code: def __init__(self, train_x, train_y, likelihood):
      super(GPRegressionModel, self).__init__(
          train_x, train_y, likelihood
      )
      self.mean_module = ZeroMean()
      self.base_covar_module = ScaleKernel(RBFKernel(ard_num_dims=2))
      self.covar_module = AdditiveStructureKernel(
          GridInterpolationKernel(
              self.base_covar_module, grid_size=100, num_dims=1
          ),
          num_dims=2,
      )
  
file_path: gpytorch/test/examples/test_kissgp_additive_regression.py
imports: import os
  import random
  import unittest
  import torch
  from torch import optim
  import gpytorch
  from gpytorch.distributions import MultivariateNormal
  from gpytorch.kernels import AdditiveStructureKernel, GridInterpolationKernel, RBFKernel, ScaleKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.means import ZeroMean
label_desc: Use image node_id 1 to create a new GPRegressionModel object from inherited base classes: gpytorch.models with example: obj = GPRegressionModel(train_x, train_y, likelihood)