autoencoder.py 文件源码

def train_with_data_augmentation(self, batch_size, num_epoch, lr_schedule):
        datagen = ImageDataGenerator(
            width_shift_range=0.125, # randomly shift images horizontally, fraction
            height_shift_range=0.125, # randomly shift images vertically, fraction
            horizontal_flip=True)

        opt = keras.optimizers.SGD(lr=lr_schedule(0), momentum=0.9, nesterov=True)
        callback_list = [LearningRateScheduler(lr_schedule)]
        self.ae.compile(optimizer=opt, loss='mse')
        assert False, 'seems that y is not augmented.'
        # history = self.ae.fit_generator(
        #     datagen.flow(
        #         self.dataset.train_xs,
        #         self.dataset.train_xs,
        #     nb_epoch=num_epoch,
        #     batch_size=batch_size,
        #     validation_data=(self.dataset.test_xs, self.dataset.test_xs),
        #     shuffle=True, callbacks=callback_list)
        self.history = history.history