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Update README to Pytorch v1.10
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README.md

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@@ -38,7 +38,7 @@ pip install tensorboardx==1.5 fastprogress==0.1.18
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# conda install -c conda-forge cupy cudatoolkit=10.2 -y
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pip install cupy-cuda102
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# Also some efficient sparse operations using https://github.com/rusty1s/pytorch_scatter
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pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.8.0+cu102.html
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pip install torch-scatter -f https://pytorch-geometric.com/whl/torch-1.10.0+cu102.html
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```
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## Generate instances (or download)
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![pipeline](res/vrp.png)
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## Acknowledgements
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This repository was built upon the excellent repository [graph-convnet-tsp](https://github.com/chaitjo/graph-convnet-tsp) by Chaitanya K. Joshi and my own repository [attention-learn-to-route](https://github.com/wouterkool/attention-learn-to-route). The TSPTW GVNS code is from the repository [TSPTW](https://github.com/sashakh/TSPTW), adapted from [the original code](http://homepages.dcc.ufmg.br/~rfsilva/tsptw/) of da Silva et al. We thank Quentin Cappart for kindly providing TSPTW instances and results.
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This repository was built upon the excellent repository [graph-convnet-tsp](https://github.com/chaitjo/graph-convnet-tsp) by Chaitanya K. Joshi and my own repository [attention-learn-to-route](https://github.com/wouterkool/attention-learn-to-route). The TSPTW GVNS code is from the repository [TSPTW](https://github.com/sashakh/TSPTW), adapted from [the original code](http://homepages.dcc.ufmg.br/~rfsilva/tsptw/) of da Silva et al. We thank Quentin Cappart for kindly providing TSPTW instances and results.

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