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ensure sum(f,x) works on GPU #1004

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Jun 21, 2021
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9 changes: 8 additions & 1 deletion src/lib/broadcast.jl
Original file line number Diff line number Diff line change
Expand Up @@ -254,7 +254,14 @@ end
placeholder = similar(xs)
sum(xs, dims = dims), Δ -> (placeholder .= Δ,)
end


# Make sure sum(f, ::CuArray) uses broadcase through forward-mode defined above
# Not the ChainRules.rrule which will use the Zygote.Context and thus not be GPU compatible
@adjoint function sum(f, xs::CuArray; kws...)
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@assert !haskey(kws, :init) # TODO add init support (julia 1.6)
return pullback(__context__, (f, xs) -> sum(f.(xs); kws...), f, xs)
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You probably don't need the context manager here

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@oxinabox oxinabox Jun 21, 2021

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This is exactly the old code.
I don't really know what it is doing returning the context<

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I think keeping it is better.
It should end up hitting the same code either way, but I can imagine if some specialization are added then the errors we would get are more confusing if we don't include the __context__

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Might be slightly tidier to call broadcast_forward directly, instead of going back to pullback. But this is a quick fix to repair an accidental break so the most direct restoration is fine too.

end

@adjoint function Base.convert(::Type{T}, xs::Array) where {T<:CUDA.CuArray}
Base.convert(T, xs), Δ -> (nothing, Base.convert(Array, Δ),)
end
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11 changes: 11 additions & 0 deletions test/cuda.jl
Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,17 @@ end
@test g_gpu |> collect ≈ g
end

@testset "sum(f, x)" begin
a = Float32.(-4:4)
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a_gpu = a |> cu

f(x) = sum(abs, x)
g = gradient(f, a)[1]
g_gpu = gradient(f, a_gpu)[1]
@test g_gpu isa CuArray
@test g_gpu |> collect ≈ g
end

@testset "jacobian" begin
v1 = cu(collect(1:3f0))

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