Missing sparse array methods for `CuSparseMatrixCOO`
bug
**Describe the bug**
Some methods of [`GPUArrays`](https://github.com/JuliaGPU/GPUArrays.jl?tab=readme-ov-file#sparse-array-support-optional) related to sparse arrays are missing for `CuSparseMatrixCOO`, whereas they exist for `CuSparseMatrixCSC` and `CuSparseMatrixCSR`.
**To reproduce**
The Minimal Working Example (MWE) for this bug:
```julia
using CUDA, CUDA.CUSPARSE
using GPUArrays
using SparseArrays
GPUArrays.sparse_array_type(CuSparseMatrixCSC(spzeros(1, 1))) == CuSparseMatrixCSC # true, correct behavior
GPUArrays.sparse_array_type(CuSparseMatrixCOO(spzeros(1, 1))) == CuSparseMatrixCOO # false, missing implem
```
<details><summary>Manifest.toml</summary>
<p>
```
Status `~/.julia/environments/v1.11/Manifest.toml`
[47edcb42] ADTypes v1.21.0
[621f4979] AbstractFFTs v1.5.0
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⌃ [79e6a3ab] Adapt v4.4.0
[35492f91] AdaptivePredicates v1.2.0
[66dad0bd] AliasTables v1.1.3
[27a7e980] Animations v0.4.2
⌃ [4fba245c] ArrayInterface v7.22.0
[a9b6321e] Atomix v1.1.2
[67c07d97] Automa v1.1.0
[13072b0f] AxisAlgorithms v1.1.0
[39de3d68] AxisArrays v0.4.8
[ab4f0b2a] BFloat16s v0.6.1
[18cc8868] BaseDirs v1.3.2
[d1d4a3ce] BitFlags v0.1.9
[e1450e63] BufferedStreams v1.2.2
[fa961155] CEnum v0.5.0
[2a0fbf3d] CPUSummary v0.2.7
[96374032] CRlibm v1.0.2
⌃ [336ed68f] CSV v0.10.15
⌃ [052768ef] CUDA v5.9.6
[1af6417a] CUDA_Runtime_Discovery v1.0.0
[d360d2e6] ChainRulesCore v1.26.0
[944b1d66] CodecZlib v0.7.8
[a2cac450] ColorBrewer v0.4.2
[35d6a980] ColorSchemes v3.31.0
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[c3611d14] ColorVectorSpace v0.11.0
[5ae59095] Colors v0.13.1
[bbf7d656] CommonSubexpressions v0.3.1
[f70d9fcc] CommonWorldInvalidations v1.0.0
[34da2185] Compat v4.18.1
⌃ [95dc2771] ComputePipeline v0.1.6
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⌃ [f0e56b4a] ConcurrentUtilities v2.5.0
[8f4d0f93] Conda v1.10.3
[187b0558] ConstructionBase v1.6.0
[d38c429a] Contour v0.6.3
[adafc99b] CpuId v0.3.1
[a8cc5b0e] Crayons v4.1.1
[9a962f9c] DataAPI v1.16.0
[a93c6f00] DataFrames v1.8.1
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[ffbed154] DocStringExtensions v0.9.5
⌃ [4e289a0a] EnumX v1.0.6
⌃ [7da242da] Enzyme v0.13.129
[f151be2c] EnzymeCore v0.8.18
[429591f6] ExactPredicates v2.2.9
[460bff9d] ExceptionUnwrapping v0.1.11
[e2ba6199] ExprTools v0.1.10
⌃ [21656369] ExpressionExplorer v1.1.3
[411431e0] Extents v0.1.6
[c87230d0] FFMPEG v0.4.5
[b86e33f2] FFTA v0.3.1
[9aa1b823] FastClosures v0.3.2
[5789e2e9] FileIO v1.18.0
[8fc22ac5] FilePaths v0.9.0
[48062228] FilePathsBase v0.9.24
[1a297f60] FillArrays v1.16.0
[53c48c17] FixedPointNumbers v0.8.5
[1fa38f19] Format v1.3.7
[f6369f11] ForwardDiff v1.3.2
[b38be410] FreeType v4.1.1
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[0c68f7d7] GPUArrays v11.4.1
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[61eb1bfa] GPUCompiler v1.8.2
[096a3bc2] GPUToolbox v1.0.0
⌃ [28b8d3ca] GR v0.73.22
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[3955a311] GridLayoutBase v0.11.2
