code: def __getitem__(self, index: int) -> Tuple:
      src_index = np.random.choice(self._source_size)
      tgt_index = index
      src = (
          None
          if self.source_dataset is None
          else self.source_dataset[src_index]
      )
      tgt = (
          None
          if self.target_dataset is None
          else self.target_dataset[tgt_index]
      )
      if src is None:
          src = tuple([None] * len(tgt))
      if tgt is None:
          tgt = tuple([None] * len(src))
      return sum(zip(src, tgt), ())
  
imports: from typing import Optional, Tuple, List, Union
  from itertools import product
  from pathlib import Path
  from torch.utils.data import Dataset
  from joblib import Parallel, delayed
  from tqdm import tqdm
  from torch import Tensor
  import torch
  import pandas
  import numpy
  from tslib.dataset import TimeSeries, TimeSeriesCorpus, WindowsDataset, MetaDataset
  from data import SeasonalReader, FourierSignalReader, FusedSeasonalSignalReader, RandomSeasonalSignalReader, TrendFourierSignalReader, GluonTSJsonReader
label_desc: Use image node_id 3 for calling the DomAdaptDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: sum