def wrapper(source_filenames, strip_dir=0, output_dir=''): try: objects = origina_func( source_filenames, strip_dir, output_dir ) for i, source in enumerate(source_filenames): # modify xx.o -> xx.cu.o/xx.cu.obj if is_cuda_file(source): old_obj = objects[i] if self.compiler.compiler_type == 'msvc': objects[i] = old_obj[:-3] + 'cu.obj' else: objects[i] = old_obj[:-1] + 'cu.o' # if user set build_directory, output objects there. if build_directory is not None: objects = [ os.path.join(build_directory, os.path.basename(obj)) for obj in objects ] # ensure to use abspath objects = [os.path.abspath(obj) for obj in objects] finally: self.compiler.object_filenames = origina_func return objects return wrapper # customized compile process if self.compiler.compiler_type == 'msvc': self.compiler.compile = win_custom_single_compiler else: self.compiler._compile = unix_custom_single_compiler self.compiler.object_filenames = object_filenames_with_cuda( self.compiler.object_filenames, self.build_lib ) self._record_op_info() print("Compiling user custom op, it will cost a few seconds.....") build_ext.build_extensions(self) # Reset runtime library path on MacOS platform so_path = self.get_ext_fullpath(self.extensions[0]._full_name) _reset_so_rpath(so_path) def get_ext_filename(self, fullname): # for example: custommed_extension.cpython-37m-x86_64-linux-gnu.so ext_name = super(BuildExtension, self).get_ext_filename(fullname) split_str = '.' name_items = ext_name.split(split_str) if self.no_python_abi_suffix and six.PY3: assert ( len(name_items) > 2 ), "Expected len(name_items) > 2, but received {}".format( len(name_items) ) name_items.pop(-2) ext_name = split_str.join(name_items) # custommed_extension.dylib if OS_NAME.startswith('darwin'): name_items[-1] = 'dylib' ext_name = split_str.join(name_items) return ext_name def _valid_clang_compiler(self): """ Make sure to use Clang as compiler on Mac platform """ compiler_infos = ['clang'] + CLANG_COMPILE_FLAGS linker_infos = ['clang'] + CLANG_LINK_FLAGS self.compiler.set_executables( compiler=compiler_infos, compiler_so=compiler_infos, compiler_cxx=['clang'], linker_exe=['clang'], linker_so=linker_infos, ) def _check_abi(self): """ Check ABI Compatibility. """ 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_abi_compatibility(compiler) # Warn user if VC env is activated but `DISTUTILS_USE_SDK` is not set. if ( IS_WINDOWS and 'VSCMD_ARG_TGT_ARCH' in os.environ and 'DISTUTILS_USE_SDK' not in os.environ ): msg = ( 'It seems that the VC environment is activated but DISTUTILS_USE_SDK is not set.' 'This may lead to multiple activations of the VC env.' 'Please run `set DISTUTILS_USE_SDK=1` and try again.' ) raise UserWarning(msg) def _record_op_info(self): """ Record custom op information. """ # parse shared library abs path outputs = self.get_outputs() assert len(outputs) == 1 # multi operators built into same one .so file so_path = os.path.abspath(outputs[0]) so_name = os.path.basename(so_path) for i, extension in enumerate(self.extensions): sources = [os.path.abspath(s) for s in extension.sources] if not self.contain_cuda_file: self.contain_cuda_file = any([is_cuda_file(s) for s in sources]) op_names = parse_op_name_from(sources) for op_name in op_names: CustomOpInfo.instance().add( op_name, so_name=so_name, so_path=so_path ) class EasyInstallCommand(easy_install, object): """ Extend easy_intall Command to control the behavior of naming shared library file. NOTE(Aurelius84): This is a hook subclass inherited Command used to rename shared library file after extracting egg-info into site-packages. """ def __init__(self, *args, **kwargs): super(EasyInstallCommand, self).__init__(*args, **kwargs) # NOTE(Aurelius84): Add args and kwargs to make compatible with PY2/PY3 def run(self, *args, **kwargs): super(EasyInstallCommand, self).run(*args, **kwargs) # NOTE: To avoid failing import .so file instead of # python file because they have same name, we rename # .so shared library to another name. for egg_file in self.outputs: filename, ext = os.path.splitext(egg_file) will_rename = False if OS_NAME.startswith('linux') and ext == '.so': will_rename = True elif OS_NAME.startswith('darwin') and ext == '.dylib': will_rename = True elif IS_WINDOWS and ext == '.pyd': will_rename = True if will_rename: new_so_path = filename + "_pd_" + ext if not os.path.exists(new_so_path): os.rename(r'%s' % egg_file, r'%s' % new_so_path) assert os.path.exists(new_so_path) class BuildCommand(build, object): """ Extend build Command to control the behavior of specifying `build_base` root directory. NOTE(Aurelius84): This is a hook subclass inherited Command used to specify customized build_base directory. """ @classmethod def with_options(cls, **options): """ Returns a BuildCommand subclass containing use-defined options. """ class cls_with_options(cls): def __init__(self, *args, **kwargs): kwargs.update(options) cls.__init__(self, *args, **kwargs) return cls_with_options def __init__(self, *args, **kwargs): # Note: shall put before super() self._specified_build_base = kwargs.get('build_base', None) super(BuildCommand, self).