[42e2da0e] Grisu v1.0.2
⌃ [cd3eb016] HTTP v1.10.19
[076d061b] HashArrayMappedTries v0.2.0
[34004b35] HypergeometricFunctions v0.3.28
⌃ [7073ff75] IJulia v1.34.1
[615f187c] IfElse v0.1.1
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[842dd82b] InlineStrings v1.4.5
[18e54dd8] IntegerMathUtils v0.1.3
[a98d9a8b] Interpolations v0.16.2
[d1acc4aa] IntervalArithmetic v1.0.2
[8197267c] IntervalSets v0.7.13
[3587e190] InverseFunctions v0.1.17
[41ab1584] InvertedIndices v1.3.1
[92d709cd] IrrationalConstants v0.2.6
[f1662d9f] Isoband v0.1.1
[c8e1da08] IterTools v1.10.0
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[1019f520] JLFzf v0.1.11
[692b3bcd] JLLWrappers v1.7.1
[682c06a0] JSON v1.4.0
[0f8b85d8] JSON3 v1.14.3
[b835a17e] JpegTurbo v0.1.6
⌃ [63c18a36] KernelAbstractions v0.9.39
[5ab0869b] KernelDensity v0.6.11
[929cbde3] LLVM v9.4.6
[8b046642] LLVMLoopInfo v1.0.0
[b964fa9f] LaTeXStrings v1.4.0
[23fbe1c1] Latexify v0.16.10
[8cdb02fc] LazyModules v0.3.1
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[b2108857] Lux v1.31.3
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[1914dd2f] MacroTools v0.5.16
⌃ [ee78f7c6] Makie v0.24.8
[dbb5928d] MappedArrays v0.4.3
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⌃ [739be429] MbedTLS v1.1.9
[442fdcdd] Measures v0.3.3
[e1d29d7a] Missings v1.2.0
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[647866c9] PolygonOps v0.1.2
[2dfb63ee] PooledArrays v1.4.3
⌅ [aea7be01] PrecompileTools v1.2.1
⌃ [21216c6a] Preferences v1.5.1
⌃ [08abe8d2] PrettyTables v3.1.2
[27ebfcd6] Primes v0.5.7
[92933f4c] ProgressMeter v1.11.0
⌃ [3349acd9] ProtoBuf v1.2.0
⌃ [43287f4e] PtrArrays v1.3.0
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⌃ [3c362404] Reactant v0.2.213
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[45858cf5] Sixel v0.1.5
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[aedffcd0] Static v1.3.1
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[4c63d2b9] StatsFuns v1.5.2
⌃ [892a3eda] StringManipulation v0.4.2
[09ab397b] StructArrays v0.7.2
[53d494c1] StructIO v0.3.1
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⌃ [ec057cc2] StructUtils v2.6.2
[3783bdb8] TableTraits v1.0.1
[bd369af6] Tables v1.12.1
[62fd8b95] TensorCore v0.1.1
⌃ [731e570b] TiffImages v0.11.6
[e689c965] Tracy v0.1.6
[3bb67fe8] TranscodingStreams v0.11.3
[981d1d27] TriplotBase v0.1.0
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[1cfade01] UnicodeFun v0.4.1
[1986cc42] Unitful v1.28.0
[013be700] UnsafeAtomics v0.3.0
[41fe7b60] Unzip v0.2.0
[81def892] VersionParsing v1.3.0
[ea10d353] WeakRefStrings v1.4.2
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[efce3f68] WoodburyMatrices v1.1.0
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⌃ [d1e2174e] CUDA_Compiler_jll v0.4.1+1
⌃ [4ee394cb] CUDA_Driver_jll v13.1.0+2
⌅ [76a88914] CUDA_Runtime_jll v0.19.2+0
⌃ [83423d85] Cairo_jll v1.18.5+0
[ee1fde0b] Dbus_jll v1.16.2+0
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[2702e6a9] EpollShim_jll v0.0.20230411+1
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[559328eb] FriBidi_jll v1.0.17+0
