ValueError: You are trying to load a weight file containing 12 layers into a model with 2 layers.

本文解决两个问题：

1、ValueError: You are trying to load a weight file containing 12 layers into a model with 2 layers.

2、The name "embedding_1_input" is used 3 times in the model

第一个问题：

相当麻烦的一个问题，百度和google都没有

而且似乎有时候不能重现，有时候又莫名其妙消失了。

结果实验，不要使用下面的语句，原因是，这种语句不能针对使用Merge类建立的嵌套型神经网络，

这种报错在何种情况下会发生呢？

假定

model_left、model_right和model_3是三个神经网络

然后用以下代码让这三个子神经网络组合

merged = Merge([model_left, model_right,model_3], mode='concat') #merge
model = Sequential()
model.add(merged) # add merge

然后输入

model.save('./model/my_model_weights.h5')
model=load_model('./model/my_model_weights.h5')

就会报错

ValueError: You are trying to load a weight file containing 12 layers into a model with 2 layers.

因为这个神经网络是嵌套的，也算是这个python库的一个bug吧。

改用以下代码即可。

model.save_weights('test.h5')
model.load_weights('test.h5',by_name=True)
json_string = model.to_json()
model = model_from_json(json_string)

第二个问题：

但是，由于该神经网络存在嵌套

即使改为以上代码后，想要在加载模型后。使用plot_model绘制神经网络，也同样是不可能的，会有如下报错：

The name "embedding_1_input" is used 3 times in the model

具体报错：

RuntimeError: (u'The name "embedding_1_input" is used 3 times in the model. All layer names should be unique. Layer names: ',
[u'embedding_1_input',u'embedding_1_input',u'embedding_1_input',u'embedding_1',u'embedding_1',u'embedding_1',u'conv1d_1',u'conv1d_4',u'conv1d_7',u'max_pooling1d_1',u'max_pooling1d_4',u'max_pooling1d_7',u'conv1d_2',u'conv1d_5',u'conv1d_8',u'max_pooling1d_2',u'max_pooling1d_5',u'max_pooling1d_8',u'conv1d_3',u'conv1d_6',u'conv1d_9',u'max_pooling1d_3',u'max_pooling1d_6',u'max_pooling1d_9',u'flatten_1',u'flatten_2',u'flatten_3',u'merge_1',u'dense_1',u'dense_2'
])

所以对于这种嵌套型神经网络，想要绘制神经网络的结构图，在进行训练模型后就要立刻使用

plot_model(model, to_file='model.png')

不要在保存模型、加载模型后再去使用上面这句代码，是会报错有layer重名的。

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