code: def _get_train_loader(
      self,
      rank: int,
      world_size: int,
  ) -> data_utils.DataLoader:
      sampler = DistributedSampler(
          Bert4RecTrainDataset(
              self.train,
          ),
          num_replicas=world_size,
          rank=rank,
          shuffle=True,
          drop_last=False,
      )
      dataloader = data_utils.DataLoader(
          Bert4RecTrainDataset(
              self.train,
          ),
          batch_size=self.train_batch_size,
          pin_memory=True,
          sampler=sampler,
      )
      return dataloader
  
imports: from typing import Any, Dict, Tuple
  import pandas
  import torch
  import torch.utils.data
  from torch.utils.data.distributed import DistributedSampler
label_desc: Use image node_id 3 for calling the Bert4RecDataloader obj's underlying member method code with example usage: obj._get_train_loader(rank, world_size) and returns: dataloader