import torch
import torch.nn.functional as F
def dissimilarity_loss(model):
total_loss = 0
for name, param in model.named_parameters():
if 'weight' in name and len(param.size()) == 4: # This is a convolution layer
n_filters = param.size(0)
for i in range(n_filters):
for j in range(i + 1, n_filters):
total_loss += F.cosine_similarity(param[i], param[j], dim=0)
return total_loss
不相似损失函数
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转载自blog.csdn.net/jacke121/article/details/132961659
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