ValueError: matrix contains invalid numeric entries

[nankepan]

Hi, first of all, thank you for your wonderful work.
When I ran the main.py to tain a model on a2d_sentences datasset, it occured an error at 23th epoch on this line :
"_lsap_module.calculate_assignment(cost_matrix, maximize)".

I didn't change anything, how can I solve it？

the error is like:
Traceback (most recent call last):
File "/data1/liunian2/nkp/RVOS/MTTR-main/main.py", line 79, in
run(process_id=0, args=args)
File "/data1/liunian2/nkp/RVOS/MTTR-main/main.py", line 20, in run
trainer.train()
File "/data1/liunian2/nkp/RVOS/MTTR-main/trainer.py", line 142, in train
loss_dict = self.criterion(outputs, targets)
File "/home/liunian2/anaconda3/envs/mttr/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/data1/liunian2/nkp/RVOS/MTTR-main/models/criterion.py", line 39, in forward
losses = self.compute_criterion(outputs, targets, losses_to_compute=self.losses)
File "/data1/liunian2/nkp/RVOS/MTTR-main/models/criterion.py", line 53, in compute_criterion
indices = self.matcher(outputs, targets)
File "/home/liunian2/anaconda3/envs/mttr/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/liunian2/anaconda3/envs/mttr/lib/python3.9/site-packages/torch/autograd/grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "/data1/liunian2/nkp/RVOS/MTTR-main/models/matcher.py", line 81, in forward
indices = [linear_sum_assignment(c[i]) for i, c in enumerate(C.split(num_traj_per_batch, -1))]
File "/data1/liunian2/nkp/RVOS/MTTR-main/models/matcher.py", line 81, in
indices = [linear_sum_assignment(c[i]) for i, c in enumerate(C.split(num_traj_per_batch, -1))]
File "/home/liunian2/anaconda3/envs/mttr/lib/python3.9/site-packages/scipy/optimize/_lsap.py", line 86, in linear_sum_assignment
return _lsap_module.calculate_assignment(cost_matrix, maximize)
ValueError: matrix contains invalid numeric entries

[Feiyu-Yao]

Hi, I meet the same problem as you, have you solved this problem?

[xiejialong]

same problem!

[canyetat]

same problem! have you solved this problem?