code: def test_named_parameters_and_constraints(self):
      likelihood = gpytorch.likelihoods.GaussianLikelihood()
      model = ExactGPModel(None, None, likelihood)
  
      for (
          name,
          _param,
          constraint,
      ) in model.named_parameters_and_constraints():
          if name == "likelihood.noise_covar.raw_noise":
              self.assertIsInstance(
                  constraint, gpytorch.constraints.GreaterThan
              )
          elif name == "mean_module.constant":
              self.assertIsNone(constraint)
          elif name == "covar_module.raw_outputscale":
              self.assertIsInstance(
                  constraint, gpytorch.constraints.Positive
              )
          elif name == "covar_module.base_kernel.raw_lengthscale":
              self.assertIsInstance(
                  constraint, gpytorch.constraints.Positive
              )
  
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 2 for calling the TestConstraintNaming obj's underlying member method code with example usage: obj.test_named_parameters_and_constraints() without return types