revisit FeaturedGraph implementation

Project.toml

@@ -5,39 +5,38 @@ version = "0.7.6"
 
 [deps]
 CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
+ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 FillArrays = "1a297f60-69ca-5386-bcde-b61e274b549b"
 Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
-GraphLaplacians = "a1251efa-393a-423f-9d7b-faaecba535dc"
 GraphMLDatasets = "21828b05-d3b3-40ad-870e-a4bc2f52d5e8"
-GraphSignals = "3ebe565e-a4b5-49c6-aed2-300248c3a9c1"
+KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 LightGraphs = "093fc24a-ae57-5d10-9952-331d41423f4d"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 NNlibCUDA = "a00861dc-f156-4864-bf3c-e6376f28a68d"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [compat]
 CUDA = "3.3"
 DataStructures = "0.18"
 FillArrays = "0.11, 0.12"
 Flux = "0.12"
-GraphLaplacians = "0.1"
 GraphMLDatasets = "0.1"
-GraphSignals = "0.2"
+KrylovKit = "0.5"
 LightGraphs = "1.3"
 NNlib = "0.7"
 NNlibCUDA = "0.1"
 Reexport = "1.1"
-Zygote = "0.6"
 julia = "1.6"
 
 [extras]
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 
 [targets]
-test = ["SparseArrays", "Test"]
+test = ["SparseArrays", "Test", "Zygote"]

docs/make.jl

@@ -19,10 +19,12 @@ makedocs(
                ["Message passing scheme" => "abstractions/msgpass.md",
                 "Graph network block" => "abstractions/gn.md"],
              "Manual" =>
-               ["Convolutional Layers" => "manual/conv.md",
+               [
+                "Graphs" => "manual/featuredgraph.md",
+                "Convolutional Layers" => "manual/conv.md",
                 "Pooling Layers" => "manual/pool.md",
                 "Models" => "manual/models.md",
-                "Linear Algebra" => "manual/linalg.md"]
+               ]
     ]
 )
 

docs/src/manual/featuredgraph.md

@@ -0,0 +1,20 @@
+# Graphs
+
+GeometricFlux relies on the [`FeaturedGraph`](@ref)
+type to represent graph structures and feature arrays associated to
+nodes and edges.
+
+
+```@docs
+GeometrixFlux.FeaturedGraph
+GeometrixFlux.edge_index
+GeometrixFlux.graph
+GeometrixFlux.adjacency_list
+GeometrixFlux.adjacency_matrix
+GeometrixFlux.add_self_loops
+GeometrixFlux.remove_self_loops
+GeometrixFlux.degree
+GeometrixFlux.laplacian_matrix
+GeometrixFlux.normalized_laplacian
+GeometrixFlux.scaled_laplacian
+```

docs/src/manual/linalg.md

@@ -1,22 +0,0 @@
-# Linear Algebra
-
-
-```@docs
-GraphSignals.degrees
-```
-
-```@docs
-GraphSignals.degree_matrix
-```
-
-```@docs
-GraphSignals.inv_sqrt_degree_matrix
-```
-
-```@docs
-GraphSignals.laplacian_matrix
-```
-
-```@docs
-GraphSignals.normalized_laplacian
-```

src/GeometricFlux.jl

@@ -1,20 +1,32 @@
 module GeometricFlux
 
+using NNlib: similar
+using LinearAlgebra: similar, fill!
 using Statistics: mean
-using LinearAlgebra: Adjoint, norm, Transpose
-using Reexport
-
+using LinearAlgebra
+using SparseArrays
+import KrylovKit
 using CUDA
 using FillArrays: Fill
 using Flux
 using Flux: glorot_uniform, leakyrelu, GRUCell, @functor
 using NNlib, NNlibCUDA
-using GraphLaplacians
-@reexport using GraphSignals
-using LightGraphs
-using Zygote
+using ChainRulesCore
+import LightGraphs
+using LightGraphs: AbstractGraph, outneighbors, inneighbors, is_directed, ne, nv, 
+                  adjacency_matrix, degree
 
 export
+    # featured_graph
+    FeaturedGraph,
+    graph, edge_index,
+    node_feature, edge_feature, global_feature,
+    adjacency_list, normalized_laplacian, scaled_laplacian,
+    add_self_loops,
+
+    # from LightGraphs
+    adjacency_matrix, 
+
     # layers/gn
     GraphNet,
 
@@ -50,8 +62,10 @@ export
     # utils
     generate_cluster
 
+
+include("featuredgraph.jl")
+include("graph_conversions.jl")
 include("datasets.jl")
-
 include("utils.jl")
 
 include("layers/gn.jl")