recurrent.py 文件源码

def _step_batch(self, x_t, mask, h_t_1, w, u, b):
        """
        step function of forward in batch version
        :param x_t:   (batch, in)
        :param mask:  (batch, )
        :param h_t_1: (batch, hidden)
        :param w:     (hidden, in)
        :param u:     (hidden, hidden)
        :param b:     (hidden)
        :return:      (batch, hidden)
        """
        # (batch, in) (in, hidden) -> (batch, hidden)
        h_t_1 = T.reshape(h_t_1, (h_t_1.shape[0], 8, 8))
        x_t = T.reshape(x_t, (x_t.shape[0], 8, 8))
        x_t = x_t / x_t.norm(2, axis=1)[:, None, :]
        h_t = self.act.activate(T.dot(x_t, w.T) + T.dot(h_t_1, u.T) + b)
        h_t = h_t / h_t.norm(2, axis=1)[:, None, :]
        h_t_1 = T.reshape(h_t_1, (h_t_1.shape[0], 64))
        h_t = T.reshape(h_t, (h_t.shape[0], 64))
        # (batch, hidden) * (batch, None) + (batch, hidden) * (batch, None) -> (batch, hidden)
        return h_t * mask[:, None] + h_t_1 * (1 - mask[:, None])