code: def get_trained_forecaster(train_data, val_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,
      )
      forecaster.fit((x, y), validation_data=val_data, epochs=3)
      return forecaster
  
file_path: BigDL/python/chronos/benchmark/forecaster_inference/forecaster_inference.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: get_trained_forecaster(train_data, val_data) and returns: forecaster