如何在softmax层之前添加计算(例如log和sqrt root)到keras vgg16

from keras.models import Model
from keras.layers import Dense, Activation, Flatten, Input
from keras.applications.vgg16 import VGG16

# 加载VGG16模型
vgg16 = VGG16(weights='imagenet', include_top=True)

# 获取VGG16模型的输入和输出
input_tensor = vgg16.input
output_tensor = vgg16.layers[-2].output  # 倒数第二层是全连接层

# 添加自定义层
x = Dense(256)(output_tensor)
x = Activation('relu')(x)
x = Dense(128)(x)
x = Activation('relu')(x)
x = Dense(64)(x)
x = Activation('relu')(x)

# 添加log和sqrt root计算
x = Activation('log')(x)
x = Activation('sqrt')(x)

# 添加softmax层
predictions = Dense(num_classes, activation='softmax')(x)

# 创建新的模型
model = Model(inputs=input_tensor, outputs=predictions)