code: def test_forecast_mtnet(self):
      # TODO hacking to fix a bug
      target_dim = 1
      model = MTNetForecaster(
          target_dim=target_dim,
          feature_dim=self.x_train.shape[-1],
          long_series_num=self.long_num,
          series_length=self.time_step,
      )
      x_train_long, x_train_short = model.preprocess_input(self.x_train)
      x_val_long, x_val_short = model.preprocess_input(self.x_val)
      x_test_long, x_test_short = model.preprocess_input(self.x_test)
  
      model.fit(
          [x_train_long, x_train_short],
          self.y_train,
          validation_data=([x_val_long, x_val_short], self.y_val),
          batch_size=32,
          distributed=False,
      )
      assert model.evaluate([x_val_long, x_val_short], self.y_val)
      predict_result = model.predict([x_test_long, x_test_short])
      assert predict_result.shape == (self.x_test.shape[0], target_dim)
  
file_path: analytics-zoo/pyzoo/test/zoo/chronos/forecaster/test_mtnet_forecaster.py
imports: import pytest
  import numpy
  from zoo.chronos.autots.deprecated.feature.time_sequence import TimeSequenceFeatureTransformer
  import tensorflow
  import pandas
  from zoo.chronos.forecaster.mtnet_forecaster import MTNetForecaster
  from unittest import TestCase
label_desc: Use image node_id 4 for calling the TestChronosModelMTNetForecaster obj's underlying member method code with example usage: obj.test_forecast_mtnet() without return types