code: def main(args: Namespace) -> None:
      # seed the RNG for better reproducibility. see docs https://pytorch.org/docs/stable/notes/randomness.html
      seed(args.seed)
  
      # device and process group initialization
      device = init_from_env()
  
      path = tempfile.mkdtemp()
      tb_logger = TensorBoardLogger(path)
  
      module = prepare_module(args.input_dim, device)
      train_accuracy = BinaryAccuracy(device=device)
      eval_accuracy = BinaryAccuracy(device=device)
  
      my_unit = MyUnit(
          tb_logger=tb_logger,
          train_accuracy=train_accuracy,
          eval_accuracy=eval_accuracy,
          module=module,
          device=device,
          strategy="ddp",
          log_every_n_steps=args.log_every_n_steps,
          precision=args.precision,
          gradient_accumulation_steps=4,
          detect_anomaly=True,
          clip_grad_norm=1.0,
      )
  
      train_dataloader = prepare_dataloader(
          args.num_batches_per_epoch,
          args.input_dim,
          args.batch_size,
          device,
      )
      eval_dataloader = prepare_dataloader(
          args.num_batches_per_epoch,
          args.input_dim,
          args.batch_size,
          device,
      )
  
      fit(
          my_unit,
          train_dataloader=train_dataloader,
          eval_dataloader=eval_dataloader,
          max_epochs=args.max_epochs,
      )
  
imports: import argparse
  import logging
  import tempfile
  import uuid
  from argparse import Namespace
  from typing import Literal, Optional, Tuple, Union
  import torch
  import torch.nn
  from torch.distributed import launcher
  from torch.utils.data.dataset import Dataset, TensorDataset
  from torcheval.metrics import BinaryAccuracy
  from torchtnt.framework.auto_unit import AutoUnit, Strategy, SWAParams, TrainStepResults
  from torchtnt.framework.fit import fit
  from torchtnt.framework.state import EntryPoint, State
  from torchtnt.utils import init_from_env, seed, TLRScheduler
  from torchtnt.utils.loggers import TensorBoardLogger
  from torchtnt.utils.prepare_module import ActivationCheckpointParams, TorchCompileParams
label_desc: Use image node_id 4 for calling a global function with example usage: main(args) without return types