code: def init_train(
      self,
      train_dataset: paddle.io.Dataset,
      batch_size: int = 1,
      num_workers: int = 0,
  ) -> tuple:
      use_gpu = True
      place = (
          paddle.CUDAPlace(ParallelEnv().dev_id)
          if use_gpu
          else paddle.CPUPlace()
      )
      paddle.disable_static(place)
  
      batch_sampler = paddle.io.DistributedBatchSampler(
          train_dataset,
          batch_size=batch_size,
          shuffle=True,
          drop_last=False,
      )
      loader = paddle.io.DataLoader(
          train_dataset,
          batch_sampler=batch_sampler,
          places=place,
          num_workers=num_workers,
          return_list=True,
      )
      return batch_sampler, loader
  
file_path: PaddleHub/demo/autoaug/paddlehub_utils/trainer.py
imports: import os
  from collections import defaultdict
  import paddle
  from paddle.distributed import ParallelEnv
  from paddlehub.finetune.trainer import Trainer
  from paddlehub.utils.log import logger
  from paddlehub.utils.utils import Timer
label_desc: Use image node_id 3 for calling the CustomTrainer obj's underlying member method code with example usage: obj.init_train(train_dataset, batch_size, num_workers) and returns: batch_sampler,  loader