code: def test_when_mw_model_trained_then_oof_predictions_and_stats_are_saved(
      temp_model_path, prediction_length, num_val_windows
  ):
      val_splitter = ExpandingWindowSplitter(
          prediction_length=prediction_length,
          num_val_windows=num_val_windows,
      )
      mw_model = get_multi_window_deepar(
          path=temp_model_path,
          prediction_length=prediction_length,
          freq=DUMMY_TS_DATAFRAME.freq,
      )
      mw_model.fit(
          train_data=DUMMY_TS_DATAFRAME, val_splitter=val_splitter
      )
  
      assert len(mw_model.get_oof_predictions()) == num_val_windows
      for oof_pred in mw_model.get_oof_predictions():
          assert (
              len(oof_pred)
              == prediction_length * DUMMY_TS_DATAFRAME.num_items
          )
      assert mw_model.val_score is not None
      assert mw_model.predict_time is not None
  
file_path: autogluon/timeseries/tests/unittests/models/test_multi_window_model.py
imports: import os
  import shutil
  import tempfile
  import pytest
  from autogluon.timeseries.models import DeepARModel, ETSModel
  from autogluon.timeseries.models.multi_window import MultiWindowBacktestingModel
  from autogluon.timeseries.splitter import ExpandingWindowSplitter
  from ..common import DUMMY_TS_DATAFRAME, dict_equal_primitive
label_desc: Use image node_id 3 for calling a global function with example usage: test_when_mw_model_trained_then_oof_predictions_and_stats_are_saved(temp_model_path, prediction_length, num_val_windows) without return types