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hello,your code loss.py and center_loss_pytorch are similar,but center loss has another implement,KaiyangZhou/pytorch-center-loss#20 ,therefore, can the scheme be modified as follows?
class CenterLoss(nn.Module):
def __init__(self, num_class=10, num_feature=2):
super(CenterLoss, self).__init__()
self.num_class = num_class
self.num_feature = num_feature
self.centers = nn.Parameter(torch.randn(self.num_class, self.num_feature))
def forward(self, feat, A, label):
center = self.centers[label]
dist = (A * ((feat - center).pow(2))).sum(dim=-1)
loss = torch.clamp(dist, min=1e-12, max=1e+12).mean(dim=-1)
return loss
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