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Add some more functions and improve broadcasting support #69

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Jun 8, 2024
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Add some more functions and improve broadcasting support #69

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05f57fa
Add some more functions and improve broadcasting support
christiangnrd Mar 13, 2024
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christiangnrd Mar 13, 2024
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christiangnrd Mar 13, 2024
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christiangnrd Mar 13, 2024
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2 changes: 1 addition & 1 deletion src/AppleAccelerate.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -92,9 +92,9 @@ function __init__()
end

if Sys.isapple()
include("Util.jl")
include("Array.jl")
include("DSP.jl")
include("Util.jl")
end

end # module
136 changes: 135 additions & 1 deletion src/Array.jl
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Expand Up @@ -116,6 +116,9 @@
Base.copy(bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T, N}}}) where {Style, Axes, N} = ($f)(bc.args...)
Base.copyto!(dest::Array{$T, N}, bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T, N}}}) where {Style, Axes, N} = ($f!)(dest, bc.args...)
end
if T == Float32
@eval Base.broadcasted(::typeof($f), arg::Union{Array{F,N},Base.Broadcast.Broadcasted}) where {N,F<:Union{Float32,Float64}} = ($f)(maybecopy(arg))
end
end
for (f, fa) in (twoarg_funcs...,(:pow,:pow))
f! = Symbol("$(f)!")
Expand All @@ -124,14 +127,19 @@
Base.copy(bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T, N},Array{$T,N}}}) where {Style, Axes, N} = ($f)(bc.args...)
Base.copyto!(dest::Array{$T, N}, bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T,N},Array{$T,N}}}) where {Style, Axes, N} = ($f!)(dest, bc.args...)
end
if T == Float32
@eval Base.broadcasted(::typeof($f), arg1::Union{Array{F, N},Base.Broadcast.Broadcasted}, arg2::Union{Array{F, N},Base.Broadcast.Broadcasted}) where {N,F<:Union{Float32,Float64}} = ($f)(maybecopy(arg1), maybecopy(arg2))
end
end
end

# Functions over single vectors that return scalars/tuples
for (T, suff) in ((Float32, ""), (Float64, "D"))

for (f, fa) in ((:maximum, :maxv), (:minimum, :minv), (:mean, :meanv),
(:meansqr, :measqv), (:meanmag, :meamgv), (:sum, :sve))
(:meanmag, :meamgv), (:meansqr, :measqv), (:meanssqr, :mvessq),
(:sum, :sve), (:summag, :svemg), (:sumsqr, :svesq),
(:sumssqr, :svs))
@eval begin
function ($f)(X::Vector{$T})
val = Ref{$T}(0.0)
Expand Down Expand Up @@ -192,7 +200,133 @@
return result
end
end

@eval begin
# Broadcasting override such that f.(X) turns into f(X)
Base.copy(bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T, N},Array{$T,N}}}) where {Style, Axes, N} = ($f)(bc.args...)
Base.copyto!(dest::Array{$T, N}, bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T,N},Array{$T,N}}}) where {Style, Axes, N} = ($f!)(dest, bc.args...)

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Base.broadcasted(::typeof($f), arg1::Union{Array{$T, N},Base.Broadcast.Broadcasted}, arg2::Union{Array{$T, N},Base.Broadcast.Broadcasted}) where {N} = ($f)(maybecopy(arg1), maybecopy(arg2))
end
end
end

# Element-wise operations over a vector and a scalar
for (T, suff) in ((Float32, ""), (Float64, "D"))

for (f, name) in ((:vsadd, "addition"), (:vsdiv, "division"), (:vsmul, "multiplication"))
f! = Symbol("$(f)!")

