class_docstr: Convenience wrapper for sampling a function from a GP prior.
  
  This wrapper implicitly defines the GP sample as a self-updating function by keeping
  track of the evaluated points and respective base samples used during the
  evaluation.
  
  This does not yet support multi-output models.
class_docstr_tok: ["Convenience","wrapper","for","sampling","a","function","from","a","GP","prior",".","This","wrapper","implicitly","defines","the","GP","sample","as","a","self-updating","function","by","keeping","track","of","the","evaluated","points","and","respective","base","samples","used","during","the","evaluation",".","This","does","not","yet","support","multi-output","models","."]
docstr: A `(batch_shape) x n_eval x d`-dim tensor of associated function values (or
  `None` if the sample has never been evaluated).
docstr_tok: ["A","`","(","batch_shape",")","x","n_eval","x","d","`","-dim","tensor","of","associated","function","values","(","or","`","None","`","if","the","sample","has","never","been","evaluated",")","."]
code: def Ys(self) -> Tensor:
      """A `(batch_shape) x n_eval x d`-dim tensor of associated function values (or
      `None` if the sample has never been evaluated).
      """
      try:
          return self._Ys
      except AttributeError:
          return None
  
imports: from __future__ import annotations
  from copy import deepcopy
  from math import pi
  from typing import List, Optional
  import torch
  from botorch.models.converter import batched_to_model_list
  from botorch.models.deterministic import GenericDeterministicModel
  from botorch.models.model import Model, ModelList
  from botorch.models.model_list_gp_regression import ModelListGP
  from botorch.models.multitask import MultiTaskGP
  from botorch.utils.sampling import manual_seed
  from botorch.utils.transforms import is_ensemble
  from gpytorch.kernels import Kernel, MaternKernel, RBFKernel, ScaleKernel
  from linear_operator.utils.cholesky import psd_safe_cholesky
  from torch import Tensor
  from torch.distributions import MultivariateNormal
  from torch.nn import Module
label_desc: Use image node_id 3 for calling the GPDraw obj's underlying member method code with example usage: obj.Ys() and returns: self, None