这是我的尝试：

inputs = Input(shape=(config.N_FRAMES_IN_SEQUENCE, config.IMAGE_H, config.IMAGE_W, config.N_CHANNELS))def cnn_model(inputs):    x = Conv2D(filters=32, kernel_size=(3,3), padding='same', activation='relu')(inputs)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=32, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=64, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=64, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=128, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    return xx = TimeDistributed(cnn_model)(inputs)

这导致了以下错误：

AttributeError: 'function' object has no attribute 'built'

回答：

你需要使用Lambda层，并将你的函数包装在其中：

# cnn_model函数和你定义的一样...x = TimeDistributed(Lambda(cnn_model))(inputs)

或者，你可以将那个块定义为一个模型，然后在其上应用TimeDistributed层：

def cnn_model():    input_frame = Input(shape=(config.IMAGE_H, config.IMAGE_W, config.N_CHANNELS))    x = Conv2D(filters=32, kernel_size=(3,3), padding='same', activation='relu')(input_frame)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=32, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=64, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=64, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    x = Conv2D(filters=128, kernel_size=(3,3), padding='same', activation='relu')(x)    x = MaxPooling2D(pool_size=(2, 2))(x)    model = Model(input_frame, x)    return modelinputs = Input(shape=(config.N_FRAMES_IN_SEQUENCE, config.IMAGE_H, config.IMAGE_W, config.N_CHANNELS))x = TimeDistributed(cnn_model())(inputs)