code: def _append_activity_regularizer_loss(
      layer, call_fn_with_losses, activity_regularizer_fn
  ):
      """Appends activity regularizer loss to losses returned by the wrapped fn."""
  
      def fn(inputs, *args, **kwargs):
          outputs, losses = call_fn_with_losses(inputs, *args, **kwargs)
          losses.append(activity_regularizer_fn(outputs))
          return outputs, losses
  
      return _create_call_fn_decorator(layer, fn)
  
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 16 for calling a global function with example usage: _append_activity_regularizer_loss(layer, call_fn_with_losses, activity_regularizer_fn) and returns: _create_call_fn_decorator, outputs,  losses