class_docstr: A Python callable for functions in the TF Runtime.
  
  Provides core functionality for tf.function including:
    - automatic lifecycle management of runtime functions
    - structured inputs (including captures) and structured outputs
    - calls from both eager and graph mode
    - dependency tracking of children functions
    - runtime error interpolation to identify user code stack traces
    - control dependencies (including automatic)
docstr: Cached FunctionDef (not guaranteed to be fresh).
docstr_tok: ["Cached","FunctionDef","(","not","guaranteed","to","be","fresh",")","."]
code: def cached_definition(self) -> function_pb2.FunctionDef:
      """Cached FunctionDef (not guaranteed to be fresh)."""
      if self._cached_definition is None:
          self._cached_definition = self.definition
  
      return self._cached_definition
  
imports: import dataclasses
  import traceback
  import typing
  from typing import Any, Dict, List, Optional, Sequence, Union
  from tensorflow.core.framework import attr_value_pb2
  from tensorflow.core.framework import function_pb2
  from tensorflow.core.framework import graph_debug_info_pb2
  from tensorflow.core.function.polymorphism import function_type
  from tensorflow.python.client import pywrap_tf_session
  from tensorflow.python.eager import context
  from tensorflow.python.eager import record
  from tensorflow.python.eager.polymorphic_function import attributes
  from tensorflow.python.eager.polymorphic_function import function_type_utils
  from tensorflow.python.framework import auto_control_deps_utils
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import error_interpolation
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import function_def_to_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import handle_data_util
  from tensorflow.python.types import core
  from tensorflow.python.util import compat
  from tensorflow.python.util import function_utils
  from tensorflow.python.util import tf_stack
label_desc: Use image node_id 11 for calling the AtomicFunction obj's underlying member method code with example usage: obj.cached_definition() and returns: self