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New feature: weighted neighborhood sampling (sample by value) #152

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deepakagrawal opened this issue Jul 11, 2021 · 3 comments
Open

New feature: weighted neighborhood sampling (sample by value) #152

deepakagrawal opened this issue Jul 11, 2021 · 3 comments
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enhancement New feature or request

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@deepakagrawal
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deepakagrawal commented Jul 11, 2021 •
edited

I have a SparseTensor with value, how can extend sample method or some other function where the neighborhood sampling probability is based on the value of the SparseTensor.
@rusty1s
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rusty1s commented Jul 12, 2021

This is sadly not supported yet. I think this needs its own condition here, where we want to perform weighted neighborhood sampling rather than uniform sampling.

@deepakagrawal
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This is sadly not supported yet. I think this needs its own condition here, where we want to perform weighted neighborhood sampling rather than uniform sampling.

How can I create a feature request for this?

@deepakagrawal deepakagrawal changed the title New features: sample by value New feature: sample by value Jul 12, 2021
@deepakagrawal deepakagrawal changed the title New feature: sample by value New feature: weighted neighborhood sampling (sample by value) Jul 12, 2021
@rusty1s
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rusty1s commented Sep 16, 2021

Feel free to send a PR with the applied changes. Other-wise, I will find some time to implement it by myself.

@rusty1s rusty1s added the enhancement New feature or request label Sep 16, 2021
RexYing added a commit to RexYing/pytorch_sparse that referenced this issue Apr 26, 2022
@RexYing @rusty1s
Test performance evaluation and early stopping (rusty1s#152)
cd917a7 
early stopping, ckpt, test set

Co-authored-by: rusty1s <matthias.fey@tu-dortmund.de>
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@deepakagrawal @rusty1s