code: def __len__(self):
      if self.rgb:
          source_ds = self._rgb_source_by_split["train"]
          target_ds = self._rgb_target_by_split["train"]
      if self.flow:
          source_ds = self._flow_source_by_split["train"]
          target_ds = self._flow_target_by_split["train"]
  
      if self._labeled_target_by_split is None:
          return DatasetSizeType.get_size(
              self._size_type, source_ds, target_ds
          )
      else:
          labeled_target_ds = self._labeled_target_by_split["train"]
          return DatasetSizeType.get_size(
              self._size_type, source_ds, labeled_target_ds, target_ds
          )
  
file_path: pykale/kale/loaddata/video_multi_domain.py
imports: import logging
  import numpy
  from sklearn.utils import check_random_state
  from kale.loaddata.dataset_access import get_class_subset
  from kale.loaddata.multi_domain import DatasetSizeType, MultiDomainDatasets, WeightingType
  from kale.loaddata.sampler import FixedSeedSamplingConfig, MultiDataLoader
  from kale.loaddata.video_access import get_image_modality
label_desc: Use image node_id 4 for calling the VideoMultiDomainDatasets obj's underlying member method code with example usage: obj.__len__() and returns: DatasetSizeType, DatasetSizeType