code: def test_prior(self):
      if self.batch_shape is None:
          prior = NormalPrior(0.0, 1.0)
      else:
          prior = NormalPrior(
              torch.zeros(self.batch_shape),
              torch.ones(self.batch_shape),
          )
      mean = self.create_mean(prior=prior)
      self.assertEqual(mean.mean_prior, prior)
      pickle.loads(
          pickle.dumps(mean)
      )  # Should be able to pickle and unpickle with a prior
      value = prior.sample()
      mean._constant_closure(mean, value)
      self.assertTrue(
          torch.equal(
              mean.constant.data,
              value.reshape(mean.constant.data.shape),
          )
      )
  
imports: import math
  import pickle
  import unittest
  import warnings
  from collections import OrderedDict
  import torch
  import gpytorch
  from gpytorch.constraints import GreaterThan
  from gpytorch.means import ConstantMean
  from gpytorch.priors import NormalPrior
  from gpytorch.test.base_mean_test_case import BaseMeanTestCase
  from gpytorch.utils.warnings import OldVersionWarning
label_desc: Use image node_id 2 for calling the TestConstantMean obj's underlying member method code with example usage: obj.test_prior() without return types