class_docstr: Example:
      >>> #The dataset is split into x_train, x_val, x_test, y_train, y_val, y_test
      >>> model = MTNetForecaster(target_dim=1,
                          feature_dim=x_train.shape[-1],
                          long_series_num=6,
                          series_length=2
                          )
      >>> x_train_long, x_train_short = model.preprocess_input(x_train)
      >>> x_val_long, x_val_short = model.preprocess_input(x_val)
      >>> x_test_long, x_test_short = model.preprocess_input(x_test)
      >>> model.fit([x_train_long, x_train_short],
            y_train,
            validation_data=([x_val_long, x_val_short], y_val),
            batch_size=32,
            distributed=False)
      >>> predict_result = [x_test_long, x_test_short]
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docstr: build a MTNet model in tf.keras
  
  :return: a tf.keras MTNet model
docstr_tok: ["build","a","MTNet","model","in","tf.keras",":","return",":","a","tf.keras","MTNet","model"]
code: def _build(self):
      """
      build a MTNet model in tf.keras
  
      :return: a tf.keras MTNet model
      """
      # TODO change this function call after MTNet fixes
      self.internal = MTNetKerasModel(
          check_optional_config=self.check_optional_config
      )
      self.internal.apply_config(config=self.model_config)
      return self.internal.build(config=self.model_config)
  
imports: from zoo.chronos.model.MTNet_keras import MTNetKeras
  from zoo.chronos.forecaster.tfpark_forecaster import TFParkForecaster
label_desc: Use image node_id 2 for calling the MTNetForecaster obj's underlying member method code with example usage: obj._build() and returns: self