class_docstr: This class is the Base class for pythae's dataset
  
  A ``__getitem__`` is redefined and outputs a python dictionnary
  with the keys corresponding to `data` and `labels`.
  This Class should be used for any new data sets.
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docstr: Generates one sample of data
  
  Args:
      index (int): The index of the data in the Dataset
  
  Returns:
      (dict): A dictionnary with the keys 'data' and 'labels' and corresponding
      torch.Tensor
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code: def __getitem__(self, index):
      """Generates one sample of data
  
      Args:
          index (int): The index of the data in the Dataset
  
      Returns:
          (dict): A dictionnary with the keys 'data' and 'labels' and corresponding
          torch.Tensor
      """
      # Select sample
      X = self.data[index]
      y = self.labels[index]
  
      return DatasetOutput(data=X, labels=y)
  
file_path: benchmark_VAE/src/pythae/data/datasets.py
imports: from collections import OrderedDict
  from typing import Any, Tuple
  import torch
  from torch.utils.data import Dataset
  from torch.utils.data._utils.collate import default_collate
label_desc: Use image node_id 3 for calling the BaseDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: DatasetOutput