parsing.py 文件源码

def _transform_decoder_init_state(self, hn):
        if isinstance(hn, tuple):
            hn, cn = hn
            # hn [2 * num_layers, batch, hidden_size]
            num_dir, batch, hidden_size = cn.size()
            # first convert cn t0 [batch, 2 * num_layers, hidden_size]
            cn = cn.transpose(0, 1).contiguous()
            # then view to [batch, num_layers, 2 * hidden_size] --> [num_layer, batch, 2 * num_layers]
            cn = cn.view(batch, num_dir / 2, 2 * hidden_size).transpose(0, 1)
            # take hx_dense to [num_layers, batch, hidden_size]
            cn = self.hx_dense(cn)
            # hn is tanh(cn)
            hn = F.tanh(cn)
            hn = (hn, cn)
        else:
            # hn [2 * num_layers, batch, hidden_size]
            num_dir, batch, hidden_size = hn.size()
            # first convert hn t0 [batch, 2 * num_layers, hidden_size]
            hn = hn.transpose(0, 1).contiguous()
            # then view to [batch, num_layers, 2 * hidden_size] --> [num_layer, batch, 2 * num_layers]
            hn = hn.view(batch, num_dir / 2, 2 * hidden_size).transpose(0, 1)
            # take hx_dense to [num_layers, batch, hidden_size]
            hn = F.tanh(self.hx_dense(hn))
        return hn