JuliaGraphs / JuliaGraphs/GraphNeuralNetworks.jl
relax graph type restriction on layer inputs
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- Dominant language
- Julia
- Stars
- 308
- Forks
- 74
- Avg merge
- 3d 6h
- Merged PRs (30d)
- 2
Description
We can relax the g::GNNGraph restriction to g::AbstractGraph or remove it entirely to allow people to use the convolutional layers on their custom graphs if they want to
Related to the discussion in https://github.com/Chemellia/AtomicGraphNets.jl/issues/66
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the convolutional layer definitions and the g::GNNGraph input restriction. Compare the implications of accepting g::AbstractGraph or removing the restriction, then verify that convolutional layers work with custom graphs as described; the related discussion in AtomicGraphNets.jl issue 66 provides context.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100