如何解决我可以在Notepad ++中缩进标点和标签吗？
最近，根据我的说法，我从VSCode切换到Notepad ++作为文本编辑器，后者比前者更适合“轻度编辑”。
在<html>中键入</html>会自动在Notepad ++和VSCode中的光标之后创建一个结束符ctrl + shift + enter：但是当我在Notepad ++中按Enter键时，它将结束符放在下一行。要开始添加代码，我需要按enter，这是太多步骤了。如何配置Notepad ++，以便按ctrl + shift + enter会导致自动按def unet_model(input_size = (256,256,1)):
input_ = keras.layers.Input(shape=input_size)
conv1 = keras.layers.Conv2D(64,3,activation = 'relu',padding = 'same',kernel_initializer = 'he_normal')(input_)
conv1 = keras.layers.Conv2D(64,kernel_initializer = 'he_normal')(conv1)
pool1 = keras.layers.MaxPooling2D(pool_size=(2,2))(conv1)
conv2 = keras.layers.Conv2D(128,kernel_initializer = 'he_normal')(pool1)
conv2 = keras.layers.Conv2D(128,kernel_initializer = 'he_normal')(conv2)
pool2 = keras.layers.MaxPooling2D(pool_size=(2,2))(conv2)
conv3 = keras.layers.Conv2D(256,kernel_initializer = 'he_normal')(pool2)
conv3 = keras.layers.Conv2D(256,kernel_initializer = 'he_normal')(conv3)
pool3 = keras.layers.MaxPooling2D(pool_size=(2,2))(conv3)
conv4 = keras.layers.Conv2D(512,kernel_initializer = 'he_normal')(pool3)
conv4 = keras.layers.Conv2D(512,kernel_initializer = 'he_normal')(conv4)
drop4 = keras.layers.Dropout(0.5)(conv4)
pool4 = keras.layers.MaxPooling2D(pool_size=(2,2))(drop4)
conv5 = keras.layers.Conv2D(1024,kernel_initializer = 'he_normal')(pool4)
conv5 = keras.layers.Conv2D(1024,kernel_initializer = 'he_normal')(conv5)
drop5 = keras.layers.Dropout(0.5)(conv5)
up6 = keras.layers.Conv2D(512,2,kernel_initializer = 'he_normal')(keras.layers.UpSampling2D(size = (2,2))(drop5))
merge6 = keras.layers.Concatenate([drop4,up6],axis = 3)
conv6 = keras.layers.Conv2D(512,kernel_initializer = 'he_normal')(merge6)
conv6 = keras.layers.Conv2D(512,kernel_initializer = 'he_normal')(conv6)
up7 = keras.layers.Conv2D(256,2))(conv6))
merge7 = keras.layers.Concatenate([conv3,up7],axis = 3)
conv7 = keras.layers.Conv2D(256,kernel_initializer = 'he_normal')(merge7)
conv7 = keras.layers.Conv2D(256,kernel_initializer = 'he_normal')(conv7)
up8 = keras.layers.Conv2D(128,2))(conv7))
merge8 = keras.layers.Concatenate([conv2,up8],axis = 3)
conv8 = keras.layers.Conv2D(128,kernel_initializer = 'he_normal')(merge8)
conv8 = keras.layers.Conv2D(128,kernel_initializer = 'he_normal')(conv8)
up9 = keras.layers.Conv2D(64,2))(conv8))
merge9 = keras.layers.Concatenate([conv1,up9],axis = 3)
conv9 = keras.layers.Conv2D(64,kernel_initializer = 'he_normal')(merge9)
conv9 = keras.layers.Conv2D(64,kernel_initializer = 'he_normal')(conv9)
conv9 = keras.layers.Conv2D(2,kernel_initializer = 'he_normal')(conv9)
conv10 = keras.layers.Conv2D(1,1,activation = 'softmax')(conv9)
model = keras.Model(inputs = [input_],outputs = [conv10])
model.compile(optimizer = Adam(lr = 1e-4),loss = 'binary_crossentropy',metrics = ['accuracy'])
return model
的过程，并自动允许我编写代码（如VSCode）？
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