Fix test sensitivity pyre fix me issues

Summary: Fixing unresolved pyre fixme issues in corresponding file

Differential Revision: D67726420

tests/helpers/evaluate_linear_model.py

@@ -6,11 +6,13 @@
 from typing import cast, Dict
 
 import torch
+
+from captum._utils.models.linear_model.model import LinearModel
 from torch import Tensor
+from torch.utils.data import DataLoader
 
 
-# pyre-fixme[2]: Parameter must be annotated.
-def evaluate(test_data, classifier) -> Dict[str, Tensor]:
+def evaluate(test_data: DataLoader, classifier: LinearModel) -> Dict[str, Tensor]:
     classifier.eval()
 
     l1_loss = 0.0

tests/metrics/test_sensitivity.py

@@ -28,19 +28,15 @@
 
 
 @typing.overload
-# pyre-fixme[43]: The implementation of `_perturb_func` does not accept all possible
-#  arguments of overload defined on line `32`.
 def _perturb_func(inputs: Tuple[Tensor, ...]) -> Tuple[Tensor, ...]: ...
 
 
 @typing.overload
-# pyre-fixme[43]: The implementation of `_perturb_func` does not accept all possible
-#  arguments of overload defined on line `28`.
 def _perturb_func(inputs: Tensor) -> Tensor: ...
 
 
 def _perturb_func(
-    inputs: TensorOrTupleOfTensorsGeneric,
+    inputs: Union[Tensor, Tuple[Tensor, ...]],
 ) -> Union[Tensor, Tuple[Tensor, ...]]:
     def perturb_ratio(input: Tensor) -> Tensor:
         return (
@@ -55,7 +51,7 @@ def perturb_ratio(input: Tensor) -> Tensor:
         input1 = inputs[0]
         input2 = inputs[1]
     else:
-        input1 = cast(Tensor, inputs)
+        input1 = inputs
 
     perturbed_input1 = input1 + perturb_ratio(input1)
 
@@ -283,12 +279,13 @@ def test_classification_sensitivity_tpl_target_w_baseline(self) -> None:
 
     def sensitivity_max_assert(
         self,
-        # pyre-fixme[24]: Generic type `Callable` expects 2 type parameters.
-        expl_func: Callable,
+        expl_func: Callable[..., Union[Tensor, Tuple[Tensor, ...]]],
         inputs: TensorOrTupleOfTensorsGeneric,
         expected_sensitivity: Tensor,
-        # pyre-fixme[24]: Generic type `Callable` expects 2 type parameters.
-        perturb_func: Callable = _perturb_func,
+        perturb_func: Union[
+            Callable[[Tensor], Tensor],
+            Callable[[Tuple[Tensor, ...]], Tuple[Tensor, ...]],
+        ] = _perturb_func,
         n_perturb_samples: int = 5,
         max_examples_per_batch: Optional[int] = None,
         baselines: Optional[BaselineType] = None,