278f71a4b7b4f0b6ada8f78d71dbfd8947ab405e,autokeras/generator.py,HillClimbingClassifierGenerator,generate,#HillClimbingClassifierGenerator#,102

Before Change

        model = RandomConvClassifierGenerator(self.n_classes,self.input_shape).generate()
        optimal_index = None
        optimal_accuracy = None
        while True:
            ModelTrainer(model, self.x_train, self.y_train, self.x_test, self.y_test, self.verbose).train_model()
            _, optimal_accuracy = model.evaluate(self.x_test,self.y_test,self.verbose)
            models = self._remove_duplicate(net_transfromer(model))
            for index in range(0,len(models)):
                ModelTrainer(models[index], self.x_train, self.y_train, self.x_test, self.y_test, self.verbose).train_model()
                _, accuracy = model[index].evaluate(self.x_test, self.y_test, self.verbose)
                if accuracy > optimal_accuracy:
                    optimal_accuracy = accuracy
                    optimal_index = index
                    model = models[index]
            if optimal_index == None:
                break
        return model

After Change

            for index in range(0,len(models)):
                models[index].compile(loss=categorical_crossentropy,
                  optimizer=Adadelta(),
                  metrics=["accuracy"])
                ModelTrainer(models[index], self.x_train, self.y_train, self.x_test, self.y_test, self.verbose).train_model()
                _, accuracy = models[index].evaluate(self.x_test, self.y_test, self.verbose)
                if accuracy > optimal_accuracy:

Instances