[CustomOp]Add cpp_extension en doc

python/paddle/fluid/tests/custom_op/test_dispatch_jit.py

@@ -32,7 +32,6 @@
     sources=['dispatch_test_op.cc'],
     extra_include_paths=paddle_includes,  # add for Coverage CI
     extra_cxx_cflags=extra_compile_args,
-    extra_cuda_cflags=extra_compile_args,  # add for Coverage CI
     verbose=True)
 
 

python/paddle/fluid/tests/custom_op/test_multi_out_jit.py

@@ -36,7 +36,6 @@
     sources=['multi_out_test_op.cc'],
     extra_include_paths=paddle_includes,  # add for Coverage CI
     extra_cxx_cflags=extra_compile_args,  # add for Coverage CI
-    extra_cuda_cflags=extra_compile_args,  # add for Coverage CI
     verbose=True)
 
 

python/paddle/utils/cpp_extension/__init__.py

@@ -25,6 +25,5 @@
 from . import extension_utils
 
 __all__ = [
-    'CppExtension', 'CUDAExtension', 'BuildExtension', 'load', 'setup',
-    'get_build_directory'
+    'CppExtension', 'CUDAExtension', 'load', 'setup', 'get_build_directory'
 ]

python/paddle/utils/cpp_extension/cpp_extension.py

@@ -41,24 +41,93 @@
 
 def setup(**attr):
     """
-    Wrapper setuptools.setup function to valid `build_ext` command and
-    implement paddle api code injection by switching `write_stub`
-    function in bdist_egg with `custom_write_stub`.
-
-    Its usage is almost same as `setuptools.setup` except for `ext_modules`
-    arguments. For compiling multi custom operators, all necessary source files
-    can be include into just one Extension (CppExtension/CUDAExtension).
-    Moreover, only one `name` argument is required in `setup` and no need to specify
-    `name` in Extension.
-
-    Example:
-
-        >> from paddle.utils.cpp_extension import CUDAExtension, setup
-        >> setup(name='custom_module',
-                 ext_modules=CUDAExtension(
-                    sources=['relu_op.cc', 'relu_op.cu'],
-                    include_dirs=[],       # specific user-defined include dirs
-                    extra_compile_args=[]) # specific user-defined compiler arguments.
+    The interface is used to config the process of compiling customized operators,
+    mainly includes how to complile 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 enviromment and versions of ``cc`` and
+    ``nvcc`` , then compiles customized operators supporting CPU or GPU device according to
+    the specified Extension type.
+
+    Moreover, `ABI compatibility <https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html>`_ 
+    will be checked to ensure that compiler version from ``cc``
+    on local machine is compatible with pre-installed Paddle whl in python site-packages.
+    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. Otherwise, a fatal error will occur because of
+    ABI compatibility.
+
+    .. note::
+
+        1. Compiler ABI compatibility is forward compatible. On Linux platform, 
+           we recommend to use GCC 8.2 as soft linking condidate of ``/usr/bin/cc`` .
+        2. Using ``which cc`` to ensure location of ``cc`` and using ``cc --version`` 
+           to ensure linking GCC version on Linux.
+        3. Currently we support Linux and Windows platfrom. MacOS is supporting...
+
+
+    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 directoies 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)
@@ -124,16 +193,41 @@ def setup(**attr):
 
 def CppExtension(sources, *args, **kwargs):
     """
-    Returns setuptools.CppExtension instance for setup.py to make it easy
-    to specify compile flags while building C++ custommed op kernel.
+    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 furtherly 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]): The C++/CUDA source file names
-           args(list[options]): list of config options used to compile shared library
-           kwargs(dict[option]): dict of config options used to compile shared library
+        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:
-           Extension: An instance of 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
@@ -149,16 +243,43 @@ def CppExtension(sources, *args, **kwargs):
 
