如何在Keras中将Conv3D输出连接到MaxPooling2D？

from keras.models import Model
from keras.layers import Input, Conv3D, MaxPooling2D, Flatten, Dense

# 定义输入层
input_3d = Input(shape=(depth, height, width, channels))

# 定义3D卷积层
conv_3d = Conv3D(filters=32, kernel_size=(3, 3, 3), activation='relu')(input_3d)

# 将3D卷积层的输出转换为2D张量
flatten = Flatten()(conv_3d)

# 定义2D最大池化层
maxpool_2d = MaxPooling2D(pool_size=(2, 2))(flatten)

# 添加其他层和输出层
# ...

# 定义模型
model = Model(inputs=input_3d, outputs=output)

# 编译模型并训练
# ...