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)
      return tsdata_train, tsdata_test
  
imports: import time
  import argparse
  import numpy
  from sklearn.preprocessing import MinMaxScaler
  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