code: def get_ts_df():
      sample_num = np.random.randint(100, 200)
      train_df = pd.DataFrame(
          {
              "datetime": pd.date_range("1/1/2019", periods=sample_num),
              "value 1": np.random.randn(sample_num),
              "value 2": np.random.randn(sample_num),
              "id": np.array(["00"] * sample_num),
              "extra feature 1": np.random.randn(sample_num),
              "extra feature 2": np.random.randn(sample_num),
          }
      )
      return train_df
  
imports: import numpy
  from unittest import TestCase
  import pytest
  from bigdl.chronos.utils import LazyImport
  import os
  import pandas
  import numpy
  from bigdl.chronos.data import TSDataset
  from ..None import op_torch, op_inference
label_desc: Use image node_id 3 for calling a global function with example usage: get_ts_df() and returns: train_df