def test_empty_kernel(self):
""" Test QSVC with empty QuantumKernel """
qkernel = QuantumKernel()
qsvc = QSVC(quantum_kernel=qkernel)
with self.assertRaises(QiskitMachineLearningError):
_ = qsvc.fit(self.sample_train, self.label_train)
def test_qsvc_parameters(self):
""" Test QSVC with extra constructor parameters """
qkernel = QuantumKernel(feature_map=self.feature_map,
quantum_instance=self.statevector_simulator)
qsvc = QSVC(quantum_kernel=qkernel, tol=1e-4, C=0.5)
qsvc.fit(self.sample_train, self.label_train)
score = qsvc.score(self.sample_test, self.label_test)
self.assertEqual(score, 0.5)
def test_qsvc(self):
""" Test QSVC """
qkernel = QuantumKernel(feature_map=self.feature_map,
quantum_instance=self.statevector_simulator)
qsvc = QSVC(quantum_kernel=qkernel)
qsvc.fit(self.sample_train, self.label_train)
score = qsvc.score(self.sample_test, self.label_test)
self.assertEqual(score, 0.5)
def test_save_load(self):
"""Tests save and load models."""
features = np.array([[0, 0], [0.1, 0.2], [1, 1], [0.9, 0.8]])
labels = np.array([0, 0, 1, 1])
quantum_kernel = QuantumKernel(
feature_map=ZZFeatureMap(2),
quantum_instance=self.statevector_simulator)
classifier = QSVC(quantum_kernel=quantum_kernel)
classifier.fit(features, labels)
# predicted labels from the newly trained model
test_features = np.array([[0.2, 0.1], [0.8, 0.9]])
original_predicts = classifier.predict(test_features)
# save/load, change the quantum instance and check if predicted values are the same
file_name = os.path.join(tempfile.gettempdir(), "qsvc.model")
classifier.save(file_name)
try:
classifier_load = QSVC.load(file_name)
loaded_model_predicts = classifier_load.predict(test_features)
np.testing.assert_array_almost_equal(original_predicts,
loaded_model_predicts)
# test loading warning
class FakeModel(SerializableModelMixin):
"""Fake model class for test purposes."""
pass
with self.assertRaises(TypeError):
FakeModel.load(file_name)
finally:
os.remove(file_name)
def test_with_kernel_parameter(self):
"""Test QSVC with the `kernel` argument."""
with self.assertWarns(QiskitMachineLearningWarning):
QSVC(kernel=1)
def test_qsvc_to_string(self):
"""Test QSVC print works when no *args passed in"""
qsvc = QSVC()
_ = str(qsvc)