code: def _get_dataloader(self, dataset_type="train"):
      dataset = NumbersDataset(
          self._num_data, always_one=True, dataset_type=dataset_type
      )
      return torch.utils.data.DataLoader(
          dataset=dataset,
          batch_size=self.batch_size,
          shuffle=False,
          num_workers=1,
          drop_last=False,
      )
  
imports: import functools
  from unittest.mock import MagicMock
  import torch
  from mmf.common.registry import registry
  from mmf.common.sample import SampleList
  from mmf.datasets.lightning_multi_datamodule import LightningMultiDataModule
  from mmf.datasets.mmf_dataset_builder import MMFDatasetBuilder
  from mmf.datasets.multi_datamodule import MultiDataModule
  from mmf.trainers.mmf_trainer import MMFTrainer
  from omegaconf import OmegaConf
  from tests.test_utils import NumbersDataset
label_desc: Use image node_id 5 for calling the LightningMultiDataModuleNumbersTestObject obj's underlying member method code with example usage: obj._get_dataloader(dataset_type) and returns: torch