logsumexp handling of edge-cases

[rasmushaugaard]

Hi! First of all thanks for this library, which has been useful in a few projects.

I've run into some inconsistencies between the torch_scatter.logsumexp and torch.logsumexp:

1. logsumexp of no elements should default to -inf, not 0.
   This is equivalent to having sum(..., start=0) in non-log space.
   torch.logsumexp(torch.tensor([]), dim=0) returns -inf.
2. it should not hide nans:
   torch.logsumexp(torch.tensor([torch.nan]), dim=0) returns nan.
3. no eps should be added. torch.logsumexp also doesn't have this.

In the first commit, I've added test cases for empty lists, -inf, inf, very large positive and negative numbers - and added a cartesian product test across the inputs and the various floating point data types.

In the second commit, I've changed the implementation to comply with the new tests.

Dependency Management

On another note, I ended up spending a few hours setting up the torch/cuda dependencies correctly to build from source.
I ended up using the following commands to install deps, build from source and run the tests:

cd pytorch_scatter
conda create -n torchscatter python=3.10 pytorch::pytorch pytorch::pytorch-cuda=11.8 nvidia/label/cuda-11.8.0::cuda
conda activate torchscatter
pip install -e ".[test]"
pytest

Maybe having this or something similar in the docs (if it's not already there and I missed it) could make it easier for others to contribute.

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All modified and coverable lines are covered by tests ✅

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@@            Coverage Diff             @@
##           master     #426      +/-   ##
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+ Coverage   97.23%   98.20%   +0.97%     
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  Files          10       10              
  Lines         217      223       +6     
==========================================
+ Hits          211      219       +8     
+ Misses          6        4       -2     

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[rasmushaugaard]

I just had a look at the history, and it seems an issue #368 motivated a change of how nans and infs were treated in #369 and introduced a new issue #407 - which is also the issue that motivated this pull request, which should solve both.

I've added tests and improved numerical stability for the inplace version.

[github-actions]

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

[rasmushaugaard]

Hi @rusty1s, Is there something I can do to help with this? :)