code: def parse_args():
      # Parse command line arguments
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--tpu", type=str, help="Name of TPU to train on."
      )
      parser.add_argument(
          "--tpu_region", type=str, help="Region of TPU to train on."
      )
      parser.add_argument("--preemptible", action="store_true")
  
      parser.add_argument(
          "--config",
          type=str,
          default=None,
          help="Config file location",
      )
  
      parser.add_argument(
          "--new",
          action="store_true",
          help="If set, deletes previous checkpoint, if it exists, and "
          "starts a new training run",
      )
  
      parser.add_argument(
          "--version",
          type=int,
          default=1,
          help="Choose which model version to use",
      )
  
      args = parser.parse_args()
      return args
  
file_path: mesh-transformer-jax/train.py
imports: import argparse
  import json
  import time
  import numpy
  import wandb
  from tqdm import tqdm
  from mesh_transformer.build_model import build_model
  from lm_eval import evaluator, tasks
  from tasks.eval_harness import EvalHarnessAdaptor
  from tfrecord_loader import TFRecordNewInputs
  import multiprocessing
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args