code: def load_datasets(self):
      self.dataset_loader = MultiDataModuleNumbersTestObject(
          config=self.config, num_data=self.num_data
      )
      self.dataset_loader.seed_sampler = MagicMock(return_value=None)
      self.dataset_loader.prepare_batch = lambda x: SampleList(x)
  
      self.train_loader = self.dataset_loader.train_dataloader()
      self.val_loader = self.dataset_loader.val_dataloader()
      self.test_loader = self.dataset_loader.test_dataloader()
  
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 2 for calling the TrainerTrainingLoopMock obj's underlying member method code with example usage: obj.load_datasets() without return types