test_torch.py 文件源码

def test_new(self):
        x = torch.autograd.Variable(torch.Tensor())
        y = torch.autograd.Variable(torch.randn(4, 4))
        z = torch.autograd.Variable(torch.IntTensor([1, 2, 3]))
        self.assertEqual(x.new().shape, [0])
        self.assertEqual(x.new(), x)
        self.assertEqual(x.new(1, 2).shape, [1, 2])
        self.assertEqual(x.new(torch.Size([3, 4])).shape, [3, 4])
        self.assertEqual(x.new([3, 4]).shape, [2])
        self.assertEqual(x.new([3, 4]).tolist(), [3, 4])
        self.assertEqual(x.new((3, 4)).tolist(), [3, 4])
        self.assertEqual(x.new(size=(3, 4)).shape, [3, 4])
        self.assertEqual(x.new(tuple()).shape, [0])
        self.assertEqual(x.new(y.storage()).data_ptr(), y.data_ptr())
        self.assertEqual(x.new(y).data_ptr(), y.data_ptr())
        self.assertIsNot(x.new(y), y)

        self.assertRaises(TypeError, lambda: x.new(z))
        # TypeError would be better
        self.assertRaises(RuntimeError, lambda: x.new(z.storage()))