def forward()

in model.py [0:0]

• 28 lines of code
• 9 McCabe index (conditional complexity)

    def forward(self, img, spec, whichhead=0):
        img_features = self.video_network(img).squeeze()
        aud_features = self.audio_network(spec).squeeze()

        if self.return_features:
            return img_features, aud_features
        if len(aud_features.shape) == 1:
            aud_features = aud_features.unsqueeze(0)
        if len(img_features.shape) == 1:
            img_features = img_features.unsqueeze(0)

        if self.hc == 1:
            nce_img_features = self.mlp_v(img_features)
            nce_aud_features = self.mlp_a(aud_features)
            if self.norm_feat:
                nce_img_features = F.normalize(nce_img_features, p=2, dim=1)
                nce_aud_features = F.normalize(nce_aud_features, p=2, dim=1)
            return nce_img_features, nce_aud_features
        elif self.hc > 1:
            # note: will return lists here.
            outs1 = []
            outs2 = []
            for head in range(self.hc):
                img_f = getattr(self, "mlp_v%d"%head)(img_features)
                aud_f = getattr(self, "mlp_a%d"%head)(aud_features)
                if self.norm_feat:
                    img_f = F.normalize(img_f, p=2, dim=1)
                    aud_f = F.normalize(aud_f, p=2, dim=1)
                outs1.append(img_f)
                outs2.append(aud_f)
            return outs1, outs2