code: def train(batch_itr, trainer):
      for batch, is_dummy_batch in batch_itr.train_batch():
          trainer.train_step(batch, is_dummy_batch)
          trainer.valid_step(batch_itr)
  
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 3 for calling a global function with example usage: train(batch_itr, trainer) without return types