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Merge pull request #1092 from apkille/ca
Add support for using non-AbstractArrays with OrdinaryDiffEq and Zygote
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using OrdinaryDiffEq, RecursiveArrayTools, LinearAlgebra | ||
using Zygote, SciMLSensitivity, Random, Test | ||
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struct CustomArray{T, N} | ||
x::Array{T, N} | ||
end | ||
Base.size(x::CustomArray) = size(x.x) | ||
Base.axes(x::CustomArray) = axes(x.x) | ||
Base.ndims(x::CustomArray) = ndims(x.x) | ||
Base.ndims(::Type{<:CustomArray{T,N}}) where {T,N} = N | ||
Base.zero(x::CustomArray) = CustomArray(zero(x.x)) | ||
Base.zero(::Type{<:CustomArray{T,N}}) where {T,N} = CustomArray(zero(Array{T,N})) | ||
Base.similar(x::CustomArray, dims::Union{Integer, AbstractUnitRange}...) = CustomArray(similar(x.x, dims...)) | ||
Base.copyto!(x::CustomArray, y::CustomArray) = CustomArray(copyto!(x.x, y.x)) | ||
Base.copy(x::CustomArray) = CustomArray(copy(x.x)) | ||
Base.length(x::CustomArray) = length(x.x) | ||
Base.isempty(x::CustomArray) = isempty(x.x) | ||
Base.eltype(x::CustomArray) = eltype(x.x) | ||
Base.zero(x::CustomArray) = CustomArray(zero(x.x)) | ||
Base.fill!(x::CustomArray, y) = CustomArray(fill!(x.x, y)) | ||
Base.getindex(x::CustomArray, i) = getindex(x.x, i) | ||
Base.setindex!(x::CustomArray, v, idx) = setindex!(x.x, v, idx) | ||
Base.firstindex(x::CustomArray) = firstindex(x.x) | ||
Base.lastindex(x::CustomArray) = lastindex(x.x) | ||
Base.eachindex(x::CustomArray) = eachindex(x.x) | ||
Base.mapreduce(f, op, x::CustomArray; kwargs...) = mapreduce(f, op, x.x; kwargs...) | ||
Base.any(f::Function, x::CustomArray; kwargs...) = any(f, x.x; kwargs...) | ||
Base.all(f::Function, x::CustomArray; kwargs...) = all(f, x.x; kwargs...) | ||
Base.similar(x::CustomArray, t) = CustomArray(similar(x.x, t)) | ||
Base.:(+)(x::CustomArray, y::CustomArray) = CustomArray(x.x + y.x) | ||
Base.:(==)(x::CustomArray, y::CustomArray) = x.x == y.x | ||
Base.:(*)(x::Number, y::CustomArray) = CustomArray(x*y.x) | ||
Base.:(/)(x::CustomArray, y::Number) = CustomArray(x.x/y) | ||
LinearAlgebra.norm(x::CustomArray) = norm(x.x) | ||
LinearAlgebra.vec(x::CustomArray) = CustomArray(vec(x.x)) | ||
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struct CustomStyle{N} <: Broadcast.BroadcastStyle where {N} end | ||
CustomStyle(::Val{N}) where N = CustomStyle{N}() | ||
CustomStyle{M}(::Val{N}) where {N,M} = NoIndexStyle{N}() | ||
Base.BroadcastStyle(::Type{<:CustomArray{T,N}}) where {T,N} = CustomStyle{N}() | ||
Broadcast.BroadcastStyle(::CustomStyle{N}, ::Broadcast.DefaultArrayStyle{0}) where {N} = CustomStyle{N}() | ||
Base.similar(bc::Base.Broadcast.Broadcasted{CustomStyle{N}}, ::Type{ElType}) where {N, ElType} = CustomArray(similar(Array{ElType, N}, axes(bc))) | ||
Base.@propagate_inbounds Base.Broadcast._broadcast_getindex(x::CustomArray, i) = x.x[i] | ||
Base.Broadcast.extrude(x::CustomArray) = x | ||
Base.Broadcast.broadcastable(x::CustomArray) = x | ||
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@inline function Base.copyto!(dest::CustomArray, bc::Base.Broadcast.Broadcasted{<:Union{Base.Broadcast.AbstractArrayStyle,CustomStyle}}) | ||
axes(dest) == axes(bc) || throwdm(axes(dest), axes(bc)) | ||
bc′ = Base.Broadcast.preprocess(dest, bc) | ||
dest′ = dest.x | ||
@simd for I in 1:length(dest′) | ||
@inbounds dest′[I] = bc′[I] | ||
end | ||
return dest | ||
end | ||
@inline function Base.copy(bc::Base.Broadcast.Broadcasted{<:CustomStyle}) | ||
bcf = Broadcast.flatten(bc) | ||
x = find_x(bcf) | ||
data = similar(x, eltype(bcf[1])) | ||
@inbounds @simd for I in 1:length(x) | ||
data[I] = bcf[I] | ||
end | ||
return CustomArray(data) | ||
end | ||
find_x(bc::Broadcast.Broadcasted) = find_x(bc.args) | ||
find_x(args::Tuple) = find_x(find_x(args[1]), Base.tail(args)) | ||
find_x(x) = x | ||
find_x(::Any, rest) = find_x(rest) | ||
find_x(x::CustomArray, rest) = x.x | ||
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RecursiveArrayTools.recursive_unitless_bottom_eltype(x::CustomArray) = eltype(x) | ||
RecursiveArrayTools.recursivecopy!(dest::CustomArray, src::CustomArray) = copyto!(dest, src) | ||
RecursiveArrayTools.recursivecopy(x::CustomArray) = copy(x) | ||
RecursiveArrayTools.recursivefill!(x::CustomArray, a) = fill!(x, a) | ||
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Base.show_vector(io::IO, x::CustomArray) = Base.show_vector(io, x.x) | ||
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Base.show(io::IO, x::CustomArray) = (print(io, "CustomArray");show(io, x.x)) | ||
function Base.show(io::IO, ::MIME"text/plain", x::CustomArray) | ||
println(io, Base.summary(x), ":") | ||
Base.print_array(io, x.x) | ||
end | ||
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ca0 = CustomArray(ones(2)) | ||
tspan = (0.0, 1.0) | ||
par = [rand(), rand()] | ||
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algs = [Tsit5(), BS3(), Vern9(), DP5()] | ||
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for alg in algs | ||
function cost(p) | ||
prob = ODEProblem((du, u, p, t) -> (du[1] = p[1]*u[1] + p[2]*u[2]; du[2] = p[2]*u[1]), ca0, tspan, p) | ||
sol = solve(prob, alg; save_everystep = false) | ||
return 1 - norm(sol[end])^2 | ||
end | ||
@test_nowarn Zygote.gradient(cost, par) | ||
end |