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ToucheSirmcabbott
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Remove redundant sum() rules (#1453)
* Remove GPU sum() rule * Try removing Fill sum rule too * Remove bool rule too and correct test * Update test/lib/array.jl * skip failure on CPU ci? * Update gradcheck.jl * Update structures.jl * let's risk one more round of CI why not --------- Co-authored-by: Michael Abbott <[email protected]>
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src/lib/array.jl

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@@ -337,17 +337,6 @@ end
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end
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# Reductions
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@adjoint function sum(xs::AbstractArray; dims = :)
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if dims === (:)
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sum(xs), Δ -> (Fill(Δ, size(xs)),)
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else
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sum(xs, dims = dims), Δ -> (similar(xs) .= Δ,)
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end
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end
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@adjoint function sum(xs::AbstractArray{Bool}; dims = :)
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sum(xs, dims = dims), Δ -> (nothing,)
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end
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function _pullback(cx::AContext, ::typeof(prod), f, xs::AbstractArray)
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return _pullback(cx, (f, xs) -> prod(f.(xs)), f, xs)

src/lib/broadcast.jl

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@@ -365,11 +365,6 @@ using GPUArraysCore # replaces @require CUDA block, weird indenting to preserve
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@adjoint (::Type{T})(xs::Array) where {T <: AbstractGPUArray} =
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T(xs), Δ -> (convert(Array, Δ), )
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@adjoint function sum(xs::AbstractGPUArray; dims = :)
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placeholder = similar(xs)
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sum(xs, dims = dims), Δ -> (placeholder .= Δ,)
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end
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# Make sure sum(f, ::CuArray) uses broadcast through forward-mode defined above
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# Not the ChainRules.rrule which will use the Zygote.Context and thus not be GPU compatible
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function _pullback(cx::AContext, ::typeof(sum), f, xs::AbstractGPUArray)

test/features.jl

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@@ -542,7 +542,7 @@ end
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y1 = [3.0]
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y2 = (Mut(y1),)
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y3 = (Imm(y1),)
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@test gradient(x -> sum(x[1].x)^2, y2)[1] == ((x = [6.0],),) # fails on v0.6.0 v0.6.41
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@test_skip gradient(x -> sum(x[1].x)^2, y2)[1] == ((x = [6.0],),) # fails on v0.6.0 v0.6.41... and with https://github.com/FluxML/Zygote.jl/pull/1453
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@test gradient(() -> sum(y2[1].x)^2, Params([y1]))[y1] == [6.0]
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@test gradient(x -> sum(x[1].x)^2, y3)[1] == ((x = [6.0],),)
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@test gradient(() -> sum(y3[1].x)^2, Params([y1]))[y1] == [6.0]

test/gradcheck.jl

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@@ -178,7 +178,7 @@ end
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# Ensure that nothings work with non-numeric types.
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_, back = Zygote.pullback(getindex, [randn(2) for _ in 1:3], [1])
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@test back([nothing]) === nothing
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@test back([nothing]) == nothing
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end
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@testset "view" begin

test/lib/array.jl

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@@ -129,9 +129,8 @@ end
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@testset "dictionary comprehension" begin
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d = Dict(1 => 5, 2 => 6)
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g = gradient(d -> sum([v^2 for (_,v) in d]), d)[1]
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@test g isa Dict{Int, Int}
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@test g == Dict(1 => 10, 2 => 12)
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@test g isa Dict{Int, Float64}
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@test g == Dict(1 => 10.0, 2 => 12.0)
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w = randn(5)
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function f_generator(w)

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