pytorch_sparse
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New feature: weighted neighborhood sampling (sample by value)
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.
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.
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?
Feel free to send a PR with the applied changes. Other-wise, I will find some time to implement it by myself.