keras - 在 Keras 中，如何获取与我的模型中包含的 "Model"对象关联的层名称？

Question

我在初始基础上使用 VGG16 网络构建了一个 Sequential 模型，例如:

from keras.applications import VGG16
conv_base = VGG16(weights='imagenet',
                  # do not include the top, fully-connected Dense layers 
                  include_top=False,
                  input_shape=(150, 150, 3))

from keras import models
from keras import layers

model = models.Sequential()
model.add(conv_base)
model.add(layers.Flatten())
model.add(layers.Dense(256, activation='relu'))
# the 3 corresponds to the three output classes
model.add(layers.Dense(3, activation='sigmoid'))

我的模型看起来像这样:

model.summary()

---

Layer (type)                 Output Shape              Param #   
=================================================================
vgg16 (Model)                (None, 4, 4, 512)         14714688  
_________________________________________________________________
flatten_1 (Flatten)          (None, 8192)              0         
_________________________________________________________________
dense_7 (Dense)              (None, 256)               2097408   
_________________________________________________________________
dense_8 (Dense)              (None, 3)                 771       
=================================================================
Total params: 16,812,867
Trainable params: 16,812,867
Non-trainable params: 0
_________________________________________________________________

现在，我想获取与我的网络的 vgg16 模型部分相关联的层名称。 IE。就像是:

layer_name = 'block3_conv1'
filter_index = 0

layer_output = model.get_layer(layer_name).output
loss = K.mean(layer_output[:, :, :, filter_index])

但是，由于 vgg16 卷积显示为模型并且它的层没有暴露，我得到错误:

ValueError: No such layer: block3_conv1

我该怎么做呢？

Answer 1

关键是先做.get_layer在 Model 对象上，然后再做一次 .get_layer在指定特定的 vgg16 层上，然后执行 .output:
layer_output = model.get_layer('vgg16').get_layer('block3_conv1').output