code: def make_serialized_model(seq_model, space, vocab_size):
      srl = space_serializer.create(space, vocab_size)
      return serialization_utils.SerializedModel(
          functools.partial(seq_model, vocab_size=vocab_size),
          observation_serializer=srl,
          action_serializer=srl,
          significance_decay=0.7,
      )
  
imports: import functools
  import io
  from unittest import mock
  from absl.testing import absltest
  from absl.testing import parameterized
  import gym
  import numpy
  from trax import models
  from trax import test_utils
  from trax.data import inputs
  from trax.layers import test_utils
  from trax.rl import serialization_utils
  from trax.rl import space_serializer
  from trax.supervised import callbacks
  from trax.supervised import lr_schedules
  from trax.supervised import trainer_lib
  from trax.supervised import training
label_desc: Use image node_id 5 for calling a global function with example usage: make_serialized_model(seq_model, space, vocab_size) and returns: serialization_utils