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Bayesian

I've changed the weight_loss to :

def weight_loss(self,cur_grad,pre_grad):
	res = []
	for i in range(len(pre_grad)):
		res.append(K.sum(K.square(cur_grad[i] - pre_grad[i])))
	return sum(res)/len(res)

The confusion matrix is confusion matrix

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