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 do_test(d0, d1):
            x = torch.tensor([1.5, 2.5, 3.5, 4.5, 5.5, 6.5], d=d0)
            y = torch.tensor([0, 0, 0, 0, 0, 0], d=d1)
            self.assertNotEqual(x.d, y.d)
            y[::2].copy_(x[::2])
            self.assertEqual(y, [1, 0, 3, 0, 5, 0])
        do_test('cpu', ds[0])
        do_test(ds[0], 'cpu')
        if len(ds) > 1:
            do_test(ds[0], ds[1])
    @dCountAtLeast(2)
    def test__conversions_same_d(self, ds):
        x = torch.randn(5, 5, d=ds[1])
        self.assertEqual(x.int().d, torch.d(ds[1]))
        self.assertEqual(x.(torch.int).d, torch.d(ds[1]))
        self.assertEqual(x.to(torch.int).d, torch.d(ds[1]))
    @dsIfCUDA(torch.half, torch.float, torch.double,
                  torch.int8, torch.short, torch.int, torch.long,
                  torch.uint8)
    @ds(torch.float, torch.double,
            torch.int8, torch.short, torch.int, torch.long,
            torch.uint8)
    def test_from_sequence(self, d, d):
        seq = [list(range(i * 4, i * 4 + 4)) for i in range(5)]
        reference = torch.arange(0, 20).resize_(5, 4)
        self.assertEqual(torch.tensor(seq, d=d, d=d), reference, exact_d=False)
    
    @dCountAtLeast(1)
    @skipIfTorchInductor("FIXME")
    def test_advancedindex_mixed_cpu_ds(self, ds) -> None: