cpp_extension.py 36.9 KB
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# 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
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import re
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import setuptools
from setuptools.command.easy_install import easy_install
from setuptools.command.build_ext import build_ext
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from distutils.command.build import build
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from .extension_utils import find_cuda_home, find_rocm_home, normalize_extension_kwargs, add_compile_flag, run_cmd
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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
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from .extension_utils import clean_object_if_change_cflags, _reset_so_rpath, _get_fluid_path
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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
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from .extension_utils import CLANG_COMPILE_FLAGS, CLANG_LINK_FLAGS
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from ...fluid import core

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# 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)
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CUDA_HOME = find_cuda_home()
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if core.is_compiled_with_rocm():
    ROCM_HOME = find_rocm_home()
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    CUDA_HOME = ROCM_HOME
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def setup(**attr):
    """
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    The interface is used to config the process of compiling customized operators,
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    mainly includes how to compile shared library, automatically generate python API 
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    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
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    flags. It also will automatically search and valid local environment and versions of 
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    ``cc(Linux)`` , ``cl.exe(Windows)`` and ``nvcc`` , then compiles customized operators 
    supporting CPU or GPU device according to the specified Extension type.
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    Moreover, `ABI compatibility <https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html>`_ 
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    will be checked to ensure that compiler version from ``cc(Linux)`` , ``cl.exe(Windows)``
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    on local machine is compatible with pre-installed Paddle whl in python site-packages.

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    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. 
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    For Windows, Visual Studio version will be checked, and it should be greater than or equal to that of 
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    PaddlePaddle (Visual Studio 2017). 
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    If the above conditions are not met, the corresponding warning will be printed, and a fatal error may 
    occur because of ABI compatibility.
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    .. note::
        
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        1. Currently we support Linux, MacOS and Windows platfrom.
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        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.
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        3. On Windows platform, we recommend to install `` Visual Studio`` (>=2017).
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    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`` .
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        include_dirs(list[str], optional): Specify the extra include directories to search head files. The interface will automatically add
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                                 ``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`` .

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    Returns: 
        None
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    """
    cmdclass = attr.get('cmdclass', {})
    assert isinstance(cmdclass, dict)
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    # if not specific cmdclass in setup, add it automatically.
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    if 'build_ext' not in cmdclass:
        cmdclass['build_ext'] = BuildExtension.with_options(
            no_python_abi_suffix=True)
        attr['cmdclass'] = cmdclass

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    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'])
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        # After running `python setup.py install`
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        from custom_module import relu
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    """
    # name argument is required
    if 'name' not in attr:
        raise ValueError(error_msg)

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    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."

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    ext_modules = attr.get('ext_modules', [])
    if not isinstance(ext_modules, list):
        ext_modules = [ext_modules]
    assert len(
        ext_modules
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    ) == 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(
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        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

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    # Add rename .so hook in easy_install
    assert 'easy_install' not in cmdclass
    cmdclass['easy_install'] = EasyInstallCommand

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    # 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)

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    # 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)


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def CppExtension(sources, *args, **kwargs):
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    """
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    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.

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    It further encapsulates python built-in ``setuptools.Extension`` .The arguments and
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    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.

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    Args:
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        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`` .
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    Returns:
        setuptools.Extension: An instance of ``setuptools.Extension``
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    """
    kwargs = normalize_extension_kwargs(kwargs, use_cuda=False)
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    # 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)
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    return setuptools.Extension(name, sources, *args, **kwargs)


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def CUDAExtension(sources, *args, **kwargs):
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    """
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    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.

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    It further encapsulates python built-in ``setuptools.Extension`` .The arguments and
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    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.

