6cd076a14fa163cae38ff7768daf810d851c4885,keras/layers/recurrent.py,SimpleDeepRNN,_step,#SimpleDeepRNN#,102

Before Change

        o = args[0]
        for i in range(1, self.depth+1):
            o += self.inner_activation(T.dot(args[i], args[i+self.depth]))
        return o        

    def output(self, train):
        X = self.get_input(train)

After Change

        o = args[0]
        for i in range(1, self.depth+1):
            o += self.inner_activation(T.dot(args[i], args[i+self.depth]))
        return self.activation(o)

    def output(self, train):
        X = self.get_input(train)
        X = X.dimshuffle((1,0,2)) 

Instances