def forward()

in trainer/loss.py [0:0]

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

    def forward(self, im, s):
        scores = self.sim(im, s)
        diagonal = scores.diag().view(im.size(0), 1)
        d1 = diagonal.expand_as(scores)
        d2 = diagonal.t().expand_as(scores)
        cost_s = (self.margin + scores - d1).clamp(min=0)
        cost_im = (self.margin + scores - d2).clamp(min=0)
        mask = torch.eye(scores.size(0)) > .5
        if self.use_cuda:
            mask = mask.cuda()
        cost_s = cost_s.masked_fill_(mask, 0)
        cost_im = cost_im.masked_fill_(mask, 0)
        return (cost_s.sum() + cost_im.sum()).div(im.shape[0] * s.shape[0])