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    Args:
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        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`` .
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    Returns:
        setuptools.Extension: An instance of setuptools.Extension
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    """
    kwargs = normalize_extension_kwargs(kwargs, use_cuda=True)
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    # 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)
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    return setuptools.Extension(name, sources, *args, **kwargs)


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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)


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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):
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            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:
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            1. super(self).__init__()
            2. initialize_options(self)
            3. the reset of current __init__()
            4. finalize_options(self)
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        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)
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        # whether containing cuda source file in Extensions
        self.contain_cuda_file = False
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    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):
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        if OS_NAME.startswith("darwin"):
            self._valid_clang_compiler()

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        self._check_abi()

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        # 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
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        # even though source file content keep unchanged.
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        so_name = self.get_ext_fullpath(self.extensions[0].name)
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        clean_object_if_change_cflags(os.path.abspath(so_name),
                                      self.extensions[0])
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        # Consider .cu, .cu.cc as valid source extensions.
        self.compiler.src_extensions += ['.cu', '.cu.cc']
        # Save the original _compile method for later.
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        if self.compiler.compiler_type == 'msvc':
            self.compiler._cpp_extensions += ['.cu', '.cuh']
            original_compile = self.compiler.compile
            original_spawn = self.compiler.spawn
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        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
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                # nvcc or hipcc compile CUDA source
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                if is_cuda_file(src):
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                    if core.is_compiled_with_rocm():
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                        assert ROCM_HOME is not None, "Not found ROCM runtime, \
                            please use `export ROCM_PATH= XXX` to specify it."

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                        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:
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                        assert CUDA_HOME is not None, "Not found CUDA runtime, \
                            please use `export CUDA_HOME= XXX` to specify it."

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                        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']
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                    cflags = prepare_unix_cudaflags(cflags)
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                # cxx compile Cpp source
                elif isinstance(cflags, dict):
                    cflags = cflags['cxx']

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                # 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')

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                # 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 core_(no)avx.so.
                # See https://stackoverflow.com/questions/34571583/understanding-gcc-5s-glibcxx-use-cxx11-abi-or-the-new-abi
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                add_compile_flag(cflags, ['-D_GLIBCXX_USE_CXX11_ABI=1'])
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                # Append this macor only when jointly compiling .cc with .cu
                if not is_cuda_file(src) and self.contain_cuda_file:
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                    if core.is_compiled_with_rocm():
                        cflags.append('-DPADDLE_WITH_HIP')
                    else:
                        cflags.append('-DPADDLE_WITH_CUDA')
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                add_std_without_repeat(cflags,
                                       self.compiler.compiler_type,
                                       use_std14=True)
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                original_compile(obj, src, ext, cc_args, cflags, pp_opts)
            finally:
                # restore original_compiler
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                self.compiler.set_executable('compiler_so', original_compiler)
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        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):
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                    assert CUDA_HOME is not None, "Not found CUDA runtime, \
                        please use `export CUDA_HOME= XXX` to specify it."

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                    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 = []

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                    cflags = prepare_win_cudaflags(cflags) + ['--use-local-env']
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                    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
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                # 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')
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                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

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        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):
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                        # modify xx.o -> xx.cu.o/xx.cu.obj
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                        if is_cuda_file(source):
                            old_obj = objects[i]
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                            if self.compiler.compiler_type == 'msvc':
                                objects[i] = old_obj[:-3] + 'cu.obj'
                            else:
                                objects[i] = old_obj[:-1] + 'cu.o'
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                    # 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
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        if self.compiler.compiler_type == 'msvc':
            self.compiler.compile = win_custom_single_compiler
        else:
            self.compiler._compile = unix_custom_single_compiler

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        self.compiler.object_filenames = object_filenames_with_cuda(
            self.compiler.object_filenames, self.build_lib)
        self._record_op_info()
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        print("Compiling user custom op, it will cost a few seconds.....")
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        build_ext.build_extensions(self)

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        # Reset runtime library path on MacOS platform
        so_path = self.get_ext_fullpath(self.extensions[0]._full_name)
        _reset_so_rpath(so_path)

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    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)
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        split_str = '.'
        name_items = ext_name.split(split_str)
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        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)

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        # custommed_extension.dylib
        if OS_NAME.startswith('darwin'):
            name_items[-1] = 'dylib'
            ext_name = split_str.join(name_items)
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        return ext_name

