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

Before Change

        Train the model with dataset and return the minimum_loss
        self.training_losses = []
        self._no_improvement_count = 0
        self.minimum_loss = float("inf")
        batch_size = min(self.x_train.shape[0], 200)
        if constant.DATA_AUGMENTATION:
            flow = self.datagen.flow(self.x_train, self.y_train, batch_size)
        else:

After Change

        terminator = EarlyStop()
        lr_scheduler = LearningRateScheduler(lr_schedule)

        lr_reducer = ReduceLROnPlateau(factor=np.sqrt(0.1),
                                       cooldown=0,
                                       patience=5,
                                       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)

Instances