code: def tmp():
      fs_args, ds_config = gen_ds_fairseq_arg()
      set_seed(fs_args.seed)
      task = tasks.setup_task(fs_args)
      trainer = DsFairseqTrainer(fs_args, ds_config, task)
      batch_itr = BatchIterator(fs_args, task)
      for epoch in batch_itr.train_epoch():
          train(batch_itr, trainer)
          log_dist(
              f'Finish epoch {epoch}, \
              {view_log(metrics.get_smoothed_values("train"))}',
              [0],
          )
          metrics.reset_meters("train")
  
imports: import math
  import torch
  from torch import nn
  import torch.distributed
  import deepspeed
  from deepspeed.utils import log_dist
  from fairseq import tasks, distributed_utils
  from fairseq.logging import metrics
  from ds_fairseq_data import BatchIterator
  from ds_fairseq_argument import gen_ds_fairseq_arg
label_desc: Use image node_id 5 for calling a global function with example usage: tmp() without return types