Fixes mypy failure with latest mypy 1.16.0

qiskit_machine_learning/gradients/lin_comb/lin_comb_estimator_gradient.py

@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2022, 2024.
+# (C) Copyright IBM 2022, 2025.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -233,7 +233,9 @@ def _run_unique(
                     gradient.imag = results[partial_sum_n + n // 2 : partial_sum_n + n]
 
                 else:
-                    gradient = np.real(results[partial_sum_n : partial_sum_n + n])
+                    gradient = np.real(
+                        results[partial_sum_n : partial_sum_n + n]
+                    )  # type: ignore[assignment, unused-ignore]
                 partial_sum_n += n
                 gradients.append(gradient)
 

qiskit_machine_learning/neural_networks/effective_dimension.py

@@ -62,16 +62,20 @@ def __init__(
         """
 
         # Store arguments
-        self._weight_samples = None
-        self._input_samples = None
-        self._num_weight_samples = 1
-        self._num_input_samples = 1
+        self._weight_samples = np.asarray([0.25])
+        self._input_samples = np.asarray([0.5])
+        self._num_weight_samples = len(self._weight_samples)
+        self._num_input_samples = len(self._input_samples)
         self._model = qnn
 
-        # Define weight samples and input samples
-        self.weight_samples = weight_samples  # type: ignore
-        # input setter uses self._model
-        self.input_samples = input_samples  # type: ignore
+        # Setup things for weight and input samples via setters that deal
+        # with the union of types that can be passed so that the private
+        # vars above that have just been set with temp values of right types
+        # to establish typing, get the right values per what was passed.
+        # Note, the samples ones above had been set to None but this results
+        # in errors when checking using mypy 1.16.0
+        self.weight_samples = weight_samples
+        self.input_samples = input_samples
 
     @property
     def weight_samples(self) -> np.ndarray:

qiskit_machine_learning/variational_algorithm.py

@@ -1,6 +1,6 @@
 # This code is part of a Qiskit project.
 #
-# (C) Copyright IBM 2019, 2024.
+# (C) Copyright IBM 2019, 2025.
 #
 # This code is licensed under the Apache License, Version 2.0. You may
 # obtain a copy of this license in the LICENSE.txt file in the root directory
@@ -91,7 +91,7 @@ def optimal_value(self) -> float | None:
         return self._optimal_value
 
     @optimal_value.setter
-    def optimal_value(self, value: int) -> None:
+    def optimal_value(self, value: float) -> None:
         """Sets optimal value"""
         self._optimal_value = value