class_docstr: Base class for test multi-objective test functions.
  
  TODO: add a pareto distance function that returns the distance
  between a provided point and the closest point on the true pareto front.
class_docstr_tok: ["Base","class","for","test","multi-objective","test","functions",".","TODO",":","add","a","pareto","distance","function","that","returns","the","distance","between","a","provided","point","and","the","closest","point","on","the","true","pareto","front","."]
docstr: Generate `n` pareto optimal points.
docstr_tok: ["Generate","`","n","`","pareto","optimal","points","."]
code: def gen_pareto_front(self, n: int) -> Tensor:
      r"""Generate `n` pareto optimal points."""
      raise NotImplementedError
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import List, Tuple, Union
  import torch
  from botorch.exceptions.errors import InputDataError
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 3 for calling the MultiObjectiveTestProblem obj's underlying member method code with example usage: obj.gen_pareto_front(n) without return types