5a9c6aa03ea55ad85601c0c33ff762d6a2e2c7fa,torch_geometric/nn/models/node2vec.py,Node2Vec,loss,#Node2Vec#Any#Any#,86

Before Change

        // Negative sampling loss.
        num_negative_samples = self.num_negative_samples
        if num_negative_samples is None:
            num_negative_samples = rest.size(1)

        neg_sample = torch.randint(self.num_nodes,
                                   (walk.size(0), num_negative_samples),
                                   dtype=torch.long, device=edge_index.device)
        h_neg_rest = self.embedding(neg_sample)

        out = (h_start * h_neg_rest).sum(dim=-1).view(-1)
        neg_loss = -torch.log(1 - torch.sigmoid(out) + EPS).mean()

After Change

        h_start = self.embedding(start).view(neg_rw.size(0), 1,
                                             self.embedding_dim)
        h_rest = self.embedding(rest.view(-1)).view(neg_rw.size(0), -1,
                                                    self.embedding_dim)

        out = (h_start * h_rest).sum(dim=-1).view(-1)
        neg_loss = -torch.log(1 - torch.sigmoid(out) + EPS).mean()

Instances