code: def main():
      args = parser.parse_args()
      train_data, val_data = create_data()
      x, y = train_data.to_numpy()
      forecaster = TCNForecaster(
          past_seq_len=lookback,
          future_seq_len=horizon,
          input_feature_num=x.shape[-1],
          output_feature_num=y.shape[-1],
          seed=1,
      )
      train_start = time.time()
      forecaster.fit((x, y), validation_data=val_data, epochs=3)
      train_end = time.time()
  
      output = json.dumps(
          {"config": args.name, "train_time": train_end - train_start}
      )
  
      print(f">>>{output}<<<")
  
file_path: BigDL/python/chronos/benchmark/forecaster_training/forecaster_training.py
imports: import time
  import json
  import argparse
  from bigdl.chronos.forecaster import TCNForecaster
  from bigdl.chronos.data import get_public_dataset
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types