conver more tests

Author: CarloLucibello

GNNGraphs/Project.toml

@@ -4,7 +4,6 @@ authors = ["Carlo Lucibello and contributors"]
 version = "1.4.1"
 
 [deps]
-Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
@@ -28,15 +27,13 @@ GNNGraphsCUDAExt = "CUDA"
 GNNGraphsSimpleWeightedGraphsExt = "SimpleWeightedGraphs"
 
 [compat]
-Adapt = "4"
 CUDA = "5"
 ChainRulesCore = "1"
 Functors = "0.5"
 Graphs = "1.4"
 KrylovKit = "0.8"
 LinearAlgebra = "1"
 MLDataDevices = "1.0"
-MLDatasets = "0.7"
 MLUtils = "0.4"
 NNlib = "0.9"
 NearestNeighbors = "0.4"
@@ -45,21 +42,4 @@ SimpleWeightedGraphs = "1.4.0"
 SparseArrays = "1"
 Statistics = "1"
 StatsBase = "0.34"
-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"]

GNNGraphs/test/Project.toml

@@ -1,11 +1,21 @@
 [deps]
 FiniteDifferences = "26cc04aa-876d-5657-8c51-4c34ba976000"
+Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
 GNNGraphs = "aed8fd31-079b-4b5a-b342-a13352159b8c"
+GPUArraysCore = "46192b85-c4d5-4398-a991-12ede77f4527"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MLDataDevices = "7e8f7934-dd98-4c1a-8fe8-92b47a384d40"
 MLUtils = "f1d291b0-491e-4a28-83b9-f70985020b54"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
+SimpleWeightedGraphs = "47aef6b3-ad0c-573a-a1e2-d07658019622"
+SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 TestItems = "1c621080-faea-4a02-84b6-bbd5e436b8fe"
+Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
+
+[compat]
+GPUArraysCore = "0.1"

GNNGraphs/test/chainrules.jl

@@ -1,24 +1,23 @@
-@testset "dict constructor" begin
+@testitem "dict constructor" setup=[GraphsTestModule] begin
+    using .GraphsTestModule
     grad = gradient(1.) do x
         d = Dict([:x => x, :y => 5]...)    
         return sum(d[:x].^2)
     end[1]
 
     @test grad == 2
 
-    ## BROKEN Constructors
-    # grad = gradient(1.) do x
-    #     d = Dict([(:x => x), (:y => 5)])    
-    #     return sum(d[:x].^2)
-    # end[1]
-
-    # @test grad == 2
+    grad = gradient(1.) do x
+        d = Dict([:x => x, :y => 5])    
+        return sum(d[:x].^2)
+    end[1]
 
+    @test grad == 2
 
-    # grad = gradient(1.) do x
-    #     d = Dict([(:x => x), (:y => 5)])    
-    #     return sum(d[:x].^2)
-    # end[1]
+    grad = gradient(1.) do x
+        d = Dict(:x => x, :y => 5)    
+        return sum(d[:x].^2)
+    end[1]
 
-    # @test grad == 2
+    @test grad == 2
 end

GNNGraphs/test/convert.jl

@@ -1,20 +1,24 @@
-if TEST_GPU
-    @testset "to_coo(dense) on gpu" begin
-        get_st(A) = GNNGraphs.to_coo(A)[1][1:2]
-        get_val(A) = GNNGraphs.to_coo(A)[1][3]
+@testitem "to_coo(dense) on gpu" setup=[GraphsTestModule] tags=[:gpu] begin
+    using .GraphsTestModule
+    get_st(A) = GNNGraphs.to_coo(A)[1][1:2]
+    get_val(A) = GNNGraphs.to_coo(A)[1][3]
+    gpu = gpu_device(force=true)
+    A = gpu([0 2 2; 2.0 0 2; 2 2 0])
 
-        A = cu([0 2 2; 2.0 0 2; 2 2 0])
+    y = get_val(A)
+    @test y isa AbstractVector{Float32}
+    @test get_device(y) == get_device(A)
+    @test Array(y) ≈ [2, 2, 2, 2, 2, 2]
 
-        y = get_val(A)
-        @test y isa CuVector{Float32}
-        @test Array(y) ≈ [2, 2, 2, 2, 2, 2]
+    s, t = get_st(A)
+    @test s isa AbstractVector{<:Integer}
+    @test t isa AbstractVector{<:Integer}
+    @test get_device(s) == get_device(A)
+    @test get_device(t) == get_device(A)
+    @test Array(s) == [2, 3, 1, 3, 1, 2]
+    @test Array(t) == [1, 1, 2, 2, 3, 3]
 
