code: def __init__(
      self, train_x, train_y, likelihood, should_use_wiski=False
  ):
      super().__init__(train_x, train_y, likelihood)
      self.mean_module = gpytorch.means.ConstantMean()
      self.covar_module = GridInterpolationKernelMock(
          base_kernel=gpytorch.kernels.ScaleKernel(
              gpytorch.kernels.RBFKernel()
          ),
          grid_size=128,
          num_dims=1,
          should_use_wiski=should_use_wiski,
      )
  
imports: import unittest
  import torch
  import gpytorch
  from gpytorch import settings
  from gpytorch.kernels import GridInterpolationKernel
  from gpytorch.likelihoods import GaussianLikelihood
  from gpytorch.mlls import ExactMarginalLogLikelihood
  from gpytorch.models import ExactGP
  from gpytorch.models.exact_prediction_strategies import InterpolatedPredictionStrategy
  from gpytorch.test.model_test_case import BaseModelTestCase
label_desc: Use image node_id 1 to create a new InterpolatedExactGPModel object from inherited base classes: ExactGP with example: obj = InterpolatedExactGPModel(train_x, train_y, likelihood, should_use_wiski)