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docs/make.jl

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using Flux, NNlib, GraphNeuralNetworks, Graphs, SparseArrays
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using GraphNeuralNetworks
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using GNNGraphs
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using Flux
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using NNlib
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using Graphs
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using SparseArrays
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using Pluto, PlutoStaticHTML # for tutorials
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using Documenter, DemoCards
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using DocumenterInterLinks

docs/src/api/gnngraph.md

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```@meta
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CurrentModule = GraphNeuralNetworks
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CurrentModule = GNNGraphs
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```
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# GNNGraph
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```
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```@docs
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Graphs.neighbors
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Graphs.has_edge
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Graphs.neighbors(::GNNGraph, ::Integer)
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```
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## Transform
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```
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```@docs
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Graphs.intersect
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Base.intersect
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```
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## Sampling

docs/src/api/heterograph.md

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Private = false
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```
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```@docs
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Graphs.has_edge(::GNNHeteroGraph, ::Tuple{Symbol, Symbol, Symbol}, ::Integer, ::Integer)
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```
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## Heterogeneous Graph Convolutions
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Heterogeneous graph convolutions are implemented in the type [`HeteroGraphConv`](@ref).

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