Fix InputXGradient pyre fixme issues (#1607)

Summary:
Pull Request resolved: #1607

Fixing unresolved pyre fixme issues in corresponding file

Differential Revision: D76736961

Author: Vivek Miglani

captum/attr/_core/input_x_gradient.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 
 # pyre-strict
-from typing import Callable, Optional
+from typing import Callable, cast, Optional
 
 from captum._utils.common import _format_output, _format_tensor_into_tuples, _is_tuple
 from captum._utils.gradient import (
@@ -126,12 +126,11 @@ def attribute(
         )
 
         undo_gradient_requirements(inputs_tuple, gradient_mask)
-        # pyre-fixme[7]: Expected `TensorOrTupleOfTensorsGeneric` but got
-        #  `Tuple[Tensor, ...]`.
-        return _format_output(is_inputs_tuple, attributions)
+        return cast(
+            TensorOrTupleOfTensorsGeneric, _format_output(is_inputs_tuple, attributions)
+        )
 
-    # pyre-fixme[24] Generic type `Callable` expects 2 type parameters.
-    def attribute_future(self) -> Callable:
+    def attribute_future(self) -> None:
         r"""
         This method is not implemented for InputXGradient.
         """

tests/attr/test_input_x_gradient.py

@@ -55,7 +55,7 @@ def test_futures_not_implemented(self) -> None:
         input_x_grad = InputXGradient(model.forward)
         attributions = None
         with self.assertRaises(NotImplementedError):
-            attributions = input_x_grad.attribute_future()
+            attributions = input_x_grad.attribute_future()  # type: ignore
         self.assertEqual(attributions, None)
 
     def _input_x_gradient_base_assert(