code: def main(args: Namespace) -> None:
      seed(args.seed)
      device = init_from_env()
  
      data_cfg = DataConfig(
          path=PATH,
          block_size=args.block_size,
          train_split=args.train_split,
          truncate=args.truncate,
      )
      train_data, eval_data, dataset = get_datasets(data_cfg)
      train_dataloader = prepare_dataloader(
          train_data, args.batch_size, device
      )
      eval_dataloader = prepare_dataloader(
          eval_data, args.batch_size, device
      )
  
      gpt_cfg = GPTConfig(
          n_layer=args.n_layer,
          n_head=args.n_head,
          n_embd=args.n_embd,
          vocab_size=dataset.vocab_size,
          block_size=dataset.block_size,
          device=str(device),
      )
      module = GPT(gpt_cfg)
  
      path = tempfile.mkdtemp()
      tb_logger = TensorBoardLogger(path)
  
      my_unit = MinGPTUnit(
          tb_logger=tb_logger,
          opt_cfg=OptimizerConfig(
              learning_rate=args.lr, weight_decay=args.weight_decay
          ),
          module=module,
          device=device,
          strategy="ddp",
          log_every_n_steps=args.log_every_n_steps,
          gradient_accumulation_steps=4,
          detect_anomaly=True,
          clip_grad_norm=args.clip_grad_norm,
      )
  
      fit(
          my_unit,
          train_dataloader=train_dataloader,
          eval_dataloader=eval_dataloader,
          max_epochs=args.max_epochs,
          max_steps=args.max_steps,
          max_train_steps_per_epoch=args.max_steps_epoch,
      )
  
imports: import argparse
  import logging
  import tempfile
  from argparse import Namespace
  from typing import Optional, Tuple
  import torch
  from libfb.py import parutil
  from torch.utils.data import random_split
  from torch.utils.data.dataset import Dataset, Subset
  from torchtnt.examples.mingpt.char_dataset import CharDataset, DataConfig
  from torchtnt.examples.mingpt.model import create_optimizer, GPT, GPTConfig, OptimizerConfig
  from torchtnt.framework.auto_unit import AutoUnit, TrainStepResults
  from torchtnt.framework.fit import fit
  from torchtnt.framework.state import State
  from torchtnt.utils import init_from_env, seed, TLRScheduler
  from torchtnt.utils.loggers import TensorBoardLogger
label_desc: Use image node_id 3 for calling a global function with example usage: main(args) without return types