class_docstr: Trains a model that predicts future time sequence from past sequence.
  Past sequence should be > 1. Future sequence can be > 1.
  For example, predict the next 2 data points from past 5 data points.
  Output have only one target value (a scalar) for each data point in the sequence.
  Input can have more than one features (value plus several features)
  Example usage:
      tsp = TimeSequencePredictor()
      tsp.fit(input_df)
      result = tsp.predict(test_df)
code: def get_model_builder(self):
      from zoo.chronos.autots.deprecated.model.time_sequence import (
          TSModelBuilder,
      )
  
      model_builder = TSModelBuilder(
          dt_col=self.dt_col,
          target_cols=self.target_col,
          future_seq_len=self.future_seq_len,
          extra_features_col=self.extra_features_col,
          drop_missing=self.drop_missing,
      )
      return model_builder
  
file_path: analytics-zoo/pyzoo/zoo/chronos/autots/deprecated/regression/time_sequence_predictor.py
imports: from zoo.chronos.autots.deprecated.regression.base_predictor import BasePredictor
  from zoo.chronos.utils import deprecated
label_desc: Use image node_id 2 for calling the TimeSequencePredictor obj's underlying member method code with example usage: obj.get_model_builder() and returns: model_builder