code: def __init__(self, train_x, train_y):
      likelihood = gpytorch.likelihoods.GaussianLikelihood()
      super().__init__(train_x, train_y, likelihood)
      self.mean_module = gpytorch.means.ZeroMean()
      self.covar_module = gpytorch.kernels.ScaleKernel(
          RFFKernel(active_dims=[0], num_samples=10)
          + MaternKernel(nu=2.5, active_dims=[1, 2])
      )
  
imports: import math
  import unittest
  import linear_operator
  import torch
  import gpytorch
  from gpytorch.kernels import LinearKernel, MaternKernel, RBFKernel, RFFKernel
label_desc: Use image node_id 1 to create a new _TestModel object from inherited base classes: gpytorch.models with example: obj = _TestModel(train_x, train_y)