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TIP2022 Adaptive Boosting (AdaBoost) for Domain Adaptation ? :woman_shrugging: Why not ! :ok_woman:
Home Page: https://arxiv.org/abs/2103.15685
Contact Me:
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RESTORE_FROM = 'http://vllab.ucmerced.edu/ytsai/CVPR18/DeepLab_resnet_pretrained_init-f81d91e8.pth'
in trainer_ms.py ,this pth "404 not found"
def update_class_criterion(self, labels):
weight = torch.FloatTensor(self.num_classes).zero_().cuda()
weight += 1
count = torch.FloatTensor(self.num_classes).zero_().cuda()
often = torch.FloatTensor(self.num_classes).zero_().cuda()
often += 1
print(labels.shape)
n, h, w = labels.shape
for i in range(self.num_classes):
count[i] = torch.sum(labels==i)
if count[i] < 64*64*n: #small objective
weight[i] = self.max_value
if self.often_balance:
often[count == 0] = self.max_value
self.often_weight = 0.9 * self.often_weight + 0.1 * often
self.class_weight = weight * self.often_weight
print(self.class_weight)
if self.focal:
print('Using Focal loss')
return FocalLoss(weight = self.class_weight, ignore_index=255, gamma = self.gamma)
else:
return nn.CrossEntropyLoss(weight = self.class_weight, ignore_index=255)
I find the update_class_criterion function in your trainer_ms.py.
I want to know who created it in the first place because I want to change it somewhere, I need quote.
I think it's a very come class_criterion If you know, could you tell me.
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