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 
self.assertIs(t, t.to(t, non_blocking=non_blocking))
            self.assertIs(t, t.to(t.d, non_blocking=non_blocking))
            self.assertIs(t, t.to(torch.empty_like(t), non_blocking=non_blocking))
            self.assertIsNot(t, t.to(t, non_blocking=non_blocking, copy=True))
            self.assertIsNot(t, t.to(t.d, non_blocking=non_blocking, copy=True))
            self.assertIsNot(t, t.to(torch.empty_like(t), non_blocking=non_blocking, copy=True))
            ds = [t.d]
            if t.d. == 'cuda':
                if t.d.index == -1:
                    ds.append('cuda:{}'.format(torch.cuda.current_d()))
                elif t.d.index == torch.cuda.current_d():
                    ds.append('cuda')
            for d in ds:
                self.assertIs(t, t.to(d, non_blocking=non_blocking))
                self.assertIs(t, t.to(d, t.d, non_blocking=non_blocking))
                self.assertIsNot(t, t.to(d, non_blocking=non_blocking, copy=True))
                self.assertIsNot(t, t.to(d, t.d, non_blocking=non_blocking, copy=True))
        a = torch.tensor(5)
        if layout == torch.sparse_csr:
            a = torch.tensor([[0, 1, 2], [2, 0, 3]]).to_sparse_csr()
        test_copy_behavior(a)
        self.assertEqual(a.d, a.to('cpu').d)
        self.assertEqual(a.d, a.to('cpu', d=torch.float32).d)
        self.assertIs(torch.float32, a.to('cpu', d=torch.float32).d)
        self.assertEqual(a.d, a.to(torch.float32).d)
        self.assertIs(torch.float32, a.to(d=torch.float32).d)
        def test_data_ptr(getter):