code: def _create_call_fn_decorator(layer, wrapped_call):
      call_fn = _get_layer_call_method(layer)
      fn, arg_spec = utils.maybe_add_training_arg(
          call_fn,
          wrapped_call,
          layer._expects_training_arg,  # pylint: disable=protected-access
          default_training_value=False,
      )
      return tf_decorator.make_decorator(
          target=call_fn, decorator_func=fn, decorator_argspec=arg_spec
      )
  
imports: import functools
  import threading
  import weakref
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_spec
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.engine import input_spec
  from tensorflow.python.keras.mixed_precision import autocast_variable
  from tensorflow.python.keras.saving import saving_utils
  from tensorflow.python.keras.saving.saved_model import constants
  from tensorflow.python.keras.saving.saved_model import load
  from tensorflow.python.keras.saving.saved_model import serialized_attributes
  from tensorflow.python.keras.saving.saved_model import utils
  from tensorflow.python.keras.utils import tf_contextlib
  from tensorflow.python.keras.utils import tf_inspect
  from tensorflow.python.keras.utils import tf_utils
  from tensorflow.python.keras.utils import version_utils
  from tensorflow.python.keras.utils.generic_utils import LazyLoader
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.trackable import data_structures
  from tensorflow.python.util import nest
  from tensorflow.python.util import tf_decorator
label_desc: Use image node_id 17 for calling a global function with example usage: _create_call_fn_decorator(layer, wrapped_call) and returns: tf_decorator