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Minor improvements to sparse tests #755

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Merged
christiangnrd merged 5 commits into from
Aug 7, 2026
Merged

Minor improvements to sparse tests #755

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5fa6226
Make some sparse tests less flaky
christiangnrd Aug 5, 2026
ca3dc68
Split tests
christiangnrd Aug 5, 2026
9be6668
More NFC testset improvements
christiangnrd Aug 6, 2026
7e11eb3
Clarify
christiangnrd Aug 6, 2026
c6fe9de
Whitespace consistency
christiangnrd Aug 6, 2026
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3 changes: 1 addition & 2 deletions test/testsuite.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -76,8 +76,7 @@ supported_eltypes() = (Int16, Int32, Int64,
ComplexF16, ComplexF32, ComplexF64,
Complex{Int16}, Complex{Int32}, Complex{Int64})

# derived sparse types that are supported by the array type

# derived sparse container types that are supported by the array type
sparse_types(::Type{AT}) where {AT} = ()

# some convenience predicates for filtering test eltypes
Expand Down
76 changes: 37 additions & 39 deletions test/testsuite/sparse.jl
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
@testsuite "sparse" (AT, eltypes)->begin
sparse_ATs = sparse_types(AT)
for sparse_AT in sparse_ATs
@testset "sparse_AT = $sparse_AT" for sparse_AT in sparse_ATs
if sparse_AT <: AbstractSparseVector
vector(sparse_AT, eltypes)
vector_construction(sparse_AT, eltypes)
Expand All @@ -22,8 +22,8 @@ using SparseArrays: nonzeroinds, nonzeros, rowvals

function vector(AT, eltypes)
dense_AT = GPUArrays.dense_array_type(AT)
for ET in eltypes
@testset "Sparse vector properties($ET)" begin
@testset "Sparse vector properties" begin
@testset "$ET" for ET in eltypes
m = 25
n = 35
k = 10
Expand Down Expand Up @@ -76,8 +76,8 @@ end

function matrix(AT, eltypes)
dense_AT = GPUArrays.dense_array_type(AT)
for ET in eltypes
@testset "Sparse matrix properties($ET)" begin
@testset "Sparse matrix properties" begin
@testset "$ET" for ET in eltypes
m = 25
n = 35
k = 10
Expand Down Expand Up @@ -153,8 +153,8 @@ end

function broadcasting_vector(AT, eltypes)
dense_AT = GPUArrays.dense_array_type(AT)
for ET in eltypes
@testset "SparseVector($ET)" begin
@testset "SparseVector broadcasting" begin
@testset "$ET" for ET in eltypes
m = 64
p = 0.5
x = sprand(ET, m, p)
Expand Down Expand Up @@ -189,7 +189,7 @@ function broadcasting_vector(AT, eltypes)
z = x .* y
dz = dx .* dy
@test dz isa AT{ET}
@test z == SparseVector(dz)
@test z ≈ SparseVector(dz)

# multiple inputs
y = sprand(ET, m, p)
Expand All @@ -200,7 +200,7 @@ function broadcasting_vector(AT, eltypes)
z = @. x * y * w
dz = @. dx * dy * dw
@test dz isa AT{ET}
@test z == SparseVector(dz)
@test z ≈ SparseVector(dz)

y = sprand(ET, m, p)
w = sprand(ET, m, p)
Expand All @@ -211,15 +211,15 @@ function broadcasting_vector(AT, eltypes)
z = @. x * y * w * dense_arr
dz = @. dx * dy * dw * d_dense_arr
@test dz isa dense_AT{ET}
@test Array(z) == Array(dz)
@test Array(z) ≈ Array(dz)

y = sprand(ET, m, p)
dy = AT(y)
dx = AT(x)
z = x .* y .* ET(2)
dz = dx .* dy .* ET(2)
@test dz isa AT{ET}
@test z == SparseVector(dz)
@test z ≈ SparseVector(dz)

