code: def main():
      parser = argparse.ArgumentParser(
          description="Tool to create a classifier for helping to categorize commits"
      )
  
      parser.add_argument(
          "--train", action="store_true", help="Train a new classifier"
      )
      parser.add_argument(
          "--commit_data_folder", default="results/classifier/"
      )
      parser.add_argument(
          "--save_path",
          default="results/classifier/commit_classifier.pt",
      )
      parser.add_argument(
          "--regen_data",
          action="store_true",
          help="Regenerate the training data, helps if labeled more examples and want to re-train.",
      )
      parser.add_argument(
          "--resample",
          action="store_true",
          help="Resample the training data to be balanced. (Only works if imblearn is installed.)",
      )
      args = parser.parse_args()
  
      if args.train:
          train(
              Path(args.save_path),
              Path(args.commit_data_folder),
              args.regen_data,
              args.resample,
          )
          return
  
      print(
          "Currently this file only trains a new classifier please pass in --train to train a new classifier"
      )
  
imports: import argparse
  import math
  import pickle
  import random
  from dataclasses import dataclass
  from itertools import chain
  from pathlib import Path
  from typing import Dict, List
  import common
  import pandas
  import torch
  import torch.nn
  import torch.nn.functional
  import torchtext
  from torchtext.functional import to_tensor
  from tqdm import tqdm
label_desc: Use image node_id 13 for calling a global function with example usage: main() without return types