code: def create_tsdataset(roll=True):
      from bigdl.chronos.data import TSDataset
      import pandas as pd
  
      timeseries = pd.date_range(
          start="2020-01-01", freq="D", periods=1000
      )
      df = pd.DataFrame(
          np.random.rand(1000, 2),
          columns=["value1", "value2"],
          index=timeseries,
          dtype=np.float32,
      )
      df.reset_index(inplace=True)
      df.rename(columns={"index": "timeseries"}, inplace=True)
      train, valid, test = TSDataset.from_pandas(
          df=df,
          dt_col="timeseries",
          target_col=["value1", "value2"],
          val_ratio=0.1,
          with_split=True,
      )
      if roll:
          for tsdata in [train, valid, test]:
              tsdata.roll(lookback=24, horizon=5)
      return train, valid, test
  
imports: import pytest
  import tempfile
  import os
  from unittest import TestCase
  import numpy
  from bigdl.chronos.utils import LazyImport
  from test.bigdl.chronos import op_tf2, op_distributed, op_inference
label_desc: Use image node_id 2 for calling a global function with example usage: create_tsdataset(roll) and returns: train,  valid,  test