layers.py 文件源码

def lyr_linear(
        self, name_,
        s_x_,
        idim_, odim_,
        init_=None, bias_=0., params_di_='params'):
        '''
        dense matrix multiplication, optionally adding a bias vector
        '''
        name_W = name_+'_w'
        name_B = name_+'_b'
        self.set_vars(params_di_)
        if init_ is None:
            init_ = dict(init_=[1.4/sqrt(idim_+odim_)])
        v_W = self.get_variable(name_W, (idim_,odim_), **init_)
        if bias_ is None:
            s_ret = T.dot(s_x_, v_W)
        else:
            v_B = self.get_variable(name_B, (odim_,), bias_)
            s_ret = T.dot(s_x_, v_W) + v_B
        return s_ret