Remove NDTensors as test dep

Author: mtfishman

TODO.md

@@ -1,4 +1,3 @@
 [deps]
 BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
-NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

ext/BlockSparseArraysGradedUnitRangesExt/test/Project.toml

@@ -1,4 +1,3 @@
 [deps]
 BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
-NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

ext/BlockSparseArraysTensorAlgebraExt/test/Project.toml

@@ -1,10 +1,6 @@
 using BlockArrays:
   BlockArrays, AbstractBlockArray, Block, BlockIndex, BlockedUnitRange, blocks
 
-# TODO: Delete this. This function was replaced
-# by `stored_length` but is still used in `NDTensors`.
-function nonzero_keys end
-
 abstract type AbstractBlockSparseArray{T,N} <: AbstractBlockArray{T,N} end
 
 ## Base `AbstractArray` interface

src/abstractblocksparsearray/abstractblocksparsearray.jl

@@ -1,4 +1,5 @@
 [deps]
+Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
 Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 ArrayLayouts = "4c555306-a7a7-4459-81d9-ec55ddd5c99a"
 BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
@@ -10,7 +11,6 @@ GradedUnitRanges = "e2de450a-8a67-46c7-b59c-01d5a3d041c5"
 JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
 LabelledNumbers = "f856a3a6-4152-4ec4-b2a7-02c1a55d7993"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-NDTensors = "23ae76d9-e61a-49c4-8f12-3f1a16adf9cf"
 NestedPermutedDimsArrays = "2c2a8ec4-3cfc-4276-aa3e-1307b4294e58"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

test/Project.toml

@@ -1,3 +1,4 @@
+using Adapt: adapt
 using ArrayLayouts: zero!
 using BlockArrays:
   Block,
@@ -28,22 +29,18 @@ using BlockSparseArrays:
   blocktype,
   view!
 using GPUArraysCore: @allowscalar
+using JLArrays: JLArray
 using LinearAlgebra: Adjoint, Transpose, dot, mul!, norm
-using NDTensors.GPUArraysCoreExtensions: cpu
 using SparseArraysBase: SparseArrayDOK, SparseMatrixDOK, SparseVectorDOK, storedlength
 using TensorAlgebra: contract
 using Test: @test, @test_broken, @test_throws, @testset, @inferred
 include("TestBlockSparseArraysUtils.jl")
 
-using NDTensors: NDTensors
-include(joinpath(pkgdir(NDTensors), "test", "NDTensorsTestUtils", "NDTensorsTestUtils.jl"))
-using .NDTensorsTestUtils: devices_list, is_supported_eltype
-@testset "BlockSparseArrays (dev=$dev, eltype=$elt)" for dev in devices_list(copy(ARGS)),
+arrayts = (Array, JLArray)
+@testset "BlockSparseArrays (arraytype=$arrayt, eltype=$elt)" for arrayt in arrayts,
   elt in (Float32, Float64, Complex{Float32}, Complex{Float64})
 
-  if !is_supported_eltype(dev, elt)
-    continue
-  end
+  dev(a) = adapt(arrayt, a)
   @testset "Broken" begin
     # TODO: Fix this and turn it into a proper test.
     a = dev(BlockSparseArray{elt}([2, 3], [2, 3]))
@@ -268,7 +265,7 @@ using .NDTensorsTestUtils: devices_list, is_supported_eltype
     @test storedlength(a) == 2 * 4 + 3 * 3
 
     # TODO: Broken on GPU.
-    if dev ≠ cpu
+    if arrayt ≠ Array
       a = dev(BlockSparseArray{elt}([2, 3], [3, 4]))
       @test_broken a[Block(1, 2)] .= 2
     end
@@ -285,7 +282,7 @@ using .NDTensorsTestUtils: devices_list, is_supported_eltype
     @test storedlength(a) == 2 * 4
 
     # TODO: Broken on GPU.
-    if dev ≠ cpu
+    if arrayt ≠ Array
       a = dev(BlockSparseArray{elt}([2, 3], [3, 4]))
       @test_broken a[Block(1, 2)] .= 0
     end
@@ -321,15 +318,15 @@ using .NDTensorsTestUtils: devices_list, is_supported_eltype
     @test iszero(b)
     @test iszero(storedlength(b))
     # TODO: Broken on GPU.
-    @test iszero(c) broken = dev ≠ cpu
+    @test iszero(c) broken = arrayt ≠ Array
     @test iszero(storedlength(c))
     @allowscalar a[5, 7] = 1
     @test !iszero(a)
     @test storedlength(a) == 3 * 4
     @test !iszero(b)
     @test storedlength(b) == 3 * 4
     # TODO: Broken on GPU.
-    @test !iszero(c) broken = dev ≠ cpu
+    @test !iszero(c) broken = arrayt ≠ Array
     @test storedlength(c) == 3 * 4
     d = @view a[1:4, 1:6]
     @test iszero(d)