-        s, t = get_st(A)
-        @test s isa CuVector{<:Integer}
-        @test t isa CuVector{<:Integer}
-        @test Array(s) == [2, 3, 1, 3, 1, 2]
-        @test Array(t) == [1, 1, 2, 2, 3, 3]
-
-        @test gradient(A -> sum(get_val(A)), A)[1] isa CuMatrix{Float32}
-    end
+    grad = gradient(A -> sum(get_val(A)), A)[1] 
+    @test grad isa AbstractMatrix{Float32}
+    @test get_device(grad) == get_device(A)
 end

GNNGraphs/test/datastore.jl

@@ -1,5 +1,5 @@
 
-@testset "constructor" begin
+@testitem "constructor" begin
     @test_throws AssertionError DataStore(10, (:x => rand(10), :y => rand(2, 4)))
 
     @testset "keyword args" begin
@@ -13,7 +13,7 @@
     end
 end
 
-@testset "getproperty / setproperty!" begin
+@testitem "getproperty / setproperty!" begin
     x = rand(10)
     ds = DataStore(10, (:x => x, :y => rand(2, 10)))
     @test ds.x == ds[:x] == x
@@ -25,14 +25,14 @@ end
     @test fill(DataStore(), 3) isa Vector
 end
 
-@testset "setindex!" begin
+@testitem "setindex!" begin
     ds = DataStore(10)
     x = rand(10)
     @test (ds[:x] = x) == x # Tests setindex!
     @test ds.x == ds[:x] == x
 end
 
-@testset "map" begin
+@testitem "map" begin
     ds = DataStore(10, (:x => rand(10), :y => rand(2, 10)))
     ds2 = map(x -> x .+ 1, ds)
     @test ds2.x == ds.x .+ 1
@@ -41,33 +41,34 @@ end
     @test_throws AssertionError ds2=map(x -> [x; x], ds)
 end
 
-@testset "getdata / getn" begin
+@testitem "getdata / getn" begin
     ds = DataStore(10, (:x => rand(10), :y => rand(2, 10)))
-    @test getdata(ds) == getfield(ds, :_data)
+    @test GNNGraphs.getdata(ds) == getfield(ds, :_data)
     @test_throws KeyError ds.data
-    @test getn(ds) == getfield(ds, :_n)
+    @test GNNGraphs.getn(ds) == getfield(ds, :_n)
     @test_throws KeyError ds.n
 end
 
-@testset "cat empty" begin
+@testitem "cat empty" begin
     ds1 = DataStore(2, (:x => rand(2)))
     ds2 = DataStore(1, (:x => rand(1)))
     dsempty = DataStore(0, (:x => rand(0)))
 
     ds = GNNGraphs.cat_features(ds1, ds2)
-    @test getn(ds) == 3
+    @test GNNGraphs.getn(ds) == 3
     ds = GNNGraphs.cat_features(ds1, dsempty)
-    @test getn(ds) == 2
+    @test GNNGraphs.getn(ds) == 2
 
     # issue #280
     g = GNNGraph([1], [2])
     h = add_edges(g, Int[], Int[])  # adds no edges
-    @test getn(g.edata) == 1
-    @test getn(h.edata) == 1
+    @test GNNGraphs.getn(g.edata) == 1
+    @test GNNGraphs.getn(h.edata) == 1
 end
 
 
-@testset "gradient" begin
+@testitem "gradient"  setup=[GraphsTestModule] begin
+    using .GraphsTestModule
     ds = DataStore(10, (:x => rand(10), :y => rand(2, 10)))
 
     f1(ds) = sum(ds.x)
@@ -80,11 +81,12 @@ end
     @test grad == exp.(x)
 end
 
-@testset "functor" begin
+@testitem "functor" begin
+    using Functors
     ds = DataStore(10, (:x => zeros(10), :y => ones(2, 10)))
     p, re = Functors.functor(ds)
-    @test p[1] === getn(ds)
-    @test p[2] === getdata(ds)
+    @test p[1] === GNNGraphs.getn(ds)
+    @test p[2] === GNNGraphs.getdata(ds)
     @test ds == re(p)
 
     ds2 = Functors.fmap(ds) do x

GNNGraphs/test/ext/SimpleWeightedGraphs.jl

@@ -1,4 +1,5 @@
-@testset "simple_weighted_graph" begin
+@testitem "simple_weighted_graph" begin
+    using SimpleWeightedGraphs
     srcs = [1, 2, 1]
     dsts = [2, 3, 3]
     wts = [0.5, 0.8, 2.0]