code: def _extract_outputs_from_fn(
      layer, call_and_return_conditional_losses
  ):
      """Returns a function that returns only call function outputs."""
      if isinstance(layer, keras_load.RevivedLayer):
          return (
              layer.keras_api.__call__
          )  # pylint: disable=protected-access
  
      def call(inputs, *args, **kwargs):
          return call_and_return_conditional_losses(
              inputs, *args, **kwargs
          )[0]
  
      return _create_call_fn_decorator(layer, call)
  
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 15 for calling a global function with example usage: _extract_outputs_from_fn(layer, call_and_return_conditional_losses) and returns: _create_call_fn_decorator, layer, call_and_return_conditional_losses