label_smoothing_pytorch.py

"""
from https://www.kaggle.com/shonenkov/tpu-training-super-fast-xlmroberta
"""

import torch.nn as nn

class LabelSmoothing(nn.Module):
    def __init__(self, smoothing = 0.1):
        super(LabelSmoothing, self).__init__()
        self.confidence = 1.0 - smoothing
        self.smoothing = smoothing

    def forward(self, x, target):
        if self.training:
            x = x.float()
            target = target.float()
            logprobs = torch.nn.functional.log_softmax(x, dim = -1)
            nll_loss = -logprobs * target
            nll_loss = nll_loss.sum(-1)
            smooth_loss = -logprobs.mean(dim=-1)
            loss = self.confidence * nll_loss + self.smoothing * smooth_loss
            return loss.mean()
        else:
            return torch.nn.functional.cross_entropy(x, target)