Zhuysheng
commented
5 months ago It seems like the tensor dimension mismatch, maybe target=target.unsqueeze(dim=-1) could solve your problem.
Open 223d opened 6 months ago
Zhuysheng
commented
5 months ago It seems like the tensor dimension mismatch, maybe target=target.unsqueeze(dim=-1) could solve your problem.
Hi ,Can you help me take a look at a question here？ thankyou!
Traceback (most recent call last): File "/home/zlq/pycharm-professional-2023.1.3/pycharm-2023.1.3/plugins/python/helpers/pydev/pydevd.py", line 1496, in _exec pydev_imports.execfile(file, globals, locals) # execute the script File "/home/zlq/pycharm-professional-2023.1.3/pycharm-2023.1.3/plugins/python/helpers/pydev/_pydev_imps/_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "/home/zlq/project/RVTCLR-main/main.py", line 57, in
p.start()
File "/home/zlq/project/RVTCLR-main/processor/processor.py", line 179, in start
self.train(epoch + 1)
File "/home/zlq/project/RVTCLR-main/processor/pretrain_skeletonclr.py", line 108, in train
loss3 = self.loss_2(logits_M[0], logits_M[1], labels_M)
File "/home/zlq/miniconda3/envs/RVTCLR/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/zlq/miniconda3/envs/RVTCLR/lib/python3.7/site-packages/torch/nn/modules/loss.py", line 1333, in forward
return F.margin_ranking_loss(input1, input2, target, margin=self.margin, reduction=self.reduction)
File "/home/zlq/miniconda3/envs/RVTCLR/lib/python3.7/site-packages/torch/nn/functional.py", line 3328, in margin_ranking_loss
"input1: {}, input2: {}, target: {} ".format(input1.size(), input2.size(), target.size())
RuntimeError: margin_ranking_loss : All input tensors should have same dimension but got sizes: input1: torch.Size([2, 1]), input2: torch.Size([2, 1]), target: torch.Size([2])
python-BaseException