一個例子：

print("Loading vgg19 weights...")

vgg_model = VGG19(include_top=False, weights='imagenet')

from_vgg = dict() # 因為模型定義中的layer的名字與原始vgg名字不同，所以需要調(diào)整

from_vgg['conv1_1'] = 'block1_conv1'

from_vgg['conv1_2'] = 'block1_conv2'

from_vgg['conv2_1'] = 'block2_conv1'

from_vgg['conv2_2'] = 'block2_conv2'

from_vgg['conv3_1'] = 'block3_conv1'

from_vgg['conv3_2'] = 'block3_conv2'

from_vgg['conv3_3'] = 'block3_conv3'

from_vgg['conv3_4'] = 'block3_conv4'

from_vgg['conv4_1'] = 'block4_conv1'

from_vgg['conv4_2'] = 'block4_conv2'

for layer in model.layers:

if layer.name in from_vgg:

vgg_layer_name = from_vgg[layer.name]

layer.set_weights(vgg_model.get_layer(vgg_layer_name).get_weights())

print("Loaded VGG19 layer: " + vgg_layer_name)

densenet.load_weights('model/densenet_weight/densenet_bottom.h5')

# densenet.save_weights('densenet_bottom.h5')

# print(densenet.weights)# 獲得模型所有權值

t=densenet.get_layer('densenet_conv1/bn')

print(t)

print(densenet.get_weights()[2])

以上這篇keras獲得某一層或者某層權重的輸出實例就是小編分享給大家的全部內(nèi)容了，希望能給大家一個參考，也希望大家多多支持腳本之家。

總結

以上是生活随笔為你收集整理的keras提取模型中的某一层_keras获得某一层或者某层权重的输出实例的全部內(nèi)容，希望文章能夠幫你解決所遇到的問題。

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