code: def get_digit_transform(dataset: "DigitDataset", n_channels):
      transform_names = {
          (DigitDataset.MNIST, 1): "mnist32",
          (DigitDataset.MNIST, 3): "mnist32rgb",
          (DigitDataset.MNIST_RGB, 3): "mnist32rgb",
          (DigitDataset.MNISTM, 3): "mnistm",
          (DigitDataset.USPS, 1): "usps32",
          (DigitDataset.USPS, 3): "usps32rgb",
          (DigitDataset.USPS_RGB, 3): "usps32rgb",
          (DigitDataset.SVHN, 3): "svhn",
      }
  
      return transform_names[(dataset, n_channels)]
  
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 2 for calling the DigitDataset obj's underlying member method code with example usage: obj.get_digit_transform(dataset, n_channels) and returns: transform_names