core.py 文件源码

def get_output(self, train=False):
        print(len(self.layers))
        u=self.layers[0].get_output(train)
        t=self.layers[1].get_output(train)
        #tp=t[0]
        #tn=t[1]
        #un=T.dot(u,u)
        #return [T.dot(u,tp)/(un*T.dot(tp,tp)) ,T.dot(u,tn)/(un*T.dot(tn,tn))]
        #theano.printing.pprint('vals')
        #x=T.dvector()
        #printed_u = hello_world_op(x)
        #f = theano.function([x], printed_u)
        #f(['here'])

        #T.reshape(u,[2,1])
        #T.reshape(t,[1,2,2])
        #d=T.dot(t.dimshuffle(1, 0, 2), u)
        #u1=self.activation(u)
        #t.reshape([2,2,2])
        return T.sum( (([u ,u]*t.dimshuffle(1,0,2)).dimshuffle(1,0,2)),2)#.reshape([2,2])
        #return d.dimshuffle(1,0,2) #just dot product