INNER CODE UNIT · Python

hist

nv-tlabs/GSCNN · loss.py:130

            hist = ((hist != 0) * self.upper_bound * (1 / hist)) + 1
        else:
            hist = ((hist != 0) * self.upper_bound * (1 - hist)) + 1
        return hist

    def forward(self, inputs, targets):
        target_cpu = targets.data.cpu().numpy()
        if self.batch_weights:
            weights = self.calculateWeights(target_cpu)
            self.nll_loss.weight = torch.Tensor(weights).cuda()

        loss = 0.0
        for i in range(0, inputs.shape[0]):
            if not self.batch_weights:
                weights = self.calculateWeights(target_cpu[i])
                self.nll_loss.weight = torch.Tensor(weights).cuda()
            
            loss += self.nll_loss(F.log_softmax(inputs[i].unsqueeze(0)),

View source record →