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- from torch import nn
- class RobustScannerLoss(nn.Module):
- def __init__(self, **kwargs):
- super(RobustScannerLoss, self).__init__()
- ignore_index = kwargs.get('ignore_index', 38)
- self.loss_func = nn.CrossEntropyLoss(reduction='mean',
- ignore_index=ignore_index)
- def forward(self, pred, batch):
- pred = pred[:, :-1, :]
- label = batch[1][:, 1:].reshape([-1])
- inputs = pred.reshape([-1, pred.shape[2]])
- loss = self.loss_func(inputs, label)
- return {'loss': loss}
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