code: def __init__(self, grid, train_x, train_y, likelihood):
      super(GridGPRegressionModel, self).__init__(
          train_x, train_y, likelihood
      )
      self.mean_module = gpytorch.means.ConstantMean()
      self.covar_module = gpytorch.kernels.GridKernel(
          gpytorch.kernels.RBFKernel(), grid=grid
      )
  
imports: import math
  import os
  import random
  import unittest
  import warnings
  import torch
  from torch import optim
  import gpytorch
  from gpytorch.test.utils import least_used_cuda_device
  from gpytorch.utils.warnings import GPInputWarning
label_desc: Use image node_id 1 to create a new GridGPRegressionModel object from inherited base classes: gpytorch.models with example: obj = GridGPRegressionModel(grid, train_x, train_y, likelihood)