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import torch | |
import torch.nn as nn | |
class RegularizationLoss(nn.Module): | |
""" | |
Enforce losses on pixels without any gts. | |
""" | |
def __init__(self, loss_weight=0.1, data_type=['sfm', 'stereo', 'lidar'], **kwargs): | |
super(RegularizationLoss, self).__init__() | |
self.loss_weight = loss_weight | |
self.data_type = data_type | |
self.eps = 1e-6 | |
def forward(self, prediction, target, mask=None, **kwargs): | |
pred_wo_gt = prediction[~mask] | |
#loss = - torch.sum(pred_wo_gt) / (pred_wo_gt.numel() + 1e-8) | |
loss = 1/ (torch.sum(pred_wo_gt) / (pred_wo_gt.numel() + self.eps)) | |
return loss * self.loss_weight |