Comments (5)
If you have not solved the problem yet, I suggest you check the following:
i) Check if GPU has enough memory. The image resolution or the batch size might be large.
ii) You might have to change the name of the last layer if you are using different number of classes (This is only if you are fine-tuning a pretrained network).
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If anything you have tried and you still don't deal it, try " sudo rm -rf ~/.nv/"
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If anything you have tried and you still don't deal it, try " sudo rm -rf ~/.nv/"
That really worked for me, THX!
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Actually, I was out of GPU memory. After killing some application, the error is fixed.
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when I was troulbed in this problem, my finally ways was just changed the gpu ID.
Caffe default gpu number is 0, so if your gpu 0 is occupied,you‘d better change thd ID,otherwise the error 'Abort(core dumped)' could be generated.
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Related Issues (20)
- benchmark result on val HOT 2
- input image HOT 1
- Really bad performance on TX2 HOT 3
- OpenCV Error
- Dataset ratio to be used in Fine-Tuning own Dataset
- Test Speed
- BN-absorber-enet
- Do you train the model on CamVid Dataset? HOT 1
- No Module named caffe HOT 1
- Why do I get wrong predictions when I train the coding and decoding network directly?That is I havn't train encoder network in advance。
- Bad test
- why i can download your cityscapes_weights
- why i can download your cityscapes_weights
- object segmentation
- use ENet to train Pascal_voc, and the result wasn't convergency. HOT 4
- transfer learning HOT 1
- Your example ENet prediction looks wrong
- TypeError HOT 1
- Question about the params and FLOPs of ENet
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