move mldatasets2gnngraph

GNNGraphs/src/GNNGraphs.jl

@@ -108,4 +108,7 @@ export sort_edge_index, color_refinement
 include("gatherscatter.jl")
 # _gather, _scatter
 
+include("mldatasets.jl")
+export mldataset2gnngraph
+
 end #module

GNNGraphs/test/runtests.jl

@@ -36,6 +36,7 @@ tests = [
     "sampling",
     "gnnheterograph",
     "temporalsnapshotsgnngraph",
+    "mldatasets",
     "ext/SimpleWeightedGraphs"
 ]
 

GNNlib/Project.toml

@@ -1,21 +1,17 @@
 name = "GNNlib"
 uuid = "a6a84749-d869-43f8-aacc-be26a1996e48"
 authors = ["Carlo Lucibello and contributors"]
-version = "0.1.0"
+version = "0.2.0-DEV"
 
 [deps]
-Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
-Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
+GNNGraphs = "aed8fd31-079b-4b5a-b342-a13352159b8c"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
-KrylovKit = "0b1a1467-8014-51b9-945f-bf0ae24f4b77"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
 NNlib = "872c559c-99b0-510c-b3b7-b6c96a88d5cd"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
-SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [weakdeps]
@@ -25,36 +21,19 @@ CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
 GNNlibCUDAExt = "CUDA"
 
 [compat]
-Adapt = "3, 4"
+ChainRulesCore = "1.24"
 CUDA = "4, 5"
-ChainRulesCore = "1"
 DataStructures = "0.18"
-Functors = "0.4.1"
-Graphs = "1.4"
-KrylovKit = "0.6, 0.7"
+GNNGraphs = "1.0"
 LinearAlgebra = "1"
-MLDatasets = "0.7"
 MLUtils = "0.4"
 NNlib = "0.9"
 Random = "1"
-Reexport = "1"
-SparseArrays = "1"
 Statistics = "1"
-cuDNN = "1"
 julia = "1.10"
 
 [extras]
-Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
-CUDA = "052768ef-5323-5732-b1bb-66c8b64840ba"
-ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"
-DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
-InlineStrings = "842dd82b-1e85-43dc-bf29-5d0ee9dffc48"
-MLDatasets = "eb30cadb-4394-5ae3-aed4-317e484a6458"
-SimpleWeightedGraphs = "47aef6b3-ad0c-573a-a1e2-d07658019622"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
-cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [targets]
-test = ["Test", "Adapt", "DataFrames", "InlineStrings", "SimpleWeightedGraphs", "Zygote", "FiniteDifferences", "ChainRulesTestUtils", "MLDatasets", "CUDA", "cuDNN"]
+test = ["Test"]

GNNlib/src/GNNlib.jl

@@ -2,13 +2,11 @@ module GNNlib
 
 using Statistics: mean
 using LinearAlgebra, Random
-using MLUtils
+using MLUtils: zeros_like
 using NNlib
 using NNlib: scatter, gather
-using ChainRulesCore
-using SparseArrays, Graphs # not needed but if removed Documenter will complain
 using DataStructures: nlargest
-using Reexport: @reexport
+using ChainRulesCore: @non_differentiable
 using GNNGraphs
 using .GNNGraphs: COO_T, ADJMAT_T, SPARSE_T,
                   check_num_nodes, check_num_edges,
@@ -33,9 +31,7 @@ export
       xi_sub_xj,
       xj_sub_xi,
       e_mul_xj,
-      w_mul_xj,
-      # mldatasets
-      mldataset2gnngraph
+      w_mul_xj
 
 ## The following methods are defined but not exported
 
@@ -80,7 +76,6 @@ include("layers/conv.jl")
 include("layers/temporalconv.jl")
 include("layers/pool.jl")
 include("msgpass.jl")
-include("mldatasets.jl")
 
 end #module
 

GNNlib/src/layers/conv.jl

@@ -199,7 +199,7 @@ function gatv2_message(l, Wxi, Wxj, e)
 end
 
 
-# TODO remove after https://github.com/JuliaDiff/ChainRules.jl/pull/521
+# TODO PIRACY! remove after https://github.com/JuliaDiff/ChainRules.jl/pull/521
 @non_differentiable fill!(x...)
 
 function gated_graph_conv(l, g::GNNGraph, H::AbstractMatrix{S}) where {S <: Real}

Project.toml

@@ -55,4 +55,4 @@ Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
 cuDNN = "02a925ec-e4fe-4b08-9a7e-0d78e3d38ccd"
 
 [targets]
-test = ["Test", "Adapt", "DataFrames", "InlineStrings", "SparseArrays", "Graphs", "Zygote", "FiniteDifferences", "ChainRulesTestUtils", "MLDatasets", "CUDA", "cuDNN"]
+test = ["Test", "MLDatasets", "Adapt", "DataFrames", "InlineStrings", "SparseArrays", "Graphs", "Zygote", "FiniteDifferences", "ChainRulesTestUtils", "CUDA", "cuDNN"]

docs/src/dev.md

@@ -1,7 +1,8 @@
 # Developer Notes
 
-## Develop Monorepo
+## Develop and Managing the Monorepo
 
+### Development
 GraphNeuralNetworks.jl is package hosted in a monorepo that contains multiple packages. 
 The GraphNeuralNetworks.jl package depends on GNNGraphs.jl, also hosted in the same monorepo.
 
@@ -11,8 +12,12 @@ pkg> activate .
 pkg> dev ./GNNGraphs
 ```
 
+### Versions and Tagging
+Each PR should update the version number in the Porject.toml file of each involved package if needed by semnatic versioning. For instance, when adding new features GNNGraphs could move from "1.17.5" to "1.18.0-DEV". The "DEV" will be removed when the package is tagged and released. Pay also attention to updating
+the compat bounds, e.g. GraphNeuralNetworks might require a newer version of GNNGraphs.
 
-For generating the documentation locally instead
+### Generate Documentation Locally
+For generating the documentation locally
 ```
 cd docs
 julia

src/GraphNeuralNetworks.jl

@@ -93,7 +93,6 @@ include("layers/heteroconv.jl")
 include("layers/temporalconv.jl")
 include("layers/pool.jl")
 include("msgpass.jl")
-include("mldatasets.jl")
 include("deprecations.jl")
 
 end

test/runtests.jl

@@ -31,7 +31,6 @@ tests = [
     "layers/heteroconv",
     "layers/temporalconv",
     "layers/pool",
-    "mldatasets",
     "examples/node_classification_cora",
 ]