class_docstr: MNIST data loader
class_docstr_tok: ["MNIST","data","loader"]
code: def get_train(self):
      return datasets.MNIST(
          self._data_path,
          train=True,
          transform=self._transform,
          download=True,
      )
  
imports: import glob
  import logging
  import os
  from enum import Enum
  import numpy
  import pydicom
  import torch
  from torchvision import datasets, transforms
  from kale.loaddata.dataset_access import DatasetAccess
  from kale.loaddata.mnistm import MNISTM
  from kale.loaddata.multi_domain import MultiDomainAccess, MultiDomainImageFolder
  from kale.loaddata.usps import USPS
  from kale.prepdata.image_transform import get_transform
  from kale.utils.download import download_file_by_url
label_desc: Use image node_id 1 for calling the MNISTDatasetAccess obj's underlying member method code with example usage: obj.get_train() and returns: datasets