@eval begin
@doc """

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`$($f!)(result::Vector{$($T)}, X::Vector{$($T)}, c::$($T))`

Implements vector-scalar **$($name)** over **Vector{$($T)}** and $($T) and overwrites
the result vector with computed value. *Returns:* **Vector{$($T)}** `result`
""" ->
function ($f!)(result::Vector{$T}, X::Vector{$T}, c::$T)
ccall(($(string("vDSP_", f, suff), libacc)), Cvoid,
(Ptr{$T}, Int64, Ptr{$T}, Ptr{$T}, Int64, UInt64),
X, 1, Ref(c), result, 1, length(result))
return result
end
end

@eval begin
@doc """

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`$($f)(X::Vector{$($T)}, c::$($T))`

Implements vector-scalar **$($name)** over **Vector{$($T)}** and $($T). Allocates
memory to store result. *Returns:* **Vector{$($T)}**
""" ->
function ($f)(X::Vector{$T}, c::$T)
result = similar(X)
($f!)(result, X, c)
return result
end
end
end
f = :vssub
f! = Symbol("$(f)!")

@eval begin
@doc """

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`$($f!)(result::Vector{$($T)}, X::Vector{$($T)}, c::$($T))`

Implements vector-scalar **subtraction** over **Vector{$($T)}** and $($T) and overwrites
the result vector with computed value. *Returns:* **Vector{$($T)}** `result`
""" ->
function ($f!)(result::Vector{$T}, X::Vector{$T}, c::$T)
ccall(($(string("vDSP_vsadd", suff), libacc)), Cvoid,
(Ptr{$T}, Int64, Ptr{$T}, Ptr{$T}, Int64, UInt64),
X, 1, Ref(-c), result, 1, length(result))
return result
end
end

@eval begin
@doc """

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`$($f)(X::Vector{$($T)}, c::$($T))`

Implements vector-scalar **subtraction** over **Vector{$($T)}** and $($T). Allocates
memory to store result. *Returns:* **Vector{$($T)}**
""" ->
function ($f)(X::Vector{$T}, c::$T)
result = similar(X)
($f!)(result, X, c)
return result
end
end

f = :svsub
f! = Symbol("$(f)!")

@eval begin
@doc """

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`$($f!)(result::Vector{$($T)}, X::Vector{$($T)}, c::$($T))`

Implements vector-scalar **subtraction** over $($T) and **Vector{$($T)}** and overwrites
the result vector with computed value. *Returns:* **Vector{$($T)}** `result`
""" ->
function ($f!)(result::Vector{$T}, X::Vector{$T}, c::$T)
ccall(($(string("vDSP_vsadd", suff), libacc)), Cvoid,
(Ptr{$T}, Int64, Ptr{$T}, Ptr{$T}, Int64, UInt64),
-X, 1, Ref(c), result, 1, length(result))
return result
end
end

@eval begin
@doc """

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`$($f)(X::Vector{$($T), c::$($T)})`

Implements vector-scalar **subtraction** over $($T) and **Vector{$($T)}**. Allocates
memory to store result. *Returns:* **Vector{$($T)}**
""" ->
function ($f)(X::Vector{$T}, c::$T)
result = similar(X)
($f!)(result, X, c)
return result
end
end

for f in (:vsadd, :vssub, :vsdiv, :vsmul)
f! = Symbol("$(f)!")
@eval begin
# Broadcasting override such that f.(X) turns into f(X)
Base.copy(bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T, N},$T}}) where {Style, Axes, N} = ($f)(bc.args...)
Base.copyto!(dest::Array{$T, N}, bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T,N},$T}}) where {Style, Axes, N} = ($f!)(dest, bc.args...)

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Base.broadcasted(::typeof($f), arg1::Union{Array{$T, N},Base.Broadcast.Broadcasted}, arg2::$T) where {N} = ($f)(maybecopy(arg1), arg2)
end
end

f = :svsub
f! = Symbol("$(f)!")

@eval begin
# Broadcasting override such that f.(X) turns into f(X)
Base.copy(bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T, N}, $T}}) where {Style, Axes, N} = ($f)(bc.args...)
Base.copyto!(dest::Array{$T, N}, bc::Base.Broadcast.Broadcasted{Style, Axes, typeof($f), Tuple{Array{$T,N}, $T}}) where {Style, Axes, N} = ($f!)(dest, bc.args...)

