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why used yt as the label for feature ft, ft_up, ft_low,it's different from your paper.
here is the code,calculate the loss Lsemi
"loss_global_eug, prec_global_eug = self.criterions[1](outputs_eug[1], pids_eug, epoch)
for i, output_p in enumerate(outputs_eug[0]):
loss_tri, prec_tri = self.criterions[0](output_p, pids_eug, epoch) loss_os += loss_tri"
and it is different from loss Lssg,
code here
"loss_global, prec_global = self.criterions[1](outputs[1], pids[0], epoch)
for i, output_p in enumerate(outputs[0]):
loss_tri, prec_tri = self.criterions[0](output_p, pids[i], epoch) loss_uns += loss_tri"
I'm tring to recurrent your paper,pls help me,Thank you
The text was updated successfully, but these errors were encountered:
why used yt as the label for feature ft, ft_up, ft_low,it's different from your paper.
here is the code,calculate the loss Lsemi
"loss_global_eug, prec_global_eug = self.criterions[1](outputs_eug[1], pids_eug, epoch)
for i, output_p in enumerate(outputs_eug[0]):
loss_tri, prec_tri = self.criterions[0](output_p, pids_eug, epoch) loss_os += loss_tri"
and it is different from loss Lssg,
code here
"loss_global, prec_global = self.criterions[1](outputs[1], pids[0], epoch)
for i, output_p in enumerate(outputs[0]):
loss_tri, prec_tri = self.criterions[0](output_p, pids[i], epoch) loss_uns += loss_tri"
I'm tring to recurrent your paper,pls help me,Thank you
The text was updated successfully, but these errors were encountered: