code: def main(args):
      """
      Main function
      Args:
          args: output of argparse with all input arguments
  
      Returns:
          None
      """
      n_features = 2
      hidden_sizes = [args.nhid] * args.levels
      kernel_size = args.ksize
      dropout = args.dropout
      seq_len = args.seq_len
      n_train = 50000
      n_val = 1000
      batch_size = args.batch_size
      n_epochs = args.epochs
      num_iterations = int(n_train * n_epochs * 1.0 / batch_size)
      results_dir = os.path.abspath(args.results_dir)
  
      adding_dataset = Adding(
          seq_len=seq_len, n_train=n_train, n_test=n_val
      )
  
      model = TCNForAdding(
          seq_len,
          n_features,
          hidden_sizes,
          kernel_size=kernel_size,
          dropout=dropout,
      )
  
      model.build_train_graph(
          args.lr, max_gradient_norm=args.grad_clip_value
      )
  
      model.run(
          adding_dataset,
          num_iterations=num_iterations,
          log_interval=args.log_interval,
          result_dir=results_dir,
      )
  
imports: import argparse
  import os
  from examples.word_language_model_with_tcn.adding_problem.adding_model import TCNForAdding
  from examples.word_language_model_with_tcn.toy_data.adding import Adding
  from nlp_architect.utils.io import validate_parent_exists, check_size
label_desc: Use image node_id 1 for calling a global function with example usage: main(args) without return types