keras 多任务多loss

记录一下：

# Three loss functions
category_predict1 = Dense(100, activation='softmax', name='ctg_out_1')(
    Dropout(0.5)(feature1)
)
category_predict2 = Dense(100, activation='softmax', name='ctg_out_2')(
    Dropout(0.5)(feature2)
)
dis = Lambda(eucl_dist, name='square')([feature1, feature2])
judge = Dense(2, activation='softmax', name='bin_out')(dis)
model = Model(inputs=[img1, img2], outputs=[category_predict1, category_predict2, judge])
model.compile(optimizer=SGD(lr=0.0001, momentum=0.9),
              loss={
    
    
                  'ctg_out_1': 'categorical_crossentropy',
                  'ctg_out_2': 'categorical_crossentropy',
                  'bin_out': 'categorical_crossentropy'},
              loss_weights={
    
    
                  'ctg_out_1': 1.,
                  'ctg_out_2': 1.,
                  'bin_out': 0.5
              },
              metrics=['accuracy'])
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作者：maocaisheng 
来源：CSDN 
原文：https://blog.csdn.net/u012938704/article/details/79904173 
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