class_docstr: Evaluates serialized sequence prediction models.
  
  Example: time series prediction. We can serialize a time series into
  a sequence of discrete tokens and model this sequence using an autoregressive
  sequence model, such as Transformer - see
  `trax.rl.serialization_utils.SerializedModel`. Then we can use this callback
  to evaluate long-horizon predictions of such a model.
code: def on_step_begin(self, step):
      pass
  
imports: import collections
  import os
  import gin
  import numpy
  from trax import jaxboard
  from trax import layers
  from trax import shapes
  from trax.rl import serialization_utils
  from trax.supervised import decoding
label_desc: Use image node_id 4 for calling the SerializedModelEvaluation obj's underlying member method code with example usage: obj.on_step_begin(step) without return types