parsing.py 文件源码

def decode(self, input_word, input_char, input_pos, mask=None, length=None, hx=None, leading_symbolic=0):
        # out_arc shape [batch, length, length]
        out_arc, out_type, mask, length = self.forward(input_word, input_char, input_pos,
                                                       mask=mask, length=length, hx=hx)
        out_arc = out_arc.data
        batch, max_len, _ = out_arc.size()
        # set diagonal elements to -inf
        out_arc = out_arc + torch.diag(out_arc.new(max_len).fill_(-np.inf))
        # set invalid positions to -inf
        if mask is not None:
            # minus_mask = (1 - mask.data).byte().view(batch, max_len, 1)
            minus_mask = (1 - mask.data).byte().unsqueeze(2)
            out_arc.masked_fill_(minus_mask, -np.inf)

        # compute naive predictions.
        # predition shape = [batch, length]
        _, heads = out_arc.max(dim=1)

        types = self._decode_types(out_type, heads, leading_symbolic)

        return heads.cpu().numpy(), types.data.cpu().numpy()