code: def test_forward_mat(self):
      test_x = torch.randn(4, 3)
      mean = self.create_mean()
      if self.__class__.batch_shape is None:
          self.assertEqual(mean(test_x).shape, torch.Size([4, 4]))
      else:
          self.assertEqual(
              mean(test_x).shape,
              torch.Size([*self.__class__.batch_shape, 4, 4]),
          )
      self.assertEqual(mean(test_x)[..., 1:].norm().item(), 0)
  
file_path: gpytorch/test/means/test_constant_mean_grad.py
imports: import unittest
  import torch
  from gpytorch.means import ConstantMeanGrad
  from gpytorch.test.base_mean_test_case import BaseMeanTestCase
label_desc: Use image node_id 3 for calling the TestConstantMeanGrad obj's underlying member method code with example usage: obj.test_forward_mat() without return types