6a4fa82792bddc6126eaf944956f49f0a0cb7ca7,test/filters/test_blur.py,TestBoxBlur,test_kernel_5x5,#TestBoxBlur#,37

Before Change

        assert_allclose(actual[0, 0, 1, 1:4], torch.tensor(1.).to(device))

    def test_kernel_5x5(self, device):
        inp = torch.tensor([[[
            [1., 1., 1., 1., 1.],
            [1., 1., 1., 1., 1.],
            [1., 1., 1., 1., 1.],
            [2., 2., 2., 2., 2.],
            [2., 2., 2., 2., 2.]
        ]]]).to(device)

        kernel_size = (5, 5)
        expected = inp.sum((1, 2, 3)) / torch.mul(*kernel_size)

        actual = kornia.filters.box_blur(inp, kernel_size)
        assert_allclose(actual[:, 0, 2, 2], expected)

    def test_kernel_5x5_batch(self, device):

After Change

        assert_allclose(actual.sum(), torch.tensor(35.).to(actual), rtol=tol_val, atol=tol_val)

    def test_kernel_5x5(self, device, dtype):
        inp = torch.tensor([[[
            [1., 1., 1., 1., 1.],
            [1., 1., 1., 1., 1.],
            [1., 1., 1., 1., 1.],
            [2., 2., 2., 2., 2.],
            [2., 2., 2., 2., 2.]
        ]]], device=device, dtype=dtype)

        kernel_size = (5, 5)
        expected = inp.sum((1, 2, 3)) / torch.mul(*kernel_size)

        actual = kornia.filters.box_blur(inp, kernel_size)

        tol_val: float = utils._get_precision_by_name(device, "xla", 1e-1, 1e-4)
        assert_allclose(actual[:, 0, 2, 2], expected, rtol=tol_val, atol=tol_val)

Instances