def forward()

in hype_kg/codes/model.py [0:0]

• 37 lines of code
• 13 McCabe index (conditional complexity)

    def forward(self, embeds1, embeds1_o, embeds2, embeds2_o, embeds3 = [], embeds3_o=[]):
        if self.center_use_offset:
            temp1 = torch.cat([embeds1, embeds1_o], dim=1)
            temp2 = torch.cat([embeds2, embeds2_o], dim=1)
            if len(embeds3) > 0:
                embeds3 = embeds3
                if embeds3_o is not None: embeds3_o = embeds3_o
                temp3 = torch.cat([embeds3, embeds3_o], dim=1)

        else:
            temp1 = embeds1
            temp2 = embeds2
            if len(embeds3) > 0:
                temp3 = embeds3

        if self.bn == 'no':
            temp1 = F.relu(temp1.mm(self.pre_mats))
            temp2 = F.relu(temp2.mm(self.pre_mats))
        elif self.bn == 'before':
            temp1 = F.relu(self.bn1(temp1.mm(self.pre_mats)))
            temp2 = F.relu(self.bn2(temp2.mm(self.pre_mats)))
        elif self.bn == 'after':
            temp1 = self.bn1(F.relu(temp1.mm(self.pre_mats)))
            temp2 = self.bn2(F.relu(temp2.mm(self.pre_mats)))
        if len(embeds3) > 0:
            if self.bn == 'no':
                temp3 = F.relu(temp3.mm(self.pre_mats))
            elif self.bn == 'before':
                temp3 = F.relu(self.bn3(temp3.mm(self.pre_mats)))
            elif self.bn == 'after':
                temp3 = self.bn3(F.relu(temp3.mm(self.pre_mats)))
            combined = torch.stack([temp1, temp2, temp3])
        else:
            combined = torch.stack([temp1, temp2])
        combined = self.agg_func(combined, dim=0)
        if type(combined) == tuple:
            combined = combined[0]
        combined = combined.mm(self.post_mats)
        return combined