 def CUDAExtension(sources, *args, **kwargs):
     """
-    Returns setuptools.CppExtension instance for setup.py to make it easy
-    to specify compile flags while build CUDA custommed op kernel.
+    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 furtherly 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]): The C++/CUDA source file names
-           args(list[options]): list of config options used to compile shared library
-           kwargs(dict[option]): dict of config options used to compile shared library
+        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:
-           Extension: An instance of 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
@@ -539,48 +660,86 @@ def load(name,
     """
     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 op in background.
+    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
+    and only ``g++/nvcc`` on Linux and clang++ on MacOS. For example it requires
+    GCC compiler with version is greater than 5.4 and linked into ``/usr/bin/cc`` .
+    If compiling Operators supporting GPU device, please make sure ``nvcc`` compiler
+    is installed in local environment.
+
+
+    Moreover, `ABI compatibility <https://gcc.gnu.org/onlinedocs/libstdc++/manual/abi.html>`_ 
+    will be checked to ensure that compiler version from ``cc``
+    on local machine is compatible with pre-installed Paddle whl in python site-packages.
+    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. Otherwise, a fatal error will 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. Compiler ABI compatibility is forward compatible. On Linux platform, 
+           we recommend to use GCC 8.2 as soft linking condidate of ``/usr/bin/cc`` .
+        2. Using ``which cc`` to ensure location of ``cc`` and using ``cc --version`` 
+           to ensure linking GCC version on Linux.
+        3. Currenly we support Linux and Windows platfrom. MacOS is supporting...
+
+
+    **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 cusomized op
+            extra_cxx_cflags=['-DPADDLE_WITH_MKLDNN'],   # need to specify the flag if pre-installed Paddle supports MKLDNN
+            extra_cuda_cflags=['-DPADDLE_WITH_MKLDNN'],  # need to specify the flag if pre-installed Paddle supports MKLDNN
+            interpreter='python3.7',                     # optional, specify another python interpreter
+            verbose=True                                 # output log information
+        )
+
+        x = paddle.randn([4, 10], dtype='float32')
+        out = custom_op_module.relu(x)
 
-    This module will perform compiling, linking, api generation and module loading
-    processes for users. It does not require CMake or Ninja environment and only
-    g++/nvcc on Linux and clang++ on MacOS. Moreover, ABI compatibility will be
-    checked to ensure that compiler version on local machine is compatible with
-    pre-installed Paddle whl in python site-packages. For example if Paddle is built
-    with GCC5.4, the version of user's local machine should satisfy GCC >= 5.4.
-    Otherwise, a fatal error will occur because  ABI compatibility.
 
     Args:
-        name(str): generated shared library file name.
-        sources(list[str]): custom op source files name with .cc/.cu suffix.
-        extra_cxx_cflags(list[str]): additional flags used to compile CPP files. By default
+        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.
                                If your pre-insall Paddle supported MKLDNN, please add
-                               '-DPADDLE_WITH_MKLDNN'. Default None.
-        extra_cuda_cflags(list[str]): additional flags used to compile CUDA files. See
-                                https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html
-                                for details. Default None.
-        extra_ldflags(list[str]): additional flags used to link shared library. See
-                                https://gcc.gnu.org/onlinedocs/gcc/Link-Options.html for details.
-                                Default None.
-        extra_include_paths(list[str]): additional include path used to search header files.
-                                        Default None.
-        build_directory(str): specific 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.
-        interpreter(str): alias or full interpreter path to specific which one to use if have installed multiple.
-                           If set None, will use `python` as default interpreter.
-        verbose(bool): whether to verbose compiled log information
+                               ``-DPADDLE_WITH_MKLDNN`` . Default is None.
+        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. If your pre-insall Paddle supported MKLDNN, 
+                               please add ``-DPADDLE_WITH_MKLDNN`` . Default None. See `Cuda Compiler Driver NVCC <https://docs.nvidia.com/cuda/cuda-compiler-driver-nvcc/index.html>`_
+                               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.
+        interpreter(str, optional): Specify nterpreter path, supporting alias and full path.
+                           If set None, it will use `python` as default interpreter. If local environment contains
+                           more than one python interpreters and want to use new interpreter to apply compilation,
+                           please specify this parameter, such as ``python3.7`` . Default is None.
+        verbose(bool, optional): whether to verbose compiled log information. Default is False
 
     Returns:
-        custom api: A callable python function with same signature as CustomOp Kernel definition.
-
-    Example:
+        Moudle: A callable python module contains all CustomOp Layer APIs.
 
-        >> from paddle.utils.cpp_extension import load
-        >> relu2 = load(name='relu2',
-                        sources=['relu_op.cc', 'relu_op.cu'])
-        >> x = paddle.rand([4, 10]], dtype='float32')
-        >> out = relu2(x)
     """
 
     if build_directory is None:

python/paddle/utils/cpp_extension/extension_utils.py

@@ -432,7 +432,22 @@ def is_cuda_file(path):
 
 def get_build_directory(verbose=False):
     """
-    Return paddle extension root directory, default specific by `PADDLE_EXTENSION_DIR`
+    Return paddle extension root directory to put shared library. It could be specified by
+    ``export PADDLE_EXTENSION_DIR=XXX`` . If not set, ``~/.cache/paddle_extension`` will be used
+    by default.
+
+    Returns:
+        The root directory of compiling customized operators.
+
+    Examples:
+
+    .. code-block:: python
+
+        from paddle.utils.cpp_extension import get_build_directory
+
+        build_dir = get_build_directory()
+        print(build_dir)
+
     """
     root_extensions_directory = os.environ.get('PADDLE_EXTENSION_DIR')
     if root_extensions_directory is None: