code: def _deserialize_metric(metric_config):
      """Deserialize metrics, leaving special strings untouched."""
      from tensorflow.python.keras import (
          metrics as metrics_module,
      )  # pylint:disable=g-import-not-at-top
  
      if metric_config in ["accuracy", "acc", "crossentropy", "ce"]:
          # Do not deserialize accuracy and cross-entropy strings as we have special
          # case handling for these in compile, based on model output shape.
          return metric_config
      return metrics_module.deserialize(metric_config)
  
imports: import collections
  import copy
  import os
  from tensorflow.python.eager import def_function
  from tensorflow.python.keras import backend
  from tensorflow.python.keras import losses
  from tensorflow.python.keras import optimizer_v1
  from tensorflow.python.keras import optimizers
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.keras.utils import version_utils
  from tensorflow.python.keras.utils.io_utils import ask_to_proceed_with_overwrite
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.util import nest
label_desc: Use image node_id 10 for calling a global function with example usage: _deserialize_metric(metric_config) and returns: metrics_module, metric_config