Segmentation fault (core dumped)

[geekyutao]

Hi, amazing work! I followed the step-by-step installation instruction but met the following error. Do you have any ideas about this? Did I miss modify something? Thank you!

2022-05-11 21:08:26,489 fcos_core.trainer INFO: Start training
DA_ON: True
2022-05-11 21:10:25,284 fcos_core.trainer INFO: eta: 6 days, 20:56:49 iter: 20 loss_ds: 6.1977 (6.9134) node_loss: 2.0234 (2.0159) mat_loss_aff: 0.0991 (0.0992) mat_loss_qu: 0.0005 (0.0005) loss_cls: 0.6540 (0.7507) loss_reg: 1.3081 (1.9726) loss_centerness: 0.6631 (0.6738) loss_adv_P7: 0.2785 (0.2792) loss_adv_P6: 0.2755 (0.2747) loss_adv_P5: 0.2736 (0.2740) loss_adv_P4: 0.2750 (0.2750) loss_adv_P3: 0.2762 (0.2762) time: 4.4850 (5.9393) data: 0.0478 (1.7929) dis_loss: 0.0604 (0.0615) lr_backbone: 0.000833 lr_middle_head: 0.001667 lr_fcos: 0.000833 lr_dis: 0.000833 max mem: 10271
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
BLAS : Program is Terminated. Because you tried to allocate too many memory regions.
Segmentation fault (core dumped)

[wymanCV]

Hi, thanks. I think you have installed this project correctly since you can train the model. I just tried searching about it and found this one, which seems to be related to CPU.

I am not sure weather you can solve this by setting WITH_CLUSTER_UPDATE (in the YAML file) False as we implement the spectral clustering algorithm with KNN on CPU. If it can work, you can reset it True and tune the n_job in the "update_seed" function of graph_matching_head. (n_job=-1 will use all CPU cores in parallel)

[geekyutao]

Thank you for the tips! I turned off WITH_CLUSTER_UPDATE and the issue has been solved. This was likely caused by insufficient CPU cores.