diff --git a/backends/arm/test/quantizer/test_generic_annotater.py b/backends/arm/test/quantizer/test_generic_annotater.py
index 4eaf1c205cc..4b43b6c9e50 100644
--- a/backends/arm/test/quantizer/test_generic_annotater.py
+++ b/backends/arm/test/quantizer/test_generic_annotater.py
@@ -4,7 +4,7 @@
 # LICENSE file in the root directory of this source tree.
 import itertools
 
-from typing import Tuple
+from typing import Any, Callable, Tuple
 
 import torch
 from executorch.backends.arm.quantizer import is_annotated
@@ -18,20 +18,25 @@
 
 
 class SingleOpModel(torch.nn.Module):
-    def __init__(self, op, example_input, **op_kwargs) -> None:
+    def __init__(
+        self,
+        op: Callable[..., torch.Tensor],
+        example_input: Tuple[Any, ...],
+        **op_kwargs: Any,
+    ) -> None:
         super().__init__()
-        self.op = op
-        self._example_input = example_input
-        self.op_kwargs = op_kwargs
+        self.op: Callable[..., torch.Tensor] = op
+        self._example_input: Tuple[Any, ...] = example_input
+        self.op_kwargs: dict[str, Any] = dict(op_kwargs)
 
-    def forward(self, x):
+    def forward(self, x: Any) -> torch.Tensor:
         return self.op(x, **self.op_kwargs)
 
-    def example_inputs(self):
+    def example_inputs(self) -> Tuple[Any, ...]:
         return self._example_input
 
 
-def check_annotation(model):
+def check_annotation(model: SingleOpModel) -> None:
     pipeline = TosaPipelineINT[input_t1](model, model.example_inputs(), [], [])
     pipeline.pop_stage("check_count.exir")
     pipeline.pop_stage("run_method_and_compare_outputs")