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 
# Test w
        def test_memory_layout(x, y, scale, zero_point, out):
            self.assertEqual(x.dim(), 4)
            self.assertEqual(x.size(), y.size())
            self.assertEqual(y.size(), out.size())
            shape = x.size()
            for n in range(shape[0]):
                for c in range(shape[1]):
                    for h in range(shape[2]):
                        for w in range(shape[3]):
                            if scale is not None and zero_point is not None:
                                self.assertEqual(
                                    out[n][c][h][w],
                                    torch.ops.quantized.add(x[n][c][h][w], y[n][c][h][w], scale, zero_point))
                            else:
                                self.assertEqual(out[n][c][h][w], x[n][c][h][w] + y[n][c][h][w])
        xraw = torch.rand(2, 3, 4, 4)
        yraw = torch.rand(2, 3, 4, 4)
        qxraw = torch.quantize_per_tensor(xraw, 0.1, 5, torch.quint8)
        qyraw = torch.quantize_per_tensor(yraw, 0.1, 5, torch.quint8)
        # contig
        test_memory_layout(xraw, yraw, None, None, xraw + yraw)
        test_memory_layout(qxraw, qyraw, 0.1, 5, torch.ops.quantized.add(qxraw, qyraw, 0.1, 5))
        # channe
        x = xraw.contiguous(memory_format=torch.channels_last)
        y = yraw.contiguous(memory_format=torch.channels_last)
        test_memory_layout(x, y, None, None, x + y)