diff --git a/test/optests_failures_dict.json b/test/optests_failures_dict.json
index 3bad0bbb027..2d01571374f 100644
--- a/test/optests_failures_dict.json
+++ b/test/optests_failures_dict.json
@@ -1,5 +1,16 @@
 {
   "_description": "This is a dict containing failures for tests autogenerated by generate_opcheck_tests. For more details, please see https://docs.google.com/document/d/1Pj5HRZvdOq3xpFpbEjUZp2hBovhy7Wnxw14m6lF2154/edit",
   "_version": 1,
-  "data": {}
+  "data": {
+    "torchvision::roi_align": {
+      "TestRoIAlign.test_aot_dispatch_dynamic__test_mps_error_inputs": {
+        "comment": "RuntimeError: MPS does not support roi_align backward with float16 inputs",
+        "status": "xfail"
+      },
+      "TestRoIAlign.test_autograd_registration__test_mps_error_inputs": {
+        "comment": "NotImplementedError: autograd_registration_check: NYI devices other than CPU/CUDA, got {'mps'}",
+        "status": "xfail"
+      }
+    }
+  }
 }
diff --git a/test/test_ops.py b/test/test_ops.py
index 6d80f037b88..d1cfce5919c 100644
--- a/test/test_ops.py
+++ b/test/test_ops.py
@@ -474,6 +474,7 @@ def test_boxes_shape(self):
     @pytest.mark.parametrize("x_dtype", (torch.float16, torch.float32, torch.float64))  # , ids=str)
     @pytest.mark.parametrize("contiguous", (True, False))
     @pytest.mark.parametrize("deterministic", (True, False))
+    @pytest.mark.opcheck_only_one()
     def test_forward(self, device, contiguous, deterministic, aligned, x_dtype, rois_dtype=None):
         if deterministic and device == "cpu":
             pytest.skip("cpu is always deterministic, don't retest")
@@ -491,6 +492,7 @@ def test_forward(self, device, contiguous, deterministic, aligned, x_dtype, rois
     @pytest.mark.parametrize("deterministic", (True, False))
     @pytest.mark.parametrize("x_dtype", (torch.float, torch.half))
     @pytest.mark.parametrize("rois_dtype", (torch.float, torch.half))
+    @pytest.mark.opcheck_only_one()
     def test_autocast(self, aligned, deterministic, x_dtype, rois_dtype):
         with torch.cuda.amp.autocast():
             self.test_forward(
@@ -506,6 +508,7 @@ def test_autocast(self, aligned, deterministic, x_dtype, rois_dtype):
     @pytest.mark.parametrize("device", cpu_and_cuda_and_mps())
     @pytest.mark.parametrize("contiguous", (True, False))
     @pytest.mark.parametrize("deterministic", (True, False))
+    @pytest.mark.opcheck_only_one()
     def test_backward(self, seed, device, contiguous, deterministic):
         if deterministic and device == "cpu":
             pytest.skip("cpu is always deterministic, don't retest")
@@ -520,6 +523,7 @@ def _make_rois(self, img_size, num_imgs, dtype, num_rois=1000):
     @pytest.mark.parametrize("aligned", (True, False))
     @pytest.mark.parametrize("scale, zero_point", ((1, 0), (2, 10), (0.1, 50)))
     @pytest.mark.parametrize("qdtype", (torch.qint8, torch.quint8, torch.qint32))
+    @pytest.mark.opcheck_only_one()
     def test_qroialign(self, aligned, scale, zero_point, qdtype):
         """Make sure quantized version of RoIAlign is close to float version"""
         pool_size = 5
@@ -589,6 +593,15 @@ def test_jit_boxes_list(self):
         self._helper_jit_boxes_list(model)
 
 
+optests.generate_opcheck_tests(
+    testcase=TestRoIAlign,
+    namespaces=["torchvision"],
+    failures_dict_path=os.path.join(os.path.dirname(__file__), "optests_failures_dict.json"),
+    additional_decorators=[],
+    test_utils=OPTESTS,
+)
+
+
 class TestPSRoIAlign(RoIOpTester):
     mps_backward_atol = 5e-2