softplus failed to compute its gradient

[Jiaming Liu]

i use your version of circle loss to do a image classification
when loss.backward() an error occured

in your code loss -> forward
loss_temp = torch.logsumexp(logit_n, dim=0) + torch.logsumexp(logit_p, dim=0) loss = self.soft_plus(loss_temp)
there is an error that softplus cannot compute its gradient, maybe the F.softplus take an inplace operation?

my version is python 3.7 and torch 1.5.0

Warning: Error detected in SoftplusBackward. Traceback of forward call that caused the error: File "train.py", line 473, in <module> train_fun(args, train_loader, feat_loader, i) File "train.py", line 221, in train_fun loss = criterion(embed_feat, labels) File "/home/anaconda3/envs/ljm/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in __call__ result = self.forward(*input, **kwargs) File "/home/Project/SDC-IL/SDC-IL/losses/circle_loss.py", line 51, in forward loss = F.softplus(loss_temp) (print_stack at /opt/conda/conda-bld/pytorch_1587428266983/work/torch/csrc/autograd/python_anomaly_mode.cpp:60) iter 0Traceback (most recent call last): File "train.py", line 473, in <module> train_fun(args, train_loader, feat_loader, i) File "train.py", line 230, in train_fun loss.backward() File "/home/anaconda3/envs/ljm/lib/python3.7/site-packages/torch/tensor.py", line 198, in backward torch.autogr ad.backward(self, gradient, retain_graph, create_graph) File "/home/anaconda3/envs/ljm/lib/python3.7/site-packages/torch/autograd/__init__.py", line 100, in backward allow_unreachable=True) # allow_unreachable flag RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.cuda.FloatTensor []], which is output 0 of SoftplusBackward, is at version 1; expected version 0 instead. Hint: the backtrace further above shows the operation that failed to compute its gradient. The variable in question was changed in there or anywhere later. Good luck!

[Jiaming Liu]

Sorry, it is something on my own code, not this circleloss.
i replace loss += loss_aug by loss = loss + loss_aug that's cause by inplace operation