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In-place broadcasting into a `VectorOfArray` mishandles arrays with fewer dimensions

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调研方向

Start with unpack_voa in src/vector_of_array.jl, which slices every array argument along its last dimension, and with the BroadcastStyle methods for VectorOfArrayStyle that route v .= ... through it. The FastBroadcast extension's fast_materialize! for AbstractVectorOfSArray depends on the same slicing. Done means each case in the issue's table (vector, 1×2, fill(2.0), and 3×2 arguments, with both Vector and SVector inner arrays) matches Array(v) broadcasting, with tests added.

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描述

Since v4, a VectorOfArray is a proper AbstractArray (VectorOfArray([[1, 2, 3], [4, 5, 6]]) is a 3×2 array whose columns are the inner arrays), so broadcasting should match broadcasting with Array(v). In-place broadcasting into a VectorOfArray only does so if every array argument has the same number of dimensions as the VectorOfArray. Otherwise it errors or silently returns wrong results:

using RecursiveArrayTools

v = VectorOfArray([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]])
v .= v .+ [10.0, 20.0, 30.0]
Array(v)
# 3×2 Matrix{Float64}:
#  11.0  24.0
#  12.0  25.0
#  13.0  26.0
#
# but Array(v) .+ [10.0, 20.0, 30.0] is
#  11.0  14.0
#  22.0  25.0
#  33.0  36.0

For the same v (and the same with SVectors as inner arrays):

x v .= x .+ 1 v .= v .+ x
[10.0, 20.0, 30.0] error¹ wrong result (see above)
[10.0 20.0] (1×2) error¹ ✓
fill(2.0) ArgumentError: tuple length should be ≥ 0, got -1 same error
3×2 Matrix ✓ ✓

¹ DimensionMismatch: destination axes (Base.OneTo(3),) are not compatible with source axes ... with Vectors as inner arrays; MethodError: Cannot convert an object of type ... to an object of type Float64 with SVectors.

Out-of-place broadcasting such as v .+ x gives the correct results for vectors and matrices x (the broadcast style becomes DefaultArrayStyle{2}, so Base handles it). It fails only for fill(2.0), because BroadcastStyle(::VectorOfArrayStyle, ::DefaultArrayStyle{0}) returns the VectorOfArrayStyle, which treats zero-dimensional arrays like scalars.

The cause is unpack_voa (src/vector_of_array.jl):

function unpack_voa(x::AbstractArray{T, N}, i) where {T, N}
    return @view x[ntuple(x -> Colon(), N - 1)..., i]
end

It slices every array argument along its own last dimension, as if that dimension indexed the inner arrays. That holds only if ndims(x) equals the number of dimensions of the VectorOfArray. With Base's broadcasting semantics, an argument with fewer dimensions should be broadcast across the inner arrays as a whole (zero-dimensional arrays like scalars), and an argument whose last dimension has size 1 should not be indexed with i.

The FastBroadcast extension relies on the same assumption: fast_materialize!(::Serial, dst::AbstractVectorOfSArray, bc) builds each inner SArray from unpack_voa(bc, i) and needs exactly length(dst.u[i]) elements. For example, with FastBroadcast 1.4.0:

using RecursiveArrayTools, StaticArrays, FastBroadcast

v = VectorOfArray([SVector(1.0, 2.0, 3.0), SVector(4.0, 5.0, 6.0)])
x = [10.0, 20.0, 30.0]
@.. v = x + 1  # ERROR: Generator produced too few elements: Expected exactly 3 elements, but got 1

RecursiveArrayTools 4.5.3, Julia 1.13.1.

🤖 Generated with Claude Code

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