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 x
x = TimeDistributed(cnn_model)(inputs)
出现以下错误:
AttributeError: 'function' object has no attribute 'built'
最佳答案
您需要使用Lambda
层并将函数包装在其中:
# cnn_model function the same way as you defined it ...
x = TimeDistributed(Lambda(cnn_model))(inputs)
或者,您可以将该块定义为模型,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 model
inputs = Input(shape=(config.N_FRAMES_IN_SEQUENCE, config.IMAGE_H, config.IMAGE_W, config.N_CHANNELS))
x = TimeDistributed(cnn_model())(inputs)
关于python - 如何在CNN块上应用TimeDistributed层?,我们在Stack Overflow上找到一个类似的问题:https://stackoverflow.com/questions/52845711/