keras metric different during training

问题

I have implemented a custom metric based on SIM and when i try the code it works. I have implemented it using tensors and np arrays and both give the same results. However when I start fitting the model the values given back are a lot higher then the values I get when i load the weights generated by the training and applying the same function.

My function is:

def SIM(y_true,y_pred):

    n_y_true=y_true/(K.sum(y_true)+K.epsilon())    
    n_y_pred=y_pred/(K.sum(y_pred)+K.epsilon())

    return K.mean(K.sum( K.minimum(n_y_true, n_y_pred)))

When I compile the Keras model I add this to the metrics and during training it gives for example SIM: 0.7092. When i load the weights and try it the SIM score is around 0.3. The correct weights are loaded (when restarting training with these weights the same values popup). Does anybody know if I am doing anything wrong?

Why are the metrics given back during training so much higher compared to running the function over a batch?

来源：https://stackoverflow.com/questions/48167733/keras-metric-different-during-training