INNER CODE UNIT · Python

calculateWeights

nv-tlabs/GSCNN · loss.py:126

    def calculateWeights(self, target):
        hist = np.histogram(target.flatten(), range(
            self.num_classes + 1), normed=True)[0]
        if self.norm:
            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:

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