diff --git a/captum/attr/_utils/approximation_methods.py b/captum/attr/_utils/approximation_methods.py
index 8debc9554..9af3cf958 100644
--- a/captum/attr/_utils/approximation_methods.py
+++ b/captum/attr/_utils/approximation_methods.py
@@ -2,7 +2,7 @@
 
 # pyre-strict
 from enum import Enum
-from typing import Callable, List, Tuple
+from typing import Callable, cast, List, Tuple
 
 import torch
 
@@ -121,19 +121,20 @@ def gauss_legendre_builders() -> (
 
     # allow using riemann even without np
     import numpy as np
+    from numpy.typing import NDArray
 
     def step_sizes(n: int) -> List[float]:
         assert n > 0, "The number of steps has to be larger than zero"
         # Scaling from 2 to 1
-        # pyre-fixme[6]: For 1st argument expected `Iterable[Variable[_T]]` but got
-        #  `float`.
-        return list(0.5 * np.polynomial.legendre.leggauss(n)[1])
+        return cast(
+            NDArray[np.float64], 0.5 * np.polynomial.legendre.leggauss(n)[1]
+        ).tolist()
 
     def alphas(n: int) -> List[float]:
         assert n > 0, "The number of steps has to be larger than zero"
         # Scaling from [-1, 1] to [0, 1]
-        # pyre-fixme[6]: For 1st argument expected `Iterable[Variable[_T]]` but got
-        #  `float`.
-        return list(0.5 * (1 + np.polynomial.legendre.leggauss(n)[0]))
+        return cast(
+            NDArray[np.float64], 0.5 * (1 + np.polynomial.legendre.leggauss(n)[0])
+        ).tolist()
 
     return step_sizes, alphas