c99295e1903952b3b806c4fd641e28f852b17c36,autokeras/utils.py,ModelTrainer,train_model,#ModelTrainer#,101

Before Change

            flow = self.datagen.flow(self.x_train, self.y_train, batch_size)
        else:
            flow = None
        for _ in range(constant.MAX_ITER_NUM):
            if constant.DATA_AUGMENTATION:
                self.model.fit_generator(flow, epochs=constant.EPOCHS_EACH)
            else:
                self.model.fit(self.x_train, self.y_train,
                               batch_size=batch_size,
                               epochs=constant.EPOCHS_EACH,
                               verbose=self.verbose)
            loss, _ = self.model.evaluate(self.x_test, self.y_test, verbose=self.verbose)
            if self._converged(loss):
                break
        return self.minimum_loss


def extract_config(network):

After Change

                                       min_lr=0.5e-6)

        callbacks = [terminator, lr_scheduler, lr_reducer]
        if constant.LIMIT_MEMORY:
            config = tf.ConfigProto()
            config.gpu_options.allow_growth = True
            sess = tf.Session(config=config)
            backend.set_session(sess)
        try:
            if constant.DATA_AUGMENTATION:
                flow = self.datagen.flow(self.x_train, self.y_train, batch_size)
                self.model.fit_generator(flow,

Instances