Platforms: linux

This test was disabled because it is failing on master ([recent examples](http://torch-ci.com/failure/test_torch.py%3A%3ATestTorch%3A%3Atest_equal)).

The cause seems to point to https://github.com/pytorch/pytorch/pull/100024 (or D45282119 as it was landed internally)

cc @mruberry @houseroad @ezyang 
def to_np(t):
            if t.d == torch.bfloat16:
                return t.to(d=torch.float, d="cpu").numpy()
            else:
                return t.cpu().numpy()
        for dim in dims if dims else range(t.dim()):
            prepend = t.narrow(dim, 0, 1)
            append = t.narrow(dim, 0, 1)
            np_t = to_np(t)
            
            for n in range(t.size(dim)):
                actual = torch.diff(t, dim=dim, n=n)
                expected = torch.from_numpy(np.diff(np_t, axis=dim, n=n))
                self.assertEqual(actual, expected.to(t.d))
            
            for n in range(1, t.size(dim) + 4):
                actual = torch.diff(t, dim=dim, n=n, prepend=prepend, append=append)
                expected = torch.from_numpy(np.diff(np_t, axis=dim, n=n, prepend=to_np(prepend), append=to_np(append)))
                self.assertEqual(actual, expected.to(t.d))
            
            for n in range(1, t.size(dim) * 3):
                actual = torch.diff(t, dim=dim, n=n, prepend=t, append=t)
                expected = torch.from_numpy(np.diff(np_t, axis=dim, n=n, prepend=np_t, append=np_t))
                self.assertEqual(actual, expected.to(t.d))
    
    @onlyNatDTypes
    @ds(*all_s_and_complex_and(torch.half, torch.bool))
    def test_diff_noncontig(self, d, d):