code: def main(
      # fmt: off
      glove_dir: str = typer.Argument(..., help="Directory containing the GloVe build"),
      in_file: str = typer.Argument(..., help="Input file (shuffled cooccurrences)"),
      vocab_file: str = typer.Argument(..., help="Vocabulary file"),
      out_dir: str = typer.Argument(..., help="Path to output directory"),
      n_threads: int = typer.Option(8, "--n-threads", "-t", help="Number of threads"),
      n_iter: int = typer.Option(15, "--n-iter", "-n", help="Number of iterations"),
      x_max: int = typer.Option(10, "--x-max", "-x", help="Parameter specifying cutoff in weighting function"),
      vector_size: int = typer.Option(128, "--vector-size", "-s", help="Dimension of word vector representations"),
      verbose: int = typer.Option(2, "--verbose", "-v", help="Set verbosity: 0, 1, or 2"),
      # fmt: on
  ):
      """
      Step 4: Train the vectors
  
      Expects a file containing the shuffled cooccurrences and a vocab file and
      will output a plain-text vectors file.
  
      Note that this script will call into GloVe and expects you to pass in the
      GloVe build directory (/build if you run the Makefile). The commands will
      also be printed if you want to run them separately.
      """
      output_path = Path(out_dir)
      if not Path(glove_dir).exists():
          msg.fail(
              "Can't find GloVe build directory", glove_dir, exits=1
          )
      if not Path(in_file).exists():
          msg.fail("Can't find input file", in_file, exits=1)
      if not Path(vocab_file).exists():
          msg.fail("Can't find vocab file", vocab_file, exits=1)
      if not output_path.exists():
          output_path.mkdir(parents=True)
          msg.good(f"Created output directory {out_dir}")
      output_file = output_path / f"vectors_glove_{vector_size}dim"
      msg.info("Training vectors")
      cmd = (
          f"{glove_dir}/glove -save-file {output_file} -threads {n_threads} "
          f"-input-file {in_file} -x-max {x_max} -iter {n_iter} "
          f"-vector-size {vector_size} -binary 0 -vocab-file {vocab_file} "
          f"-verbose {verbose}"
      )
      print(cmd)
      train_cmd = os.system(cmd)
      if train_cmd != 0:
          msg.fail("Failed training vectors", exits=1)
      msg.good("Successfully trained vectors")
  
imports: import os
  from pathlib import Path
  from wasabi import msg
  import typer
label_desc: Use image node_id 1 for calling a global function with example usage: main(glove_dir, in_file, vocab_file, out_dir, n_threads, n_iter, x_max, vector_size, verbose) without return types