keras内置loss函数中不包含rmse均方根误差,当运行如下代码:
losses = {"Tf1": "rmse", "Tf2": "rmse", "Tr1": "rmse", "Tr2": "rmse", "A1": "rmse", "A2": "rmse"}
metric = {"Tf1": "mae", "Tf2": "mae", "Tr1": "mae", "Tr2": "mae", "A1": "mae", "A2": "mae"}
modelD.compile(loss=losses,
optimizer=sgd,
metrics=metric)
会报错:
ValueError: Unknown loss function: rmse. Please ensure this object is passed to the `custom_objects` argument. See https://www.tensorflow.org/guide/keras/save_and_serialize#registering_the_custom_object for details.
有什么办法可以如代码中表达的需要那样以Tf1,Tf2,Tr1,Tr2,A1,A2的rmse同时作为loss来训练神经网络?