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17 lines
546 B
Python
17 lines
546 B
Python
import torch.nn.functional as F
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from torch import nn
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class LabelSmoothingLoss(nn.Module):
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def __init__(self, epsilon= 0.5, reduction='mean'):
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super().__init__()
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self.epsilon = epsilon
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self.reduction = reduction
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def forward(self, pred, target):
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n = pred.size()[-1]
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log_pred = F.log_softmax(pred, dim=-1)
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loss = -log_pred.sum(dim=-1).mean()
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nll = F.nll_loss(log_pred, target, reduction=self.reduction)
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out = (1-self.epsilon)*nll + self.epsilon*(loss / n)
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return out
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