2ca943ad4981b69af135e179144c559c872b5edd,cube/models/vocoder.py,BeeCoder,_predict_one,#BeeCoder#Any#Any#Any#,89

Before Change

        output_real = self.output_real_w.expr(update=True) * hidden + self.output_real_b.expr(update=True)
        output_imag = self.output_imag_w.expr(update=True) * hidden + self.output_imag_b.expr(update=True)
        output = [output_real, output_imag]
        return output

    def learn(self, wave, mgc, batch_size):

After Change

            hidden_power = dy.tanh(w.expr(update=True) * hidden_power + b.expr(update=True))

        for w, b in zip(self.hidden_w_angle, self.hidden_b_angle):
            hidden_angle = dy.tanh(w.expr(update=True) * hidden_angle + b.expr(update=True))

        output_power = dy.logistic(self.output_power_w.expr(update=True) * hidden_power +
                                   self.output_power_b.expr(update=True))
        output_angle = self.output_angle_w.expr(update=True) * hidden_angle + \

Instances