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 
t1 = torch.empty(3, 4, 9, 10)
        t2 = torch.empty(3, 4)
        t3 = torch.empty(1, 9, 3, 3)
        t4 = torch.empty(3, 4, 9, 10)
        self.assertFalse(t1.is_same_size(t2))
        self.assertFalse(t1.is_same_size(t3))
        self.assertTrue(t1.is_same_size(t4))
        nt1 = torch.nested.nested_tensor([torch.ones(2, 4), torch.ones(3, 4), torch.ones(5, 4)])
        nt2 = torch.nested.nested_tensor([torch.ones(2, 4), torch.ones(2, 4), torch.ones(2, 4)])
        nt3 = torch.nested.nested_tensor([torch.ones(2, 4, 5), torch.ones(2, 6, 5)])
        nt4 = torch.nested.nested_tensor([torch.ones(2, 4), torch.ones(3, 4), torch.ones(5, 4)])
        self.assertFalse(nt1.is_same_size(nt2))
        self.assertFalse(nt1.is_same_size(nt3))
        self.assertTrue(nt1.is_same_size(nt4))
        with self.assertRaisesRegex(RuntimeError, "Expected both self and other to be nested tensors."):
            t1.is_same_size(nt1)
        with self.assertRaisesRegex(RuntimeError, "Expected both self and other to be nested tensors."):
            nt1.is_same_size(t1)
    def test_tensor_set(self):