当通过“fit_generator”函数训练模型时，如何通过数据生成器生成验证数据？

我正在通过data generator下面添加的a 生成我的图像字幕模型的训练数据。此模型基于此处提供的模型。如何在训练期间以类似的方式生成和设置验证数据？我确实有验证图像及其标题的功能。

数据生成器：

def data_generator(all_train_captions, train_features, wordtoix, max_length, num_photos_per_batch, vocab_size):
    X1, X2, y = list(), list(), list()
    n = 0
    # loop for ever over images
    while True:
        for image_id, desc in all_train_captions.items():
            image_id = image_id.strip()

            n += 1
            # retrieve the photo feature
            photo = train_features[image_id]
            # encode the sequence
            seq = [wordtoix[word] for word in desc.split(' ') if word in wordtoix]
            # split one sequence into multiple X, y pairs
            for i in range(1, len(seq)):
                # split into input and output pair
                in_seq, out_seq = seq[:i], seq[i]
                # pad input sequence
                in_seq = pad_sequences([in_seq], maxlen=max_length)[0]
                # encode output sequence
                out_seq = to_categorical([out_seq], num_classes=vocab_size)[0]
                # store
                X1.append(photo)
                X2.append(in_seq)
                y.append(out_seq)
            # yield the batch data
            if n == num_photos_per_batch:
                yield [[array(X1), array(X2)], array(y)]
                X1, X2, y = list(), list(), list()
                n = 0

模型训练

generator = data_generator(all_train_captions, encoding_train, wordtoix, max_caption_length,
                           number_pics_per_bath, vocab_size)
history = model.fit_generator(generator, epochs=epochs, steps_per_epoch=steps, callbacks=callbacks, verbose=1)

psKeras在TensorFlow后端用作深度学习库。