neural_cryptography_data_generator.py

def data_generator(image_size, sentence_len, dict_len, batch_size=32):
    while True:
        x_img = np.zeros((batch_size, image_size[0], image_size[1], image_size[2]))
        x_sen = np.zeros((batch_size, sentence_len))
        y_img = np.zeros((batch_size, image_size[0], image_size[1], image_size[2]))
        y_sen = np.zeros((batch_size, sentence_len, dict_len))
        for i in range(batch_size):
            img = rand_img(image_size)
            sentence = rand_sentence(sentence_len, dict_len)
            sentence_onehot = onehot(sentence, dict_len)
            x_img[i] = img
            x_sen[i] = sentence
            y_img[i] = img
            y_sen[i] = sentence_onehot
        yield [[x_img, x_sen], [y_img, y_sen]]