code: def _write_header(log_path, args):
      rows = [
          [
              f"# torch: {torch.__version__}",
          ],
          [
              f"# torchaudio: {torchaudio.__version__}",
          ],
      ]
      rows.append(["# arguments"])
      for key, item in vars(args).items():
          rows.append([f"#   {key}: {item}"])
  
      dist_utils.write_csv_on_master(log_path, *rows)
  
file_path: audio/examples/source_separation/conv_tasnet/train.py
imports: import argparse
  import pathlib
  import time
  import conv_tasnet
  import torch
  import torchaudio
  import torchaudio.models
  from utils import dist_utils
  from utils.dataset import utils
label_desc: Use image node_id 4 for calling a global function with example usage: _write_header(log_path, args) without return types