class_docstr: This is a multi-task dataset that is constructed from the datasets of
  individual tasks. It offers functionality to combine parts of individual
  datasets to construct the inputs necessary for the `MultiTaskGP` models.
  
  The datasets of individual tasks are allowed to represent different sets
  of features. When there are heterogeneous feature sets, calling
  `MultiTaskDataset.X` will result in an error.
docstr: Concatenates Yvars of the datasets if they exist.
code: def Yvar(self) -> Optional[Tensor]:
      """Concatenates Yvars of the datasets if they exist."""
      all_Yvars = [ds.Yvar for ds in self.datasets.values()]
      return (
          None if all_Yvars[0] is None else torch.cat(all_Yvars, dim=0)
      )
  
imports: from __future__ import annotations
  import collections
  import warnings
  from typing import Any, Dict, List, Optional, Union
  import torch
  from botorch.exceptions.errors import InputDataError, UnsupportedError
  from botorch.utils.containers import BotorchContainer, SliceContainer
  from torch import long, ones, Tensor
label_desc: Use image node_id 6 for calling the MultiTaskDataset obj's underlying member method code with example usage: obj.Yvar() and returns: unknown