code: def layer_postprocess(layer_input, layer_output, hparams):
    
    return layer_prepostprocess(
        layer_input,
        layer_output,
        sequence=hparams.layer_postprocess_sequence,
        dropout_rate=hparams.layer_prepostprocess_dropout,
        norm_type=hparams.norm_type,
        depth=None,
        epsilon=hparams.norm_epsilon,
        dropout_broadcast_dims=comma_separated_string_to_integer_list(
            getattr(hparams, "layer_prepostprocess_dropout_broadcast_dims", "")),
        default_name="layer_postprocess")
docs: Apply layer postprocessing.
  
    See layer_prepostprocess() for details.
  
    A hyperparameters object is passed for convenience.  The hyperparameters
    that may be used are:
  
      layer_postprocess_sequence
      layer_prepostprocess_dropout
      norm_type
      hidden_size
      norm_epsilon
  
    Args:
      layer_input: a Tensor
      layer_output: a Tensor
      hparams: a hyperparameters object.
  
    Returns:
      a Tensor