code: def get_tsdata():
      name = "nyc_taxi"
      tsdata_train, tsdata_val, tsdata_test = get_public_dataset(name)
      stand = StandardScaler()
      for tsdata in [tsdata_train, tsdata_val, tsdata_test]:
          tsdata.gen_dt_feature(
              one_hot_features=["HOUR", "WEEK"]
          ).impute("last").scale(stand, fit=tsdata is tsdata_train)
      return tsdata_train, tsdata_val, tsdata_test
  
file_path: BigDL/python/chronos/example/onnx/onnx_autotsestimator_nyc_taxi.py
imports: import time
  import argparse
  import numpy
  from sklearn.preprocessing import StandardScaler
  from bigdl.orca import init_orca_context, stop_orca_context
  from bigdl.chronos.autots.autotsestimator import AutoTSEstimator
  from bigdl.chronos.data import get_public_dataset
label_desc: Use image node_id 1 for calling a global function with example usage: get_tsdata() and returns: tsdata_train,  tsdata_val,  tsdata_test