__init__(*args, **kwargs) def initialize_options(self): """ build_base is root directory for all sub-command, such as build_lib, build_temp. See `distutils.command.build` for details. """ super(BuildCommand, self).initialize_options() if self._specified_build_base is not None: self.build_base = self._specified_build_base def load( name, sources, extra_cxx_cflags=None, extra_cuda_cflags=None, extra_ldflags=None, extra_include_paths=None, build_directory=None, verbose=False, ): """ An Interface to automatically compile C++/CUDA source files Just-In-Time and return callable python function as other Paddle layers API. It will append user defined custom operators in background while building models. It will perform compiling, linking, Python API generation and module loading processes under a individual subprocess. It does not require CMake or Ninja environment. On Linux platform, it requires GCC compiler whose version is greater than 5.4 and it should be soft linked to ``/usr/bin/cc`` . On Windows platform, it requires Visual Studio whose version is greater than 2017. On MacOS, clang++ is requited. In addition, if compiling Operators supporting GPU device, please make sure ``nvcc`` compiler is installed in local environment. Moreover, `ABI compatibility `_ will be checked to ensure that compiler version from ``cc(Linux)`` , ``cl.exe(Windows)`` on local machine is compatible with pre-installed Paddle whl in python site-packages. For Linux, GCC version will be checked . For example if Paddle with CUDA 10.1 is built with GCC 8.2, then the version of user's local machine should satisfy GCC >= 8.2. For Windows, Visual Studio version will be checked, and it should be greater than or equal to that of PaddlePaddle (Visual Studio 2017). If the above conditions are not met, the corresponding warning will be printed, and a fatal error may occur because of ABI compatibility. Compared with ``setup`` interface, it doesn't need extra ``setup.py`` and excute ``python setup.py install`` command. The interface contains all compiling and installing process underground. Note: 1. Currently we support Linux, MacOS and Windows platfrom. 2. On Linux platform, we recommend to use GCC 8.2 as soft linking condidate of ``/usr/bin/cc`` . Then, Use ``which cc`` to ensure location of ``cc`` and using ``cc --version`` to ensure linking GCC version. 3. On Windows platform, we recommend to install `` Visual Studio`` (>=2017). **A simple example:** .. code-block:: text import paddle from paddle.utils.cpp_extension import load custom_op_module = load( name="op_shared_libary_name", # name of shared library sources=['relu_op.cc', 'relu_op.cu'], # source files of customized op extra_cxx_cflags=['-g', '-w'], # optional, specify extra flags to compile .cc/.cpp file extra_cuda_cflags=['-O2'], # optional, specify extra flags to compile .cu file verbose=True # optional, specify to output log information ) x = paddle.randn([4, 10], dtype='float32') out = custom_op_module.relu(x) Args: name(str): Specify the name of generated shared library file name, not including ``.so`` and ``.dll`` suffix. sources(list[str]): Specify source files name of customized operators. Supporting ``.cc`` , ``.cpp`` for CPP file and ``.cu`` for CUDA file. extra_cxx_cflags(list[str], optional): Specify additional flags used to compile CPP files. By default all basic and framework related flags have been included. extra_cuda_cflags(list[str], optional): Specify additional flags used to compile CUDA files. By default all basic and framework related flags have been included. See `Cuda Compiler Driver NVCC `_ for details. Default is None. extra_ldflags(list[str], optional): Specify additional flags used to link shared library. See `GCC Link Options `_ for details. Default is None. extra_include_paths(list[str], optional): Specify additional include path used to search header files. By default all basic headers are included implicitly from ``site-package/paddle/include`` . Default is None. build_directory(str, optional): Specify root directory path to put shared library file. If set None, it will use ``PADDLE_EXTENSION_DIR`` from os.environ. Use ``paddle.utils.cpp_extension.get_build_directory()`` to see the location. Default is None. verbose(bool, optional): whether to verbose compiled log information. Default is False Returns: Module: A callable python module contains all CustomOp Layer APIs. """ if build_directory is None: build_directory = get_build_directory(verbose) # ensure to use abs path build_directory = os.path.abspath(build_directory) log_v("build_directory: {}".format(build_directory), verbose) file_path = os.path.join(build_directory, "{}_setup.py".format(name)) sources = [os.path.abspath(source) for source in sources] if extra_cxx_cflags is None: extra_cxx_cflags = [] if extra_cuda_cflags is None: extra_cuda_cflags = [] assert isinstance( extra_cxx_cflags, list ), "Required type(extra_cxx_cflags) == list[str], but received {}".format( extra_cxx_cflags ) assert isinstance( extra_cuda_cflags, list ), "Required type(extra_cuda_cflags) == list[str], but received {}".format( extra_cuda_cflags ) log_v( "additional extra_cxx_cflags: [{}], extra_cuda_cflags: [{}]".format( ' '.join(extra_cxx_cflags), ' '.join(extra_cuda_cflags) ), verbose, ) # write setup.py file and compile it build_base_dir = os.path.join(build_directory, name) _write_setup_file( name, sources, file_path, build_base_dir, extra_include_paths, extra_cxx_cflags, extra_cuda_cflags, extra_ldflags, verbose, ) _jit_compile(file_path, verbose) # import as callable python api custom_op_api = _import_module_from_library(name, build_base_dir, verbose) return custom_op_api