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WIP: Inline optimized any/all for ArrayPartition on Julia 1.13+ #1

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WIP: Inline optimized any/all for ArrayPartition on Julia 1.13+ #1

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23 changes: 18 additions & 5 deletions src/array_partition.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -741,9 +741,22 @@ ODEProblem(func, AP[ [1.,2.,3.], [1. 2.;3. 4.] ], (0, 1)) |> solve
"""
struct AP end

# Optimized partition-level any/all for ArrayPartition lives in
# RecursiveArrayToolsArrayPartitionAnyAll to avoid ~780 invalidations.
# Without the extension, any/all uses the AbstractArray element-by-element
# fallback, which triggers scalar indexing errors on GPU arrays.
# Load the subpackage to fix:
# Optimized partition-level any/all for ArrayPartition.
#
# On Julia ≥ 1.13 (JuliaLang/julia#61184), Base removes the f::Function
# restriction from any/all, so defining any(f, ::ArrayPartition) causes
# only 1 invalidation (down from ~780). Safe to inline directly.
#
# On Julia < 1.13, the methods live in RecursiveArrayToolsArrayPartitionAnyAll
# to avoid the invalidations. Without the extension, any/all uses the
# AbstractArray element-by-element fallback, which triggers scalar indexing
# errors on GPU arrays. Load the subpackage to fix:
# using RecursiveArrayToolsArrayPartitionAnyAll
@static if VERSION >= v"1.13.0-DEV.0"
Base.any(f, A::ArrayPartition) = any((any(f, x) for x in A.x))
Base.any(f::Function, A::ArrayPartition) = any((any(f, x) for x in A.x))
Base.any(A::ArrayPartition) = any(identity, A)
Base.all(f, A::ArrayPartition) = all((all(f, x) for x in A.x))
Base.all(f::Function, A::ArrayPartition) = all((all(f, x) for x in A.x))
Base.all(A::ArrayPartition) = all(identity, A)
end
16 changes: 10 additions & 6 deletions test/partitions_test.jl
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Expand Up @@ -178,13 +178,17 @@ recursivecopy!(dest_ap, src_ap)
@inferred mapreduce(string, *, x)
@test mapreduce(i -> string(i) * "q", *, x) == "1q2q3.0q4.0q"

# any/all — optimized partition-level iteration requires RecursiveArrayToolsArrayPartitionAnyAll
# to avoid ~780 invalidations. Without the extension, Base's AbstractArray fallback is used.
# On GPU arrays, the fallback triggers scalar indexing errors — load the subpackage to fix.
@test which(any, Tuple{Function, ArrayPartition}).module === Base
@test which(all, Tuple{Function, ArrayPartition}).module === Base
# any/all — on Julia ≥ 1.13, optimized methods are inlined (1 invalidation).
# On older Julia, they require RecursiveArrayToolsArrayPartitionAnyAll (~780 invalidations).
@static if VERSION >= v"1.13.0-DEV.0"
@test which(any, Tuple{Function, ArrayPartition}).module === RecursiveArrayTools
@test which(all, Tuple{Function, ArrayPartition}).module === RecursiveArrayTools
else
@test which(any, Tuple{Function, ArrayPartition}).module === Base
@test which(all, Tuple{Function, ArrayPartition}).module === Base
end

# Correctness tests (work via AbstractArray fallback on CPU)
# Correctness tests
@test !any(isnan, AP[[1, 2], [3.0, 4.0]])
@test !any(isnan, AP[[3.0, 4.0]])
@test any(isnan, AP[[NaN], [3.0, 4.0]])
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