softmax_variants Various loss functions for softmax variants: center loss, cosface loss, large-margin gaussian mixture, COCOLoss implemented by pytorch 0.3.1 the training dataset is MNIST You can directly run code train_mnist_xxx.py to reproduce the result The reference papers are as follow: Ce...
cos_loss=tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y,logits=value))returncos_loss
然后,rank regularization模块将这些权重按降序排列,将它们分成两组(即高重要度权重和低重要度权重),并通过在两组的平均权重之间设置一个margin来对这两组进行正则化。这种正则化是通过一个损失函数来实现的,称为Rank Regularization loss (RR-Loss)。rank regularization模块确保第一个模块学习有意义的权值来突出某些样...
Although I'm using version 1.9, I think the problem still exists on master. I think the problem might be in this line of code:https://github.com/pytorch/pytorch/blob/main/aten/src/ATen/native/cuda/SoftMax.cu#L667. When dim_size is too large for int, it becomes negative. May I ask...