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Base.broadcasted(::typeof($f), arg1::Union{Array{$T, N},Base.Broadcast.Broadcasted}, arg2::$T) where {N} = ($f)(maybecopy(arg1), arg2)
end
end

22 changes: 21 additions & 1 deletion src/Util.jl
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Expand Up @@ -2,6 +2,13 @@

tupletypelength(a)=length(a.parameters)

@inline maybecopy(x::T) where {T <: Base.Broadcast.Broadcasted} = copy(x)
@inline maybecopy(x::T) where {T <: Array} = x

const OPS = Dict{Symbol,Tuple{Symbol, Symbol, Symbol}}(:+ => (:vadd, :vsadd, :vsadd),
:- => (:vsub, :vssub, :svsub),
:* => (:vadd, :vsmul, :vsmul),
:/ => (:vadd, :vsdiv, :vsdiv),)

macro replaceBase(fs...)
b = Expr(:block)
Expand All @@ -28,16 +35,29 @@
e = quote
(Base.$f)(X::Array{T}) where {T <: Union{Float64,Float32}} = ($fa)(X)
(Base.$f)(X::Union{Float64,Float32}) = ($fa)([X])[1]
Base.broadcasted(::typeof(Base.$f), arg::Union{Array{F,N},Base.Broadcast.Broadcasted}) where {N,F<:Union{Float32,Float64}} = ($fa)(maybecopy(arg))

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end
arg_consumed = true
end
if fa in (:copysign,:atan,:pow,:rem,:div_float, :vadd, :vsub, :vmul)
if fa in (:copysign,:atan,:pow,:rem)
e = quote
(Base.$f)(X::Array{T},Y::Array{T}) where {T <: Union{Float32,Float64}} = ($fa)(X,Y)
(Base.$f)(X::T,Y::T) where {T <: Union{Float32,Float64}} = ($fa)([X],[Y])[1]
Base.broadcasted(::typeof(Base.$f), arg1::Union{Array{F, N},Base.Broadcast.Broadcasted}, arg2::Union{Array{F, N},Base.Broadcast.Broadcasted}) where {N,F<:Union{Float32,Float64}} = ($fa)(maybecopy(arg1), maybecopy(arg2))

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end
arg_consumed = true
end
if f in (:+,:-,:*,:/)
e = quote
(Base.$f)(X::Array{T},Y::Array{T}) where {T <: Union{Float32,Float64}} = ($(OPS[f][1]))(X,Y)
(Base.$f)(X::T,Y::T) where {T <: Union{Float32,Float64}} = ($(OPS[f][1]))([X],[Y])[1]
Base.broadcasted(::typeof(Base.$f), arg1::Union{Array{F, N},Base.Broadcast.Broadcasted}, arg2::Union{Array{F, N},Base.Broadcast.Broadcasted}) where {N,F<:Union{Float32,Float64}} = ($(OPS[f][1]))(maybecopy(arg1), maybecopy(arg2))

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Base.broadcasted(::typeof(Base.$f), arg1::Union{Array{T, N},Base.Broadcast.Broadcasted}, arg2::T) where {N, T <: Union{Float32,Float64}} = ($(OPS[f][2]))(maybecopy(arg1), arg2)
Base.broadcasted(::typeof(Base.$f), arg1::T, arg2::Union{Array{T, N},Base.Broadcast.Broadcasted}) where {N, T <: Union{Float32,Float64}} = ($(OPS[f][3]))(maybecopy(arg2), arg1)

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end
arg_consumed = true
end
if !arg_consumed
error("Function $f not defined by AppleAccelerate.jl")
end
Expand Down
73 changes: 69 additions & 4 deletions test/runtests.jl
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Expand Up @@ -10,14 +10,62 @@ end
Random.seed!(7)
N = 1_000

@testset "AppleAccelerate.jl" begin
for T in (Float32, Float64)
@testset "Element-wise Operators::$T" begin
X::Vector{T} = randn(N)
Y::Vector{T} = randn(N)
Z::Vector{T} = similar(X)
# Vector-vector
@test (X .+ Y) ≈ AppleAccelerate.vadd(X, Y)
@test (X .- Y) ≈ AppleAccelerate.vsub(X, Y)
@test (X .* Y) ≈ AppleAccelerate.vmul(X, Y)
@test (X ./ Y) ≈ AppleAccelerate.vdiv(X, Y)

