Python extension.Extension方法代码示例

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def test_get_outputs(self):
        pkg_dir, dist = self.create_dist()
        cmd = install_lib(dist)

        # setting up a dist environment
        cmd.compile = cmd.optimize = 1
        cmd.install_dir = pkg_dir
        f = os.path.join(pkg_dir, 'foo.py')
        self.write_file(f, '# python file')
        cmd.distribution.py_modules = [pkg_dir]
        cmd.distribution.ext_modules = [Extension('foo', ['xxx'])]
        cmd.distribution.packages = [pkg_dir]
        cmd.distribution.script_name = 'setup.py'

        # get_output should return 4 elements
        self.assertGreaterEqual(len(cmd.get_outputs()), 2) 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def test_get_inputs(self):
        pkg_dir, dist = self.create_dist()
        cmd = install_lib(dist)

        # setting up a dist environment
        cmd.compile = cmd.optimize = 1
        cmd.install_dir = pkg_dir
        f = os.path.join(pkg_dir, 'foo.py')
        self.write_file(f, '# python file')
        cmd.distribution.py_modules = [pkg_dir]
        cmd.distribution.ext_modules = [Extension('foo', ['xxx'])]
        cmd.distribution.packages = [pkg_dir]
        cmd.distribution.script_name = 'setup.py'

        # get_input should return 2 elements
        self.assertEqual(len(cmd.get_inputs()), 2) 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def generate_extensions(ext_modules, line_trace=False):

    extensions = []

    if line_trace:
        print("define cython trace to True ...")
        define_macros = [('CYTHON_TRACE', 1), ('CYTHON_TRACE_NOGIL', 1)]
    else:
        define_macros = []

    for pyxfile in ext_modules:
        ext = Extension(name='.'.join(pyxfile.split('/'))[:-4],
                        sources=[pyxfile],
                        define_macros=define_macros)
        extensions.append(ext)
    return extensions 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def test_get_outputs(self):
        pkg_dir, dist = self.create_dist()
        cmd = install_lib(dist)

        # setting up a dist environment
        cmd.compile = cmd.optimize = 1
        cmd.install_dir = pkg_dir
        f = os.path.join(pkg_dir, 'foo.py')
        self.write_file(f, '# python file')
        cmd.distribution.py_modules = [pkg_dir]
        cmd.distribution.ext_modules = [Extension('foo', ['xxx'])]
        cmd.distribution.packages = [pkg_dir]
        cmd.distribution.script_name = 'setup.py'

        # get_output should return 4 elements
        self.assertTrue(len(cmd.get_outputs()) >= 2) 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def run(self):
        # add numpy headers
        import numpy
        self.include_dirs.append(numpy.get_include())

        # add dimod headers
        include = os.path.join(os.path.dirname(__file__), 'dimod', 'include')
        self.include_dirs.append(include)

        if self.build_tests:

            test_extensions = [Extension('*', ['tests/test_*'+ext])]
            if USE_CYTHON:
                test_extensions = cythonize(test_extensions,
                                            # annotate=True
                                            )
            self.extensions.extend(test_extensions)

        super().run() 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def test_get_outputs(self):
        project_dir, dist = self.create_dist()
        os.chdir(project_dir)
        os.mkdir('spam')
        cmd = install_lib(dist)

        # setting up a dist environment
        cmd.compile = cmd.optimize = 1
        cmd.install_dir = self.mkdtemp()
        f = os.path.join(project_dir, 'spam', '__init__.py')
        self.write_file(f, '# python package')
        cmd.distribution.ext_modules = [Extension('foo', ['xxx'])]
        cmd.distribution.packages = ['spam']
        cmd.distribution.script_name = 'setup.py'

        # get_outputs should return 4 elements: spam/__init__.py and .pyc,
        # foo.import-tag-abiflags.so / foo.pyd
        outputs = cmd.get_outputs()
        self.assertEqual(len(outputs), 4, outputs) 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def test_get_inputs(self):
        project_dir, dist = self.create_dist()
        os.chdir(project_dir)
        os.mkdir('spam')
        cmd = install_lib(dist)

