Comments (2)
Hello! Thanks for your interest, this code was tested more than 1 year ago with PyTorch 0.4 and CUDA 9.0. If you are running it today, you may have to match the CUDA version or make edits to the code.
Alternatively, you may use my new codebase to train similar Non-autoregressive TSP models + you can now train on variable graph sizes instead of fixed: https://github.com/chaitjo/learning-tsp
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I have seen the same error with Ubuntu 16.04, RTX 2080 Ti.
Seems that it can be solved by changing to CUDA 9.2.
conda remove cudnn cudatoolkit pytorch
conda install pytorch=0.4.1 cuda92 -c pytorch
See https://discuss.pytorch.org/t/runtimeerror-cudnn-error-cudnn-status-success/28045/5
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Related Issues (12)
- Train for 500 nodes HOT 2
- Error in beamsearch.py HOT 6
- Node and edge feature aggreation w.r.t connectivity HOT 2
- a question about data format in google_tsp_reader HOT 1
- A code issue HOT 6
- There is an error in backward pass step as the values are not contigous HOT 8
- RuntimeError when executing "test backward pass" block in main.ipynb HOT 7
- Question: Testing the model on TSPLIB example HOT 1
- RuntimeError: grad_input must be contiguous HOT 1
- I can not install concorde solver on my system. HOT 1
- runerror HOT 5
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