code: def test_multi_domain_datasets(
      weight_type, datasize_type, download_path
  ):
      source, target, num_channels = DigitDataset.get_source_target(
          DigitDataset(SOURCES[0]),
          DigitDataset(TARGETS[0]),
          download_path,
      )
      assert num_channels == 3
      assert isinstance(source, DigitDatasetAccess)
      assert isinstance(target, DigitDatasetAccess)
  
      dataset = MultiDomainDatasets(
          source,
          target,
          config_weight_type=weight_type,
          config_size_type=datasize_type,
      )
      assert isinstance(dataset, DomainsDatasetBase)
  
file_path: pykale/tests/loaddata/test_image_access.py
imports: import pytest
  import torch
  from numpy import testing
  from yacs.config import CfgNode
  from kale.loaddata.dataset_access import get_class_subset
  from kale.loaddata.image_access import DigitDataset, DigitDatasetAccess, get_cifar, ImageAccess
  from kale.loaddata.multi_domain import DomainsDatasetBase, MultiDomainAdapDataset, MultiDomainDatasets
label_desc: Use image node_id 5 for calling a global function with example usage: test_multi_domain_datasets(weight_type, datasize_type, download_path) without return types