pytorch_cluster

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This commit implements weighted biased random walks as in the original Node2vec paper. In particular, it adds a new parameter to the random_walk function, i.e., edge_weight, which allows passing edge weights to the underlying random walk generation procedure. If edge weights are set, the function normalizes them by the node degree and converts the weights into CDFs over given nodes (needed by the rejection sampling method). The implementation of the new rejection sampling method is based on [1].

[1] https://github.com/louisabraham/fastnode2vec/blob/master/fastnode2vec/graph.py#L69

• Update random_walk API
• Implement weighted rejection sampling on CPU
• Implement weighted random walk for GPU (CUDA)
• Compute CDFs using C++/CUDA
• Add tests for weighted random walks

Aug 10 '22 15:08 pbielak

Codecov Report

All modified and coverable lines are covered by tests :white_check_mark:

Project coverage is 98.63%. Comparing base (cc4696b) to head (2b63087). Report is 22 commits behind head on master.

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@@             Coverage Diff             @@
##            master     #140      +/-   ##
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- Coverage   100.00%   98.63%   -1.37%     
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  Files            9       11       +2     
  Lines           77      146      +69     
===========================================
+ Hits            77      144      +67     
- Misses           0        2       +2     

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Aug 10 '22 15:08 codecov-commenter

Thank you @pbielak, will have a look ASAP.

Aug 11 '22 09:08 rusty1s

Hi, I am highly interested in this pull request :), is there any way this could be merged? Thanks :)

Feb 15 '23 20:02 Alvaro-Ciudad

This pull request had no activity for 6 months. It will be closed in 2 weeks unless there is some new activity.

Aug 15 '23 00:08 github-actions[bot]

Hello, is there any chance, this will be implemented?

Oct 11 '23 21:10 AmosDinh

This pull request had no activity for 6 months. It will be closed in 2 weeks unless there is some new activity.

Apr 09 '24 00:04 github-actions[bot]