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Remove unfortunate OffsetArrays specializations #154

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Remove unfortunate OffsetArrays specializations #154

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a6fd7e8
Remove unfortunate OffsetArrays specializations
timholy Jan 27, 2020
7b500f6
WIP (might make it slower)
timholy Mar 30, 2020
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1 change: 0 additions & 1 deletion src/ImageFiltering.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,6 @@ export Kernel, KernelFactors,

FixedColorant{T<:Normed} = Colorant{T}
StaticOffsetArray{T,N,A<:StaticArray} = OffsetArray{T,N,A}
OffsetVector{T} = OffsetArray{T,1}

# Add a fix that should have been included in julia-1.0.3
if isdefined(Broadcast, :_sametype) && !isdefined(Broadcast, :axistype)
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5 changes: 0 additions & 5 deletions src/border.jl
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Expand Up @@ -681,11 +681,6 @@ function copydata!(dest, img, inds)
dest
end

function copydata!(dest::OffsetArray, img, inds::Tuple{Vararg{OffsetArray}})
copydata!(parent(dest), img, map(parent, inds))
dest
end

Base.ndims(b::AbstractBorder) = ndims(typeof(b))
Base.ndims(::Type{Pad{N}}) where {N} = N

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78 changes: 7 additions & 71 deletions src/imfilter.jl
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Expand Up @@ -996,36 +996,15 @@ end

function __imfilter_inbounds!(r, out, A, kern, border, R, z)
Rk = CartesianIndices(axes(kern))
Rkhead, Rktail = safehead(Rk), safetail(Rk)
for I in safetail(R), i in safehead(R)
tmp = z
@inbounds for J in safetail(Rk), j in safehead(Rk)
tmp += safe_for_prod(A[i+j,I+J], tmp)*kern[j,J]
end
@inbounds out[i,I] = tmp
end
out
end

# This is unfortunate, but specializing this saves an add in the inner
# loop and results in a modest performance improvement. It would be
# nice if LLVM did this automatically. (@polly?)
function __imfilter_inbounds!(r, out, A::OffsetArray, kern::OffsetArray, border, R, z)
off, k = CartesianIndex(kern.offsets), parent(kern)
o, O = safehead(off), safetail(off)
Rnew = CartesianIndices(map((x,y)->x.+y, R.indices, Tuple(off)))
Rk = CartesianIndices(axes(k))
offA, pA = CartesianIndex(A.offsets), parent(A)
oA, OA = safehead(offA), safetail(offA)
for I in safetail(Rnew)
IA = I-OA
for i in safehead(Rnew)
tmp = z
iA = i-oA
@inbounds for J in safetail(Rk), j in safehead(Rk)
tmp += safe_for_prod(pA[iA+j,IA+J], tmp)*k[j,J]
@inbounds for J in Rktail
for j in Rkhead
tmp += safe_for_prod(A[i+j,I+J], tmp)*kern[j,J]
end
@inbounds out[i-o,I-O] = tmp
end
@inbounds out[i,I] = tmp
end
out
end
Expand All @@ -1042,64 +1021,21 @@ function _imfilter_inbounds!(r::AbstractResource, out, A::AbstractArray, kern::R
_imfilter_inbounds!(r, z, out, A, k, Rpre, ind, Rpost)
end

# Many of the following are unfortunate specializations
function _imfilter_inbounds!(r::AbstractResource, z, out, A::AbstractArray, k::OffsetVector, Rpre::CartesianIndices, ind, Rpost::CartesianIndices)
_imfilter_inbounds!(r, z, out, A, parent(k), Rpre, ind, Rpost, k.offsets[1])
end

function _imfilter_inbounds!(r::AbstractResource, z, out, A::AbstractArray, k::AbstractVector, Rpre::CartesianIndices, ind, Rpost::CartesianIndices, koffset=0)
indsk = axes(k, 1)
for Ipost in Rpost
for i in ind
ik = i+koffset
for Ipre in Rpre
tmp = z
for j in indsk
@inbounds tmp += safe_for_prod(A[Ipre,ik+j,Ipost], tmp)*k[j]
end
@inbounds out[Ipre,i,Ipost] = tmp
end
end
end
out
end

function _imfilter_inbounds!(r::AbstractResource, out, A::OffsetArray, kern::ReshapedVector, border::NoPad, inds)
Rpre, ind, Rpost = iterdims(inds, kern)
k = kern.data
R, Rk = CartesianIndices(inds), CartesianIndices(axes(kern))
if isempty(R) || isempty(Rk)
return out
end
p = accumfilter(A[first(R)+first(Rk)], first(k))
z = zero(typeof(p+p))
Opre, o, Opost = KernelFactors.indexsplit(CartesianIndex(A.offsets), kern)
_imfilter_inbounds!(r, z, out, parent(A), k, Rpre, ind, Rpost, Opre, o, Opost)
end

function _imfilter_inbounds!(r::AbstractResource, z, out, A::AbstractArray, k::OffsetVector, Rpre::CartesianIndices, ind, Rpost::CartesianIndices, Opre, o, Opost)
_imfilter_inbounds!(r, z, out, A, parent(k), Rpre, ind, Rpost, Opre, o, Opost, k.offsets[1])
end

function _imfilter_inbounds!(r::AbstractResource, z, out, A::AbstractArray, k::AbstractVector, Rpre::CartesianIndices, ind, Rpost::CartesianIndices, Opre, o, Opost, koffset=0)
function _imfilter_inbounds!(r::AbstractResource, z, out, A::AbstractArray, k::AbstractVector, Rpre::CartesianIndices, ind, Rpost::CartesianIndices)
indsk = axes(k, 1)
for Ipost in Rpost
IOpost = Ipost - Opost
for i in ind
io = i-o+koffset
for Ipre in Rpre
IOpre = Ipre - Opre
tmp = z
for j in indsk
@inbounds tmp += safe_for_prod(A[IOpre,io+j,IOpost], tmp)*k[j]
@inbounds tmp += safe_for_prod(A[Ipre,i+j,Ipost], tmp)*k[j]
end
@inbounds out[Ipre,i,Ipost] = tmp
end
end
end
out
end
# end unfortunate specializations

## commented out because "virtual padding" is commented out
# function _imfilter_iter!(r::AbstractResource, out, padded, kernel::AbstractArray, iter)
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