# Vector-vector non-allocating
AppleAccelerate.vadd!(Z, X, Y)
@test (X .+ Y) ≈ Z
AppleAccelerate.vsub!(Z, X, Y)
@test (X .- Y) ≈ Z
AppleAccelerate.vmul!(Z, X, Y)
@test (X .* Y) ≈ Z
AppleAccelerate.vdiv!(Z, X, Y)
@test (X ./ Y) ≈ Z

# Vector-vector broadcasting
@test (X .+ Y) ≈ AppleAccelerate.vadd.(X, Y)
@test (X .- Y) ≈ AppleAccelerate.vsub.(X, Y)
@test (X .* Y) ≈ AppleAccelerate.vmul.(X, Y)
@test (X ./ Y) ≈ AppleAccelerate.vdiv.(X, Y)

#Vector-scalar
c::T = randn()
@test (X .+ c) ≈ AppleAccelerate.vsadd.(X, c)
@test (X .- c) ≈ AppleAccelerate.vssub.(X, c)
@test (c .- X) ≈ AppleAccelerate.svsub.(X, c)
@test (X .* c) ≈ AppleAccelerate.vsmul.(X, c)
@test (X ./ c) ≈ AppleAccelerate.vsdiv.(X, c)

#Vector-scalar non-allocating
AppleAccelerate.vsadd!(Y, X, c)
@test (X .+ c) ≈ Y
AppleAccelerate.vssub!(Y, X, c)
@test (X .- c) ≈ Y
AppleAccelerate.svsub!(Y, X, c)
@test (c .- X) ≈ Y
AppleAccelerate.vsmul!(Y, X, c)
@test (X .* c) ≈ Y
AppleAccelerate.vsdiv!(Y, X, c)
@test (X ./ c) ≈ Y

#Vector-scalar broadcasting
@test (X .+ c) ≈ AppleAccelerate.vsadd.(X, c)
@test (X .- c) ≈ AppleAccelerate.vssub.(X, c)
@test (c .- X) ≈ AppleAccelerate.svsub.(X, c)
@test (X .* c) ≈ AppleAccelerate.vsmul.(X, c)
@test (X ./ c) ≈ AppleAccelerate.vsdiv.(X, c)

@test (X .+ Y .+ Y) ≈ AppleAccelerate.vadd.(X, Y .+ Y)
end
end

Expand Down Expand Up @@ -198,12 +246,28 @@ for T in (Float32, Float64)
@test fa(X)[2] ≈ fb(X)[2]
end

@testset "Testing meanmag::$T" begin
@test AppleAccelerate.meanmag(X) ≈ mean(abs, X)
end

@testset "Testing meansqr::$T" begin
@test AppleAccelerate.meansqr(X) ≈ mean(X .*X)
@test AppleAccelerate.meansqr(X) ≈ mean(X .* X)
end

@testset "Testing meanmag::$T" begin
@test AppleAccelerate.meanmag(X) ≈ mean(abs.(X))
@testset "Testing meanssqr::$T" begin
@test AppleAccelerate.meanssqr(X) ≈ mean(X .* abs.(X))
end

@testset "Testing summag::$T" begin
@test AppleAccelerate.summag(X) ≈ sum(abs, X)
end

@testset "Testing sumsqr::$T" begin
@test AppleAccelerate.sumsqr(X) ≈ sum(abs2, X)
end

@testset "Testing sumssqr::$T" begin
@test AppleAccelerate.sumssqr(X) ≈ sum(X .* abs.(X))
end

end
Expand Down Expand Up @@ -270,6 +334,7 @@ Y::Array{T} = abs.(randn(N))
@test X ./ Y == AppleAccelerate.div_float(X, Y)
end
=#
end

if AppleAccelerate.get_macos_version() < v"13.3"
@info("AppleAccelerate.jl needs macOS >= 13.3 for BLAS forwarding. Not testing forwarding capabilities.")
Expand Down Expand Up @@ -338,6 +403,6 @@ end
end

run(`$(Base.julia_cmd()) --project=$(Base.active_project()) $(dir)/runtests.jl LinearAlgebra/blas LinearAlgebra/lapack`)
end;
end;
end

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