diff --git a/python/paddle/fluid/tests/custom_op/test_dispatch_jit.py b/python/paddle/fluid/tests/custom_op/test_dispatch_jit.py index 45fd640887e98..54d317c37faa9 100644 --- a/python/paddle/fluid/tests/custom_op/test_dispatch_jit.py +++ b/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) diff --git a/python/paddle/fluid/tests/custom_op/test_multi_out_jit.py b/python/paddle/fluid/tests/custom_op/test_multi_out_jit.py index bbf97734b81a2..79d366cc4af44 100644 --- a/python/paddle/fluid/tests/custom_op/test_multi_out_jit.py +++ b/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) diff --git a/python/paddle/utils/cpp_extension/__init__.py b/python/paddle/utils/cpp_extension/__init__.py index 024fbb6bf7c4e..130ab79b3038d 100644 --- a/python/paddle/utils/cpp_extension/__init__.py +++ b/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' ] diff --git a/python/paddle/utils/cpp_extension/cpp_extension.py b/python/paddle/utils/cpp_extension/cpp_extension.py index 894d538e494b3..57bcea658b53c 100644 --- a/python/paddle/utils/cpp_extension/cpp_extension.py +++ b/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 `_ + 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 `_ + 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 `_ + 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. + 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: diff --git a/python/paddle/utils/cpp_extension/extension_utils.py b/python/paddle/utils/cpp_extension/extension_utils.py index 0825f7479b5e6..db2da5574854c 100644 --- a/python/paddle/utils/cpp_extension/extension_utils.py +++ b/python/paddle/utils/cpp_extension/extension_utils.py @@ -440,7 +440,22 @@ 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: