把这段代码改为分类损失 loss = F.relu(dis_a + self.args.margin_hrt - dis_b).sum()
时间: 2023-06-14 12:04:59 浏览: 43
好的,将代码修改如下:
```python
class HRTNet(nn.Module):
def __init__(self, args):
super(HRTNet, self).__init__()
self.args = args
self.entity_emb = nn.Embedding(args.ent_total, args.hidden_size)
self.relation_emb = nn.Embedding(args.rel_total, args.hidden_size)
self.margin_loss = nn.MarginRankingLoss(args.margin_hrt, reduction='sum')
def forward(self, pos_h, pos_t, pos_r, neg_h, neg_t, neg_r):
pos_h_e = self.entity_emb(pos_h)
pos_t_e = self.entity_emb(pos_t)
pos_r_e = self.relation_emb(pos_r)
neg_h_e = self.entity_emb(neg_h)
neg_t_e = self.entity_emb(neg_t)
neg_r_e = self.relation_emb(neg_r)
dis_pos = torch.norm(pos_h_e + pos_r_e - pos_t_e, p=2, dim=-1)
dis_neg = torch.norm(neg_h_e + neg_r_e - neg_t_e, p=2, dim=-1)
loss = F.relu(dis_pos - dis_neg + self.args.margin_hrt).sum()
return loss
```
其中,将 `nn.MarginRankingLoss` 替换为 `F.relu` 函数,同时修改输入参数即可。