[0656b61e] GLFW_jll v3.4.1+0
⌅ [d2c73de3] GR_jll v0.73.22+0
[b0724c58] GettextRuntime_jll v0.22.4+0
[61579ee1] Ghostscript_jll v9.55.1+0
[59f7168a] Giflib_jll v5.2.3+0
⌃ [7746bdde] Glib_jll v2.86.2+0
[3b182d85] Graphite2_jll v1.3.15+0
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[c834827a] Xorg_libSM_jll v1.2.6+0
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[0c0b7dd1] Xorg_libXau_jll v1.0.13+0
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[ea2f1a96] Xorg_libXrender_jll v0.9.12+0
[a65dc6b1] Xorg_libpciaccess_jll v0.18.1+0
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[e920d4aa] Xorg_xcb_util_cursor_jll v0.1.6+0
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[2f01184e] SparseArrays v1.11.0
[f489334b] StyledStrings v1.11.0
[4607b0f0] SuiteSparse
[fa267f1f] TOML v1.0.3
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[4536629a] OpenBLAS_jll v0.3.27+1
[05823500] OpenLibm_jll v0.8.5+0
[efcefdf7] PCRE2_jll v10.42.0+1
[bea87d4a] SuiteSparse_jll v7.7.0+0
[83775a58] Zlib_jll v1.2.13+1
[8e850b90] libblastrampoline_jll v5.11.0+0
[8e850ede] nghttp2_jll v1.59.0+0
[3f19e933] p7zip_jll v17.4.0+2
```
</p>
</details>
**Expected behavior**
The following methods should be implemented:
```julia
GPUArrays.sparse_array_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCOO
GPUArrays.sparse_array_type(::Type{<:CuSparseMatrixCSR}) = CuSparseMatrixCOO
GPUArrays.csc_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCSC
GPUArrays.csr_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCSR
GPUArrays.coo_type(sa::CuSparseMatrixCOO) = CuSparseMatrixCOO
```
The appropriate location for them is https://github.com/JuliaGPU/CUDA.jl/blob/153f819e49a18e9be8726af548a15ee8f69ba750/lib/cusparse/array.jl#L108-L126
**Version info**
Details on Julia:
```
# please post the output of: versioninfo()
Julia Version 1.11.5
Commit 760b2e5b739 (2025-04-14 06:53 UTC)
Build Info:
Official https://julialang.org/ release
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: 2 × Intel(R) Xeon(R) CPU @ 2.00GHz
WORD_SIZE: 64
LLVM: libLLVM-16.0.6 (ORCJIT, skylake-avx512)
Threads: 2 default, 0 interactive, 1 GC (on 2 virtual cores)
Environment:
LD_LIBRARY_PATH = /usr/lib64-nvidia
JULIA_NUM_THREADS = auto
```
Details on CUDA:
```
# please post the output of: CUDA.versioninfo()
CUDA toolchain:
- runtime 12.8, local installation
- driver 580.82.7 for 13.1
- compiler 12.9
CUDA libraries:
- CUBLAS: 12.8.4
- CURAND: 10.3.9
- CUFFT: 11.3.3
- CUSOLVER: 11.7.3
- CUSPARSE: 12.5.8
- CUPTI: 2025.1.1 (API 12.8.0)
- NVML: 13.0.0+580.82.7
Julia packages:
- CUDA: 5.9.6
- GPUArrays: 11.4.1
- GPUCompiler: 1.8.2
- KernelAbstractions: 0.9.39
- CUDA_Driver_jll: 13.1.0+2
- CUDA_Compiler_jll: 0.4.1+1
- CUDA_Runtime_jll: 0.19.2+0
- CUDA_Runtime_Discovery: 1.0.0
Toolchain:
- Julia: 1.11.5
- LLVM: 16.0.6
Preferences:
- CUDA_Runtime_jll.version: 12.8.1
- CUDA_Runtime_jll.local: true
1 device:
0: Tesla T4 (sm_75, 14.560 GiB / 15.000 GiB available)
```
**Additional context**
Tested on a Colab notebook (hence the weird deps).
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