code: def get_tsdata():
      name = "network_traffic"
      path = "~/.chronos/dataset"
      tsdata_train, _, tsdata_test = get_public_dataset(
          name, path, redownload=False, with_split=True, test_ratio=0.1
      )
      minmax = MinMaxScaler()
      for tsdata in [tsdata_train, tsdata_test]:
          tsdata.gen_dt_feature(
              one_hot_features=["HOUR", "WEEK"]
          ).impute("last").scale(
              minmax, fit=tsdata is tsdata_train
          ).roll(
              lookback=100, horizon=10
          )
      return tsdata_train, tsdata_test
  
file_path: analytics-zoo/pyzoo/zoo/chronos/examples/distributed/distributed_training_network_traffic.py
imports: import argparse
  import numpy
  from sklearn.preprocessing import MinMaxScaler
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca import init_orca_context, stop_orca_context
  from zoo.chronos.forecaster.seq2seq_forecaster import Seq2SeqForecaster
  from zoo.chronos.data.repo_dataset 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_test