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Fix rrule for rfft and ifft for CuArray #96

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Fix rrule for rfft and ifft for CuArray #96

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e0e667f
fix https://github.com/JuliaMath/AbstractFFTs.jl/issues/95
ziyiyin97 Mar 28, 2023
eac7da4
scaling in place instead of type conversion
ziyiyin97 Apr 11, 2023
dc2cfab
fix immutable array by similar
ziyiyin97 Apr 12, 2023
a22c168
add more comments
ziyiyin97 Apr 12, 2023
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58 changes: 39 additions & 19 deletions ext/AbstractFFTsChainRulesCoreExt.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -26,18 +26,25 @@ end
function ChainRulesCore.rrule(::typeof(rfft), x::AbstractArray{<:Real}, dims)
y = rfft(x, dims)

# compute scaling factors
halfdim = first(dims)
d = size(x, halfdim)
n = size(y, halfdim)
scale = reshape(
[i == 1 || (i == n && 2 * (i - 1) == d) ? 1 : 2 for i in 1:n],
ntuple(i -> i == first(dims) ? n : 1, Val(ndims(x))),
)

project_x = ChainRulesCore.ProjectTo(x)
function rfft_pullback(ȳ)
x̄ = project_x(brfft(ChainRulesCore.unthunk(ȳ) ./ scale, d, dims))
dY = ChainRulesCore.unthunk(ȳ)
# apply scaling; below approach is for GPU CuArray compatibility, see PR #96
dY_scaled = similar(dY)
dY_scaled .= dY ./ 2
# assign view to a separate variable before assignment, to support Julia <1.2
# see https://github.com/JuliaLang/julia/issues/31295
v = selectdim(dY_scaled, halfdim, 1)
v .*= 2
if 2 * (n - 1) == d
v = selectdim(dY_scaled, halfdim, n)
v .*= 2
end
x̄ = project_x(brfft(dY_scaled, d, dims))
return ChainRulesCore.NoTangent(), x̄, ChainRulesCore.NoTangent()
end
return y, rfft_pullback
Expand Down Expand Up @@ -67,19 +74,25 @@ end
function ChainRulesCore.rrule(::typeof(irfft), x::AbstractArray, d::Int, dims)
y = irfft(x, d, dims)

# compute scaling factors
halfdim = first(dims)
n = size(x, halfdim)
invN = AbstractFFTs.normalization(y, dims)
twoinvN = 2 * invN
scale = reshape(
[i == 1 || (i == n && 2 * (i - 1) == d) ? invN : twoinvN for i in 1:n],
ntuple(i -> i == first(dims) ? n : 1, Val(ndims(x))),
)

project_x = ChainRulesCore.ProjectTo(x)
function irfft_pullback(ȳ)
x̄ = project_x(scale .* rfft(real.(ChainRulesCore.unthunk(ȳ)), dims))
dX = rfft(real.(ChainRulesCore.unthunk(ȳ)), dims)
# apply scaling; below approach is for GPU CuArray compatibility, see PR #96
dX_scaled = similar(dX)
dX_scaled .= dX .* invN .* 2
# assign view to a separate variable before assignment, to support Julia <1.2
# see https://github.com/JuliaLang/julia/issues/31295
v = selectdim(dX_scaled, halfdim, 1)
v ./= 2
if 2 * (n - 1) == d
v = selectdim(dX_scaled, halfdim, n)
v ./= 2
end
x̄ = project_x(dX_scaled)
return ChainRulesCore.NoTangent(), x̄, ChainRulesCore.NoTangent(), ChainRulesCore.NoTangent()
end
return y, irfft_pullback
Expand Down Expand Up @@ -108,17 +121,24 @@ end
function ChainRulesCore.rrule(::typeof(brfft), x::AbstractArray, d::Int, dims)
y = brfft(x, d, dims)

# compute scaling factors
halfdim = first(dims)
n = size(x, halfdim)
scale = reshape(
[i == 1 || (i == n && 2 * (i - 1) == d) ? 1 : 2 for i in 1:n],
ntuple(i -> i == first(dims) ? n : 1, Val(ndims(x))),
)

project_x = ChainRulesCore.ProjectTo(x)
function brfft_pullback(ȳ)
x̄ = project_x(scale .* rfft(real.(ChainRulesCore.unthunk(ȳ)), dims))
dX = rfft(real.(ChainRulesCore.unthunk(ȳ)), dims)
# apply scaling; below approach is for GPU CuArray compatibility, see PR #96
dX_scaled = similar(dX)
dX_scaled .= dX .* 2
# assign view to a separate variable before assignment, to support Julia <1.2
# see https://github.com/JuliaLang/julia/issues/31295
v = selectdim(dX_scaled, halfdim, 1)
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@gaurav-arya gaurav-arya Apr 12, 2023 •
edited
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maybe a comment above this line saying something like like # assign view to a separate variable before assignment, to support Julia <1.2?

v ./= 2
if 2 * (n - 1) == d
v = selectdim(dX_scaled, halfdim, n)
v ./= 2
end
x̄ = project_x(dX_scaled)
return ChainRulesCore.NoTangent(), x̄, ChainRulesCore.NoTangent(), ChainRulesCore.NoTangent()
end
return y, brfft_pullback
Expand Down