# type-mismatching
## non-zero-preserving
Expand All @@ -242,8 +242,8 @@ end

function broadcasting_matrix(AT, eltypes)
dense_AT = GPUArrays.dense_array_type(AT)
for ET in eltypes
@testset "SparseMatrix($ET)" begin
@testset "SparseMatrix broadcasting" begin
@testset "$ET" for ET in eltypes
m, n = 5, 6
p = 0.5
x = sprand(ET, m, n, p)
Expand All @@ -267,22 +267,22 @@ function broadcasting_matrix(AT, eltypes)
dy = dx .* dense_AT(ones(ET, m, n))
@test dy isa dense_AT{ET}
@test Array(y) == Array(dy)

# multiple inputs
y = sprand(ET, m, n, p)
dy = AT(y)
z = x .* y .* ET(2)
dz = dx .* dy .* ET(2)
@test dz isa AT{ET}
@test z == SparseMatrixCSC(dz)
@test z ≈ SparseMatrixCSC(dz)

# multiple inputs
w = sprand(ET, m, n, p)
dw = AT(w)
z = x .* y .* w
dz = dx .* dy .* dw
@test dz isa AT{ET}
@test z == SparseMatrixCSC(dz)
@test z ≈ SparseMatrixCSC(dz)

# create a matrix with nnz < leading_dim
x = spdiagm(m, m, 2=>rand(ET, m - 2))
Expand All @@ -302,8 +302,8 @@ end

function mapreduce_matrix(AT, eltypes)
dense_AT = GPUArrays.dense_array_type(AT)
for ET in eltypes
@testset "SparseMatrix($ET)" begin
@testset "SparseMatrix mapreduce" begin
@testset "$ET" for ET in eltypes
m,n = 5,6
p = 0.5
x = sprand(ET, m, n, p)
Expand Down Expand Up @@ -355,31 +355,29 @@ end

function linalg(AT, eltypes)
dense_AT = GPUArrays.dense_array_type(AT)
for ET in eltypes
@testset "Sparse matrix linear algebra" begin
# sprandn doesn't work nicely with these...
if !(ET <: Union{Int16, Int32, Int64, Complex{Int16}, Complex{Int32}, Complex{Int64}})
@testset "Sparse matrix($ET) linear algebra" begin
m = 10
A = sprandn(ET, m, m, 0.2)
B = sprandn(ET, m, m, 0.3)
ZA = spzeros(ET, m, m)
C = I(div(m, 2))
dA = AT(A)
dB = AT(B)
dZA = AT(ZA)
@testset "opnorm and norm" begin
@test opnorm(A, Inf) ≈ opnorm(dA, Inf)
@test opnorm(A, 1) ≈ opnorm(dA, 1)
@test_throws ArgumentError opnorm(dA, 2)
end
@testset "$ET" for ET in filter(T -> !(T <: Union{Int16, Int32, Int64, Complex{Int16}, Complex{Int32}, Complex{Int64}}), eltypes)
m = 10
A = sprandn(ET, m, m, 0.2)
B = sprandn(ET, m, m, 0.3)
ZA = spzeros(ET, m, m)
C = I(div(m, 2))
dA = AT(A)
dB = AT(B)
dZA = AT(ZA)
@testset "opnorm and norm" begin
@test opnorm(A, Inf) ≈ opnorm(dA, Inf)
@test opnorm(A, 1) ≈ opnorm(dA, 1)
@test_throws ArgumentError opnorm(dA, 2)
end
end
end
end

function iszero_vector(AT, eltypes)
for ET in eltypes
@testset "iszero SparseVector($ET)" begin
@testset "iszero SparseVector" begin
@testset "$ET" for ET in eltypes
m = 25

# Test non-zero sparse vector
Expand Down Expand Up @@ -408,8 +406,8 @@ function iszero_vector(AT, eltypes)
end

function iszero_matrix(AT, eltypes)
for ET in eltypes
@testset "iszero SparseMatrix($ET)" begin
@testset "iszero SparseMatrix" begin
@testset "$ET" for ET in eltypes
m, n = 10, 10

# Test non-zero sparse matrix
Expand Down
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