class_docstr: Provides ways to export symbols to the TensorFlow API.
class_docstr_tok: ["Provides","ways","to","export","symbols","to","the","TensorFlow","API","."]
docstr: Calls this decorator.
  
  Args:
    func: decorated symbol (function or class).
  
  Returns:
    The input function with _tf_api_names attribute set.
docstr_tok: ["Calls","this","decorator",".","Args",":","func",":","decorated","symbol","(","function","or","class",")",".","Returns",":","The","input","function","with","_tf_api_names","attribute","set","."]
code: def __call__(self, func: T) -> T:
      """Calls this decorator.
  
      Args:
        func: decorated symbol (function or class).
  
      Returns:
        The input function with _tf_api_names attribute set.
      """
      api_names_attr = API_ATTRS[self._api_name].names
      api_names_attr_v1 = API_ATTRS_V1[self._api_name].names
  
      _, undecorated_func = tf_decorator.unwrap(func)
      self.set_attr(undecorated_func, api_names_attr, self._names)
      self.set_attr(undecorated_func, api_names_attr_v1, self._names_v1)
  
      for name in self._names:
          _NAME_TO_SYMBOL_MAPPING[name] = func
      for name_v1 in self._names_v1:
          _NAME_TO_SYMBOL_MAPPING["compat.v1.%s" % name_v1] = func
  
      return func
  
imports: from collections.abc import Sequence
  import functools
  import sys
  from typing import Any, NamedTuple, Optional, Protocol, TypeVar
  from tensorflow.python.util import tf_decorator
  from tensorflow.python.util import tf_inspect
label_desc: Use image node_id 3 for calling the api_export obj's underlying member method code with example usage: obj.__call__(func) and returns: func