值错误:应在输入列表上调用合并层.添加()

Question

# import the necessary packages
import keras
from keras.initializers import glorot_uniform
from keras.layers import AveragePooling2D, Input, Add
from keras.models import Model
from keras.layers.normalization import BatchNormalization
from keras.layers.convolutional import Conv2D
from keras.layers.convolutional import MaxPooling2D
from keras.layers.core import Activation
from keras.layers.core import Flatten
from keras.layers.core import Dropout
from keras.layers.core import Dense

class SmallerVGGNet:
@staticmethod
def build(width, height, depth, classes, finalact):
X1 = Input(shape=(height, width, depth))
# # CONV => RELU => POOL
X = Conv2D(16, (3, 3), padding="same", strides=(1, 1), name="con_layer1")(X1)
X = BatchNormalization(axis=3)(X)
X = Activation("relu")(X)
X = MaxPooling2D(pool_size=(3, 3), strides=(1, 1))(X)
X = Conv2D(32, (3, 3), padding="same", strides=(2, 2), name="con_layer2")(X)
X = BatchNormalization(axis=3)(X)
X = Activation("relu")(X)
X = Conv2D(32, (3, 3), padding="same", strides=(1, 1), name="con_layer3")(X)
X = Activation("relu")(X)
X = BatchNormalization(axis=3)(X)
X = MaxPooling2D(pool_size=(3, 3), strides=(1, 1))(X)
# First component
X0 = Conv2D(256, (5, 5), strides=(1, 1), padding='same', kernel_initializer=glorot_uniform(seed=0))(X)
X0 = BatchNormalization(axis=3)(X0)
X0 = Activation("relu")(X0)
# (CONV => RELU) * 2 => POOL
X = Conv2D(64, (3, 3), padding="same", strides=(2, 2), name="con_layer4")(X0)
X = BatchNormalization(axis=3)(X)
X = Activation("relu")(X)
X = Conv2D(64, (3, 3), padding="same", strides=(1, 1), name="con_layer5")(X)
X = BatchNormalization(axis=3)(X)
X = Activation("relu")(X)
X = AveragePooling2D(pool_size=(3, 3), strides=(1, 1))(X)
# Second Component
X0 = Conv2D(512, (5, 5), strides=(1, 1), padding='valid', kernel_initializer=glorot_uniform(seed=0))(X)
X0 = BatchNormalization(axis=3)(X0)
X0 = Activation("relu")(X0)
# (CONV => RELU) * 2 => POOL
X = Conv2D(128, (3, 3), padding="same", strides=(2, 2), name="con_layer6")(X0)
X = BatchNormalization(axis=3)(X)
X = Activation("relu")(X)
X = Conv2D(128, (3, 3), padding="same", strides=(1, 1), name="con_layer7")(X)
X = BatchNormalization(axis=3)(X)
X = Activation("relu")(X)
X = MaxPooling2D(pool_size=(3, 3), strides=(1, 1))(X)
# Third Component
X0 = Conv2D(1024, (7, 7), strides=(2, 2), padding='valid', kernel_initializer=glorot_uniform(seed=0))(X)
X0 = BatchNormalization(axis=3)(X0)
X0 = Dense(128, activation="relu")(X0)
X0 = Activation("relu")(X0)
X = Add()([X0])
X = Flatten()(X1)
X = BatchNormalization()(X)
X = Dropout(0.5)(X)
output = Dense(classes, activation=finalact)(X)
model = Model(inputs=[X1], outputs=output)
print(model.summary())
return model

我想在最后一个激活函数上添加第三个组件，为此我创建了一个添加函数来添加所有 X0 值。 但是在添加此内容时会发生此错误。 添加 ADD 函数时会发生这种情况。

提高 ValueError('应该调用合并层' 值错误：应在输入列表上调用合并层。

Answer 1

Add()通常在列表中取2个值。你只给了一个。