code: def TimeSeriesModel(
      seq_model,
      low=0.0,
      high=1.0,
      precision=2,
      vocab_size=64,
      significance_decay=0.7,
      mode="train",
  ):
      """Simplified constructor for SerializedModel, for time series prediction."""
      # Model scalar time series.
      obs_srl = space_serializer.BoxSpaceSerializer(
          space=gym.spaces.Box(shape=(), low=low, high=high),
          vocab_size=vocab_size,
          precision=precision,
      )
      # Artifact of the fact that we must provide some actions.
      # TODO(pkozakowski): Remove this requirement.
      act_srl = space_serializer.DiscreteSpaceSerializer(
          space=gym.spaces.Discrete(n=1), vocab_size=1
      )
      seq_model = functools.partial(seq_model, vocab_size=vocab_size)
      return SerializedModel(
          seq_model, obs_srl, act_srl, significance_decay, mode
      )
  
imports: import functools
  import gym
  import numpy
  from trax import layers
  from trax.fastmath import numpy
  from trax.rl import space_serializer
label_desc: Use image node_id 6 for calling a global function with example usage: TimeSeriesModel(seq_model, low, high, precision, vocab_size, significance_decay, mode) and returns: SerializedModel