code: def _parse_model_supervised(
      consumer: Model, dataset: SupervisedDataset, **ignore: Any
  ) -> Dict[str, Tensor]:
      parsed_data = {"train_X": dataset.X, "train_Y": dataset.Y}
      if dataset.Yvar is not None:
          parsed_data["train_Yvar"] = dataset.Yvar
      return parsed_data
  
file_path: botorch/botorch/models/utils/parse_training_data.py
imports: from __future__ import annotations
  from typing import Any, Dict, Type
  import torch
  from botorch.models.model import Model
  from botorch.models.pairwise_gp import PairwiseGP
  from botorch.utils.datasets import RankingDataset, SupervisedDataset
  from botorch.utils.dispatcher import Dispatcher
  from torch import Tensor
label_desc: Use image node_id 3 for calling a global function with example usage: _parse_model_supervised(consumer, dataset) and returns: parsed_data