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Narrow AbstractArray to AbstractArray{<:Number} in jacobian #1582

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Narrow AbstractArray to AbstractArray{<:Number} in jacobian #1582

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179bfaf
narrow AbstractArray in jacobian
mcabbott Jul 23, 2025
9f84c3f
mark unbroken an unrelated test
mcabbott Jul 23, 2025
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6 changes: 3 additions & 3 deletions src/lib/grad.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@ julia> jacobian((a,d) -> prod(a, dims=d), [1 2; 3 4; 5 6], 2)
```

!!! warning
For arguments of any type except `Number` & `AbstractArray`, the result is `nothing`.
For arguments of any type except `Number` & `AbstractArray{<:Number}`, the result is `nothing`.

```
julia> jacobian((a,s) -> a.^length(s), [1,2,3], "str")
Expand Down Expand Up @@ -181,7 +181,7 @@ function withjacobian(f, args...)
y, back = pullback(_jvec∘f, args...)
out = map(args) do x
T = promote_type(eltype(x), eltype(y))
dx = x isa AbstractArray ? similar(x, T, length(y), length(x)) :
dx = x isa AbstractArray{<:Number} ? similar(x, T, length(y), length(x)) :
x isa Number ? similar(y, T, length(y)) :
nothing
end
Expand All @@ -196,7 +196,7 @@ function withjacobian(f, args...)
(val=y, grad=out)
end

_jvec(x::AbstractArray) = vec(x)
_jvec(x::AbstractArray{<:Number}) = vec(x)
_jvec(x::Number) = _jvec(vcat(x))
_jvec(x) = throw(ArgumentError("jacobian expected a function which returns an array, or a scalar, got $(typeof(x))"))
_jvec(x::AbstractArray{<:Complex}) = throw(ArgumentError("jacobian does not accept complex output"))
Expand Down
4 changes: 2 additions & 2 deletions test/gradcheck_p1_tests.jl
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Expand Up @@ -190,8 +190,8 @@ end
@test gradient(p -> sum(collect(p*i for i in Iterators.take([1.0, 2.0, 3.0], 3))), 2.0) == (6.0,)
@test gradient(p -> sum(collect(p*i for i in Iterators.take(p*[1.0, 2.0, 3.0], 2))), 2.0) == (12.0,)
# generator 0-d behavior handled incorrectly
@test_broken gradient(p -> sum(collect(p*i for i in 1.0)), 2.0)
@test_broken gradient(p -> sum(collect(p*i for i in fill(1.0))), 2.0)
@test_broken gradient(p -> sum(collect(p*i for i in 1.0)), 2.0) == (1.0,)
@test gradient(p -> sum(collect(p*i for i in fill(1.0))), 2.0) == (1.0,)

# adjoints for iterators
@test gradient(x -> sum(collect(Iterators.take([x*i for i in 1:5], 4))), 1.0) == (10.0,)
Expand Down
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