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    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
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        self.compiler.set_executables(compiler=compiler_infos,
                                      compiler_so=compiler_infos,
                                      compiler_cxx=['clang'],
                                      linker_exe=['clang'],
                                      linker_so=linker_infos)
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    def _check_abi(self):
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        """
        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)
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        # Warn user if VC env is activated but `DISTUTILS_USE_SDK` is not set.
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        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.'
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                'Please run `set DISTUTILS_USE_SDK=1` and try again.')
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            raise UserWarning(msg)
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    def _record_op_info(self):
        """
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        Record custom op information.
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        """
        # parse shared library abs path
        outputs = self.get_outputs()
        assert len(outputs) == 1
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        # 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]
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            if not self.contain_cuda_file:
                self.contain_cuda_file = any([is_cuda_file(s) for s in sources])
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            op_names = parse_op_name_from(sources)

            for op_name in op_names:
                CustomOpInfo.instance().add(op_name,
                                            so_name=so_name,
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                                            so_path=so_path)
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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)
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            will_rename = False
            if OS_NAME.startswith('linux') and ext == '.so':
                will_rename = True
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            elif OS_NAME.startswith('darwin') and ext == '.dylib':
                will_rename = True
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            elif IS_WINDOWS and ext == '.pyd':
                will_rename = True

            if will_rename:
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                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)


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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):
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            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


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def load(name,
         sources,
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         extra_cxx_cflags=None,
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         extra_cuda_cflags=None,
         extra_ldflags=None,
         extra_include_paths=None,
         build_directory=None,
         verbose=False):
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    """
    An Interface to automatically compile C++/CUDA source files Just-In-Time
    and return callable python function as other Paddle layers API. It will
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    append user defined custom operators in background while building models.

    It will perform compiling, linking, Python API generation and module loading
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    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 
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    platform, it requires Visual Studio whose version is greater than 2017.
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    On MacOS, clang++ is requited. In addition, if compiling Operators supporting 
    GPU device, please make sure ``nvcc`` compiler is installed in local environment.
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    Moreover, `ABI compatibility <https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html>`_ 
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    will be checked to ensure that compiler version from ``cc(Linux)`` , ``cl.exe(Windows)``
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    on local machine is compatible with pre-installed Paddle whl in python site-packages.
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    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. 
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    For Windows, Visual Studio version will be checked, and it should be greater than or equal to that of 
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    PaddlePaddle (Visual Studio 2017). 
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    If the above conditions are not met, the corresponding warning will be printed, and a fatal error may 
    occur because of ABI compatibility.
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    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::

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        1. Currently we support Linux, MacOS and Windows platfrom.
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        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.
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        3. On Windows platform, we recommend to install `` Visual Studio`` (>=2017).
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    **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
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            sources=['relu_op.cc', 'relu_op.cu'],        # source files of customized op
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            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
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        )

        x = paddle.randn([4, 10], dtype='float32')
        out = custom_op_module.relu(x)
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    Args:
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        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
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                               all basic and framework related flags have been included.
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        extra_cuda_cflags(list[str], optional): Specify additional flags used to compile CUDA files. By default
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                               all basic and framework related flags have been included. 
                               See `Cuda Compiler Driver NVCC <https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html>`_
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                               for details. Default is None.
        extra_ldflags(list[str], optional): Specify additional flags used to link shared library. See
                                `GCC Link Options <https://gcc.gnu.org/onlinedocs/gcc/Link-Options.html>`_ 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
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    Returns:
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        Module: A callable python module contains all CustomOp Layer APIs.
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    """
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    if build_directory is None:
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        build_directory = get_build_directory(verbose)

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    # ensure to use abs path
    build_directory = os.path.abspath(build_directory)
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    log_v("build_directory: {}".format(build_directory), verbose)
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    file_path = os.path.join(build_directory, "{}_setup.py".format(name))
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    sources = [os.path.abspath(source) for source in sources]

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    if extra_cxx_cflags is None: extra_cxx_cflags = []
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    if extra_cuda_cflags is None: extra_cuda_cflags = []
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    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)

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    log_v(
        "additional extra_cxx_cflags: [{}], extra_cuda_cflags: [{}]".format(
            ' '.join(extra_cxx_cflags), ' '.join(extra_cuda_cflags)), verbose)
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    # write setup.py file and compile it
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    build_base_dir = os.path.join(build_directory, name)
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    _write_setup_file(name, sources, file_path, build_base_dir,
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                      extra_include_paths, extra_cxx_cflags, extra_cuda_cflags,
                      extra_ldflags, verbose)
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    _jit_compile(file_path, verbose)
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    # import as callable python api
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    custom_op_api = _import_module_from_library(name, build_base_dir, verbose)
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    return custom_op_api