old_contents: import torch
  import torchvision.utils as utils
  import unittest
  
  
  class Tester(unittest.TestCase):
  
      def test_make_grid_not_inplace(self):
          t = torch.rand(5, 3, 10, 10)
          t_clone = t.clone()
  
          utils.make_grid(t, normalize=False)
          assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
  
          utils.make_grid(t, normalize=True, scale_each=False)
          assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
  
          utils.make_grid(t, normalize=True, scale_each=True)
          assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
  
      def test_make_grid_raises_with_variable(self):
          t = torch.autograd.Variable(torch.rand(3, 10, 10))
          with self.assertRaises(TypeError):
              utils.make_grid(t)
  
          with self.assertRaises(TypeError):
              utils.make_grid([t, t, t, t])
  
  
  if __name__ == '__main__':
      unittest.main()
  
new_contents: import torch
  import torchvision.utils as utils
  import unittest
  
  
  class Tester(unittest.TestCase):
  
      def test_make_grid_not_inplace(self):
          t = torch.rand(5, 3, 10, 10)
          t_clone = t.clone()
  
          utils.make_grid(t, normalize=False)
          assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
  
          utils.make_grid(t, normalize=True, scale_each=False)
          assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
  
          utils.make_grid(t, normalize=True, scale_each=True)
          assert torch.equal(t, t_clone), 'make_grid modified tensor in-place'
  
  
  if __name__ == '__main__':
      unittest.main()
  
subject: Update test_utils.py (#486)