def METHOD_NAME():
    original_df = DATAFRAME_WITH_COVARIATES.copy()
    splitter = MultiWindowSplitter()
    prediction_length = 7
    train_data, val_data = splitter.split(ts_dataframe=original_df, prediction_length=prediction_length)
    for column in original_df.drop("target", axis=1).columns:
        for item_id in train_data.item_ids:
            train_series = train_data[column].loc[item_id]
            assert (train_series == original_df[column].loc[item_id][: len(train_series)]).all()
        for item_id in val_data.item_ids:
            original_item_id, _, _ = get_original_item_id_and_slice(item_id)
            val_series = val_data[column].loc[item_id]
            assert (val_series == original_df[column].loc[original_item_id][: len(val_series)]).all()