code: def mnist_dataloader_train(seed_setup):
      return load_mnist_dataset(
          train=True, object_type="DataLoader", shuffle=False
      )
  
imports: import pathlib
  import numpy
  import pytest
  import torch
  from torch.utils.data import DataLoader, Dataset
  from deepchecks.vision.context import Context
  from deepchecks.vision.datasets.classification.mnist_torch import collate_without_model
  from deepchecks.vision.datasets.classification.mnist_torch import deepchecks_collate
  from deepchecks.vision.datasets.classification.mnist_torch import load_dataset
  from deepchecks.vision.datasets.classification.mnist_torch import load_model
  from deepchecks.vision.datasets.detection import coco_tensorflow
  from deepchecks.vision.datasets.detection.coco_torch import collate_without_model
  from deepchecks.vision.datasets.detection.coco_torch import load_dataset
  from deepchecks.vision.datasets.segmentation.segmentation_coco import load_dataset
  from deepchecks.vision.utils.test_utils import replace_collate_fn_dataloader, replace_collate_fn_visiondata, un_normalize_batch
  from deepchecks.vision.vision_data import TaskType, VisionData
  from deepchecks.vision.vision_data.batch_wrapper import BatchWrapper
  from deepchecks.vision.vision_data.utils import set_seeds
label_desc: Use image node_id 5 for calling a global function with example usage: mnist_dataloader_train(seed_setup) and returns: load_mnist_dataset