class_docstr: Modified Park test functions for multi-objective multi-fidelity optimization.
  
  (4+1)-dimensional function with domain `[0,1]^5` where the last dimension
  is the fidelity parameter `s`. See [Irshad2021]_ for more details.
  
  The first modified Park function is
  
      P1(x, s)=A*(T1(x,s)+T2(x,s)-B)/22-0.8
  
  The second modified Park function is
  
      P2(x,s)=A*(5-2/3*exp(x1+x2)-x4*sin(x3)*A+x3-B)/4 - 0.7
  
  Here
  
      T_1(x,s) = (x1+0.001*(1-s))/2*sqrt(1+(x2+x3**2)*x4/(x1**2))
  
      T_2(x, s) = (x1+3*x4)*exp(1+sin(x3))
  
  and `A(s)=(0.9+0.1*s)`, `B(s)=0.1*(1-s)`.
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code: def _transform(self, X: Tensor) -> Tensor:
      x1 = X[..., 0]
      x2 = X[..., 1]
      x3 = X[..., 2]
      x4 = X[..., 3]
      s = X[..., 4]
      _x1 = 1 - 2 * (x1 - 0.6) ** 2
      _x2 = x2
      _x3 = 1 - 3 * (x3 - 0.5) ** 2
      _x4 = 1 - (x4 - 0.8) ** 2
      return torch.stack([_x1, _x2, _x3, _x4, s], dim=-1)
  
file_path: botorch/botorch/test_functions/multi_objective_multi_fidelity.py
imports: import math
  import torch
  from botorch.test_functions.base import MultiObjectiveTestProblem
  from torch import Tensor
label_desc: Use image node_id 1 for calling the MOMFPark obj's underlying member method code with example usage: obj._transform(X) and returns: torch