Python load_library.load_op_library函数代码示例

def get_tf_abi(build_ext, include_dirs, lib_dirs, libs, cpp_flags):
    last_err = None
    cxx11_abi_macro = '_GLIBCXX_USE_CXX11_ABI'
    for cxx11_abi in ['0', '1']:
        try:
            lib_file = test_compile(build_ext, 'test_tensorflow_abi',
                                    macros=[(cxx11_abi_macro, cxx11_abi)],
                                    include_dirs=include_dirs, library_dirs=lib_dirs,
                                    libraries=libs, extra_preargs=cpp_flags,
                                    code=textwrap.dedent('''\
                #include <string>
                #include "tensorflow/core/framework/op.h"
                #include "tensorflow/core/framework/op_kernel.h"
                #include "tensorflow/core/framework/shape_inference.h"
                void test() {
                    auto ignore = tensorflow::strings::StrCat("a", "b");
                }
                '''))

            from tensorflow.python.framework import load_library
            load_library.load_op_library(lib_file)

            return cxx11_abi_macro, cxx11_abi
        except (CompileError, LinkError):
            last_err = 'Unable to determine CXX11 ABI to use with TensorFlow (see error above).'
        except Exception:
            last_err = 'Unable to determine CXX11 ABI to use with TensorFlow.  ' \
                       'Last error:\n\n%s' % traceback.format_exc()

    raise DistutilsPlatformError(last_err)

def _maybe_load_sdca_ops():
  with _sdca_ops_lock:
    global _sdca_ops
    if not _sdca_ops:
      _sdca_ops = load_op_library(os.path.join(
          resource_loader.get_data_files_path(), '_sdca_ops.so'))
      assert _sdca_ops, 'Could not load _sdca_ops.so'

def _load_library(name, op_list=None):
  """Loads a .so file containing the specified operators.

  Args:
    name: The name of the .so file to load.
    op_list: A list of names of operators that the library should have. If None
        then the .so file's contents will not be verified.

  Raises:
    NameError if one of the required ops is missing.
  """
  try:
    filename = resource_loader.get_path_to_datafile(name)
    library = load_library.load_op_library(filename)
    for expected_op in (op_list or []):
      for lib_op in library.OP_LIST.op:
        if lib_op.name == expected_op:
          break
      else:
        raise NameError(
          'Could not find operator %s in dynamic library %s' %
          (expected_op, name))
    return library
  except errors.NotFoundError:
    logging.warning('%s file could not be loaded.', name)

def load_op_library(path):
  """Loads a contrib op library from the given path.

  NOTE(mrry): On Windows, we currently assume that some contrib op
  libraries are statically linked into the main TensorFlow Python
  extension DLL - use dynamically linked ops if the .so is present.

  Args:
    path: An absolute path to a shared object file.

  Returns:
    A Python module containing the Python wrappers for Ops defined in the
    plugin.
  """
  if os.name == 'nt':
    # To avoid makeing every user_ops aware of windows, re-write
    # the file extension from .so to .dll.
    path = re.sub(r'\.so$', '.dll', path)

    # Currently we have only some user_ops as dlls on windows - don't try
    # to load them if the dll is not found.
    # TODO(mrry): Once we have all of them this check should be removed.
    if not os.path.exists(path):
      return None
  path = resource_loader.get_path_to_datafile(path)
  ret = load_library.load_op_library(path)
  assert ret, 'Could not load %s' % path
  return ret