code: def create_data():
      lookback = 5
      horizon = 1
  
      def get_data(num_samples):
          values = np.random.randn(num_samples)
          df = pd.DataFrame(
              {
                  "timestep": pd.date_range(
                      start="2010-01-01", freq="m", periods=num_samples
                  ),
                  "value 1": values,
                  "value 2": values,
                  "value 3": values,
                  "value 4": values,
              }
          )
          return df
  
      tsdata_train = TSDataset.from_pandas(
          get_data(64),
          target_col=["value 1", "value 2", "value 3", "value 4"],
          dt_col="timestep",
          with_split=False,
      )
      tsdata_test = TSDataset.from_pandas(
          get_data(16),
          target_col=["value 1", "value 2", "value 3", "value 4"],
          dt_col="timestep",
          with_split=False,
      )
      for tsdata in [tsdata_train, tsdata_test]:
          tsdata.roll(lookback=lookback, horizon=horizon)
      return tsdata_train, tsdata_test
  
file_path: BigDL/python/chronos/test/bigdl/chronos/forecaster/tf/test_mtnet_forecaster.py
imports: import pytest
  import numpy
  import pandas
  from bigdl.chronos.data import TSDataset
  from bigdl.chronos.utils import LazyImport
  from unittest import TestCase
  from test.bigdl.chronos import op_tf2
label_desc: Use image node_id 1 for calling a global function with example usage: create_data() and returns: tsdata_train,  tsdata_test, df