Fix PYRE_MISSING_ANNOTATIONS issues in fbcode/pearl/test/unit/with_pytorch

Differential Revision: D101136138

fbshipit-source-id: 4ff1e63d8a5453a64e833787fcd9b571cc6900e8

Author: generatedunixname1401739305002972

test/unit/with_pytorch/test_linear_bandits.py

@@ -300,7 +300,7 @@ def test_unobserved_actions(self) -> None:
 
         # Create a class to hold the action counts to avoid nonlocal issues
         class ActionCounter:
-            def __init__(self, num_actions: int):
+            def __init__(self, num_actions: int) -> None:
                 self.counts = torch.zeros(num_actions)
 
             def update(self, actions: torch.Tensor) -> None:

test/unit/with_pytorch/test_neural_linear_bandits.py

@@ -39,8 +39,7 @@ def test_set_use_skip_connections(self) -> None:
         for child in policy_learner.model._nn_layers._model.children():
             self.assertIsInstance(child, ResidualWrapper)
 
-    # pyre-fixme[3]: Return type must be annotated.
-    def test_state_dict(self):
+    def test_state_dict(self) -> None:
         # There has been discussions and debating on how to support state dict of policy learner
         # This unittest is to ensure regardless of solution, this functionality needs to be there
         # init a policy learn and learn once to get some random value