code: def serialize(policy):
      if _policy_equivalent_to_dtype(policy):
          # We return either None or the policy name for compatibility with older
          # versions of Keras. If the policy name is returned, it is a dtype string
          # such as 'float32'.
          return None if policy.name == "_infer" else policy.name
      return generic_utils.serialize_keras_object(policy)
  
imports: import contextlib
  from tensorflow.python.framework import dtypes
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import base_layer_utils
  from tensorflow.python.keras.mixed_precision import device_compatibility_check
  from tensorflow.python.keras.mixed_precision import loss_scale
  from tensorflow.python.keras.utils import generic_utils
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training.experimental import mixed_precision_global_state
label_desc: Use image node_id 7 for calling a global function with example usage: serialize(policy) and returns: generic_utils, unknown