Source code for neuralkg.loss.CrossE_Loss

import torch
import torch.nn.functional as F
import torch.nn as nn
from IPython import embed


[docs]class CrossE_Loss(nn.Module): def __init__(self, args, model): super(CrossE_Loss, self).__init__() self.args = args self.model = model
[docs] def forward(self, score, label): return -torch.sum(torch.log(torch.clamp(score, 1e-10, 1.0)) * torch.clamp(label, 0.0, 1.0) + \ torch.log(torch.clamp(1-score, 1e-10, 1.0)) * torch.clamp(-label, 0.0, 1.0))