code: def _reset_layer_losses(parent_layer):
      """Resets losses of layer and its sublayers, and returns original losses."""
      losses_dict = {}
      for layer in utils.list_all_layers_and_sublayers(parent_layer):
          losses_dict[layer] = {
              "losses": layer._losses[:],
              "eager_losses": layer._eager_losses[:],
          }
          with utils.no_automatic_dependency_tracking_scope(layer):
              layer._losses = []
              layer._eager_losses = []
      return losses_dict
  
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 7 for calling a global function with example usage: _reset_layer_losses(parent_layer) and returns: losses_dict