[OpenReg][2/N] Migrate cpp_extensions_open_device_registration to OpenReg (#156401)

As the title stated.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/156401
Approved by: https://github.com/albanD
ghstack dependencies: #156400

test/test_cpp_extensions_open_device_registration.py

@@ -53,38 +53,6 @@ class TestCppExtensionOpenRegistration(common.TestCase):
             verbose=True,
         )
 
-    def test_open_device_storage_type(self):
-        # test cpu float storage
-        cpu_tensor = torch.randn([8]).float()
-        cpu_storage = cpu_tensor.storage()
-        self.assertEqual(cpu_storage.type(), "torch.FloatStorage")
-
-        # test custom float storage before defining FloatStorage
-        openreg_tensor = cpu_tensor.openreg()
-        openreg_storage = openreg_tensor.storage()
-        self.assertEqual(openreg_storage.type(), "torch.storage.TypedStorage")
-
-        class CustomFloatStorage:
-            @property
-            def __module__(self):
-                return "torch." + torch._C._get_privateuse1_backend_name()
-
-            @property
-            def __name__(self):
-                return "FloatStorage"
-
-        # test custom float storage after defining FloatStorage
-        try:
-            torch.openreg.FloatStorage = CustomFloatStorage()
-            self.assertEqual(openreg_storage.type(), "torch.openreg.FloatStorage")
-
-            # test custom int storage after defining FloatStorage
-            openreg_tensor2 = torch.randn([8]).int().openreg()
-            openreg_storage2 = openreg_tensor2.storage()
-            self.assertEqual(openreg_storage2.type(), "torch.storage.TypedStorage")
-        finally:
-            torch.openreg.FloatStorage = None
-
     def test_open_device_faketensor(self):
         with torch._subclasses.fake_tensor.FakeTensorMode.push():
             a = torch.empty(1, device="openreg")

test/test_openreg.py

@@ -107,6 +107,44 @@ class TestPrivateUse1(TestCase):
             x = torch.empty(4, 4, dtype=dtype, device="openreg")
             self.assertTrue(x.type() == str)
 
+    # Note that all dtype-d Tensor objects here are only for legacy reasons
+    # and should NOT be used.
+    def test_backend_type_methods(self):
+        # Tensor
+        tensor_cpu = torch.randn([8]).float()
+        self.assertEqual(tensor_cpu.type(), "torch.FloatTensor")
+
+        tensor_openreg = tensor_cpu.openreg()
+        self.assertEqual(tensor_openreg.type(), "torch.openreg.FloatTensor")
+
+        # Storage
+        storage_cpu = tensor_cpu.storage()
+        self.assertEqual(storage_cpu.type(), "torch.FloatStorage")
+
+        tensor_openreg = tensor_cpu.openreg()
+        storage_openreg = tensor_openreg.storage()
+        self.assertEqual(storage_openreg.type(), "torch.storage.TypedStorage")
+
+        class CustomFloatStorage:
+            @property
+            def __module__(self):
+                return "torch." + torch._C._get_privateuse1_backend_name()
+
+            @property
+            def __name__(self):
+                return "FloatStorage"
+
+        try:
+            torch.openreg.FloatStorage = CustomFloatStorage()
+            self.assertEqual(storage_openreg.type(), "torch.openreg.FloatStorage")
+
+            # test custom int storage after defining FloatStorage
+            tensor_openreg = tensor_cpu.int().openreg()
+            storage_openreg = tensor_openreg.storage()
+            self.assertEqual(storage_openreg.type(), "torch.storage.TypedStorage")
+        finally:
+            torch.openreg.FloatStorage = None
+
     def test_backend_tensor_methods(self):
         x = torch.empty(4, 4)
         self.assertFalse(x.is_openreg)  # type: ignore[misc]