From 02ee6a7fa0ce8c3b1c5758e17aba0da03174a1b2 Mon Sep 17 00:00:00 2001
From: "M. Emre Sahin" <40424147+OkuyanBoga@users.noreply.github.com>
Date: Mon, 16 Dec 2024 19:28:19 +0000
Subject: [PATCH] Fix callback compatibility for trainable_model (#878)

* Fix callback compatibility for trainable_model

* Update releasenotes/notes/fix-callback-trainable_model-ca52060260a3e466.yaml

Co-authored-by: Edoardo Altamura <38359901+edoaltamura@users.noreply.github.com>

* Update tests with callbacks

* Disable pylint unused arguments in tests

---------

Co-authored-by: Edoardo Altamura <38359901+edoaltamura@users.noreply.github.com>
---
 qiskit_machine_learning/algorithms/trainable_model.py  |  5 +++--
 .../fix-callback-trainable_model-ca52060260a3e466.yaml |  5 +++++
 .../classifiers/test_neural_network_classifier.py      |  9 +++++----
 .../regressors/test_neural_network_regressor.py        | 10 ++++++----
 4 files changed, 19 insertions(+), 10 deletions(-)
 create mode 100644 releasenotes/notes/fix-callback-trainable_model-ca52060260a3e466.yaml

diff --git a/qiskit_machine_learning/algorithms/trainable_model.py b/qiskit_machine_learning/algorithms/trainable_model.py
index 108dcdecd..3b2bace9b 100644
--- a/qiskit_machine_learning/algorithms/trainable_model.py
+++ b/qiskit_machine_learning/algorithms/trainable_model.py
@@ -20,7 +20,7 @@
 
 from .objective_functions import ObjectiveFunction
 from .serializable_model import SerializableModelMixin
-from ..optimizers import Optimizer, SLSQP, OptimizerResult, Minimizer
+from ..optimizers import Optimizer, SciPyOptimizer, SLSQP, OptimizerResult, Minimizer
 from ..utils import algorithm_globals
 from ..neural_networks import NeuralNetwork
 from ..utils.loss_functions import (
@@ -269,7 +269,8 @@ def _get_objective(
 
         def objective(objective_weights):
             objective_value = function.objective(objective_weights)
-            self._callback(objective_weights, objective_value)
+            if isinstance(self._optimizer, SciPyOptimizer):
+                self._callback(objective_weights, objective_value)
             return objective_value
 
         return objective
diff --git a/releasenotes/notes/fix-callback-trainable_model-ca52060260a3e466.yaml b/releasenotes/notes/fix-callback-trainable_model-ca52060260a3e466.yaml
new file mode 100644
index 000000000..dbdee5f73
--- /dev/null
+++ b/releasenotes/notes/fix-callback-trainable_model-ca52060260a3e466.yaml
@@ -0,0 +1,5 @@
+---
+fixes:
+  - |
+      Fixed a compatibility issue for different `callback` functions when they are 
+      used in :class:`~qiskit_machine_learning.algorithms.trainable_model` based algorithms.
\ No newline at end of file
diff --git a/test/algorithms/classifiers/test_neural_network_classifier.py b/test/algorithms/classifiers/test_neural_network_classifier.py
index 69655b301..4cb40dae8 100644
--- a/test/algorithms/classifiers/test_neural_network_classifier.py
+++ b/test/algorithms/classifiers/test_neural_network_classifier.py
@@ -521,17 +521,18 @@ def test_callback_setter(self):
 
         loss_history = []
 
-        def store_loss(_, loss):
-            loss_history.append(loss)
+        def store_loss(nfev, x_next, loss, update, is_accepted):  # pylint: disable=unused-argument
+            if is_accepted:
+                loss_history.append(loss)
 
         # use setter for the callback instead of providing in the initialize method
-        classifier.callback = store_loss
+        classifier.optimizer.callback = store_loss
 
         features = np.array([[0, 0], [1, 1]])
         labels = np.array([0, 1])
         classifier.fit(features, labels)
 
-        self.assertEqual(len(loss_history), 3)
+        self.assertEqual(len(loss_history), 1)
 
 
 if __name__ == "__main__":
diff --git a/test/algorithms/regressors/test_neural_network_regressor.py b/test/algorithms/regressors/test_neural_network_regressor.py
index a7c9cb225..fb791167b 100644
--- a/test/algorithms/regressors/test_neural_network_regressor.py
+++ b/test/algorithms/regressors/test_neural_network_regressor.py
@@ -239,17 +239,19 @@ def test_callback_setter(self):
 
         loss_history = []
 
-        def store_loss(_, loss):
-            loss_history.append(loss)
+        def store_loss(nfev, x_next, loss, update, is_accepted):  # pylint: disable=unused-argument
+
+            if is_accepted:
+                loss_history.append(loss)
 
         # use setter for the callback instead of providing in the initialize method
-        regressor.callback = store_loss
+        regressor.optimizer.callback = store_loss
 
         features = np.array([[0, 0], [0.1, 0.1], [0.4, 0.4], [1, 1]])
         labels = np.array([0, 0.1, 0.4, 1])
         regressor.fit(features, labels)
 
-        self.assertEqual(len(loss_history), 3)
+        self.assertEqual(len(loss_history), 1)
 
 
 if __name__ == "__main__":