在keras中，如何匹配不同类型多个输入数据

from keras.layers import Input

text_input = Input(shape=(100,), dtype='int32', name='text_input')
image_input = Input(shape=(256, 256, 3), name='image_input')

from keras.layers import Dense, Conv2D, LSTM
from keras.models import Model

# 文本输入的处理层
text_embedding = Embedding(input_dim=10000, output_dim=128)(text_input)
text_lstm = LSTM(64)(text_embedding)

# 图像输入的处理层
image_conv = Conv2D(64, (3, 3))(image_input)
image_flatten = Flatten()(image_conv)

# 合并两个输入的处理层
merged = concatenate([text_lstm, image_flatten])
output = Dense(10, activation='softmax')(merged)

# 定义模型
model = Model(inputs=[text_input, image_input], outputs=output)

model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])
model.fit({'text_input': text_data, 'image_input': image_data}, labels, epochs=10, batch_size=32)