code: def __init__(self, train_x, train_y, likelihood):
      super(ExactGPModel, self).__init__(train_x, train_y, likelihood)
      self.mean_module = gpytorch.means.ConstantMean()
      self.covar_module = gpytorch.kernels.ScaleKernel(
          gpytorch.kernels.RBFKernel()
      )
  
imports: import math
  import unittest
  import torch
  from torch import sigmoid
  from torch.nn.functional import softplus
  import gpytorch
  from gpytorch.test.base_test_case import BaseTestCase
label_desc: Use image node_id 1 to create a new ExactGPModel object from inherited base classes: gpytorch.models with example: obj = ExactGPModel(train_x, train_y, likelihood)