        # setting up a dist environment
        cmd.compile = cmd.optimize = 1
        cmd.install_dir = self.mkdtemp()
        f = os.path.join(project_dir, 'spam', '__init__.py')
        self.write_file(f, '# python package')
        cmd.distribution.ext_modules = [Extension('foo', ['xxx'])]
        cmd.distribution.packages = ['spam']
        cmd.distribution.script_name = 'setup.py'

        # get_inputs should return 2 elements: spam/__init__.py and
        # foo.import-tag-abiflags.so / foo.pyd
        inputs = cmd.get_inputs()
        self.assertEqual(len(inputs), 2, inputs) 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def test_optional_extension(self):

        # this extension will fail, but let's ignore this failure
        # with the optional argument.
        modules = [Extension('foo', ['xxx'], optional=False)]
        dist = Distribution({'name': 'xx', 'ext_modules': modules})
        cmd = self.build_ext(dist)
        cmd.ensure_finalized()
        self.assertRaises((UnknownFileError, CompileError),
                          cmd.run)  # should raise an error

        modules = [Extension('foo', ['xxx'], optional=True)]
        dist = Distribution({'name': 'xx', 'ext_modules': modules})
        cmd = self.build_ext(dist)
        cmd.ensure_finalized()
        cmd.run()  # should pass 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def config_cython():
    """Try to configure cython and return cython configuration"""
    if not with_cython:
        return []
    # pylint: disable=unreachable
    if os.name == 'nt':
        print("WARNING: Cython is not supported on Windows, will compile without cython module")
        return []

    try:
        from Cython.Build import cythonize
        # from setuptools.extension import Extension
        if sys.version_info >= (3, 0):
            subdir = "_cy3"
        else:
            subdir = "_cy2"
        ret = []
        path = "mxnet/cython"
        if os.name == 'nt':
            library_dirs = ['mxnet', '../build/Release', '../build']
            libraries = ['libmxnet']
        else:
            library_dirs = None
            libraries = None

        for fn in os.listdir(path):
            if not fn.endswith(".pyx"):
                continue
            ret.append(Extension(
                "mxnet/%s/.%s" % (subdir, fn[:-4]),
                ["mxnet/cython/%s" % fn],
                include_dirs=["../include/", "../3rdparty/tvm/nnvm/include"],
                library_dirs=library_dirs,
                libraries=libraries,
                language="c++"))
        return cythonize(ret)
    except ImportError:
        print("WARNING: Cython is not installed, will compile without cython module")
        return [] 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.
    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        print(extra_postargs)
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile


# run the customize_compiler 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.

    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile


# run the customize_compiler 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.

    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        print(extra_postargs)
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile


# run the customize_compiler 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.
    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile


# run the customize_compiler 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.

    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        print extra_postargs
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile


# run the customize_compiler 

# 需要导入模块: from distutils import extension [as 别名]
# 或者: from distutils.extension import Extension [as 别名]
def customize_compiler_for_nvcc(self):
    """inject deep into distutils to customize how the dispatch
    to gcc/nvcc works.

    If you subclass UnixCCompiler, it's not trivial to get your subclass
    injected in, and still have the right customizations (i.e.
    distutils.sysconfig.customize_compiler) run on it. So instead of going
    the OO route, I have this. Note, it's kindof like a wierd functional
    subclassing going on."""

    # tell the compiler it can processes .cu
    self.src_extensions.append('.cu')

    # save references to the default compiler_so and _comple methods
    default_compiler_so = self.compiler_so
    super = self._compile

    # now redefine the _compile method. This gets executed for each
    # object but distutils doesn't have the ability to change compilers
    # based on source extension: we add it.
    def _compile(obj, src, ext, cc_args, extra_postargs, pp_opts):
        print(extra_postargs)
        if os.path.splitext(src)[1] == '.cu':
            # use the cuda for .cu files
            self.set_executable('compiler_so', CUDA['nvcc'])
            # use only a subset of the extra_postargs, which are 1-1 translated
            # from the extra_compile_args in the Extension class
            postargs = extra_postargs['nvcc']
        else:
            postargs = extra_postargs['gcc']

        super(obj, src, ext, cc_args, postargs, pp_opts)
        # reset the default compiler_so, which we might have changed for cuda
        self.compiler_so = default_compiler_so

    # inject our redefined _compile method into the class
    self._compile = _compile

# run the customize_compiler