def test_validation(self): # model cnn_model = CharacterLevelCnnModel(label_mapping=self.label_mapping) cnn_model._construct_model() # data for model cv_data_gen = [[ np.array([['test']]), # x_data np.zeros((1, 3400, max(self.label_mapping.values()) + 1)) ] # y_data ] # validation cnn_model._validate_training(cv_data_gen, batch_size_test=32, verbose_log=True, verbose_keras=False)
def test_validation_evaluate_and_classification_report(self, *mocks): cnn_model = CharacterLevelCnnModel(self.label_mapping) cnn_model._construct_model() # validation data val_gen = [[ np.array([['123 fake st']]), np.zeros((1, 3400, max(self.label_mapping.values()) + 1)) ]] val_gen[0][1][:, :11, self.label_mapping['ADDRESS']] = 1 f1, f1_report = cnn_model._validate_training(val_gen, 32, True, True) self.assertIsNotNone(f1) self.assertIsNotNone(f1_report) self.assertEqual(11, f1_report['ADDRESS']['support'])