如何使用CNN模型添加关注层

Question

我已经创建了用于图像分类的AlexNet模型。代码如下。我想用这种架构添加一个Attention层。我不知道如何使用这种CNN模型添加关注层。

` model = Sequential()

# 1st Convolutional Layer

model.add(Conv2D(filters=96, input_shape=(227,227,3), kernel_size=(11,11), strides=(4,4), padding="valid", activation = "relu"))

# Max Pooling
model.add(MaxPool2D(pool_size=(3,3), strides=(2,2), padding="valid"))

# 2nd Convolutional Layer
model.add(Conv2D(filters=256, kernel_size=(5,5), strides=(1,1), padding="same", activation = "relu"))

# Max Pooling
model.add(MaxPool2D(pool_size=(3,3), strides=(2,2), padding="valid"))

# 3rd Convolutional Layer
model.add(Conv2D(filters=384, kernel_size=(3,3), strides=(1,1), padding="same", activation = "relu"))

# 4th Convolutional Layer
model.add(Conv2D(filters=384, kernel_size=(3,3), strides=(1,1), padding="same", activation = "relu"))

# 5th Convolutional Layer
model.add(Conv2D(filters=256, kernel_size=(3,3), strides=(1,1), padding="same", activation = "relu"))

# Max Pooling
model.add(MaxPool2D(pool_size=(3,3), strides=(2,2), padding="valid"))

# Passing it to a Fully Connected layer
model.add(Flatten())
# 1st Fully Connected Layer
model.add(Dense(units = 9216, activation = "relu"))

# 2nd Fully Connected Layer
model.add(Dense(units = 4096, activation = "relu"))

# 3rd Fully Connected Layer
model.add(Dense(4096, activation = "relu"))

# Output Layer
model.add(Dense(2, activation = "softmax")) #As we have two classes
model.summary()
 `