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fix: fix usage of ReverseDiff in parameters #1078

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merged 5 commits into from
Sep 4, 2024
Merged

fix: fix usage of ReverseDiff in parameters #1078

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b24a59e
fix: fix `anyeltypedual` for `ReverseDiff.TrackedArray`
AayushSabharwal Sep 3, 2024
036c669
feat: use tunable portion of parameter object in `promote_u0`
AayushSabharwal Sep 3, 2024
b818689
fix: recursively descend `anyeltypedual` for `TrackedArray`
AayushSabharwal Sep 3, 2024
eb42bc2
fix: fix promote_u0 when `p isa TrackedArray` and `u0` is not
AayushSabharwal Sep 3, 2024
4e60a87
test: add tests for ReverseDiff dual detection and promotion
AayushSabharwal Sep 3, 2024
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2 changes: 2 additions & 0 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -27,6 +27,7 @@ RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
SciMLOperators = "c0aeaf25-5076-4817-a8d5-81caf7dfa961"
SciMLStructures = "53ae85a6-f571-4167-b2af-e1d143709226"
Setfield = "efcf1570-3423-57d1-acb7-fd33fddbac46"
Static = "aedffcd0-7271-4cad-89d0-dc628f76c6d3"
StaticArraysCore = "1e83bf80-4336-4d27-bf5d-d5a4f845583c"
Expand Down Expand Up @@ -95,6 +96,7 @@ Reexport = "1.0"
ReverseDiff = "1"
SciMLBase = "2.28.0"
SciMLOperators = "0.3"
SciMLStructures = "1.5"
Setfield = "1"
SparseArrays = "1.9"
Static = "1"
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4 changes: 4 additions & 0 deletions ext/DiffEqBaseReverseDiffExt.jl
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Expand Up @@ -5,6 +5,10 @@ import DiffEqBase: value
import ReverseDiff
import DiffEqBase.ArrayInterface

function DiffEqBase.anyeltypedual(::Type{T}, ::Type{Val{counter}} = Val{0}) where {counter} where {V, D, N, VA, DA, T <: ReverseDiff.TrackedArray{V, D, N, VA, DA}}
DiffEqBase.anyeltypedual(V, Val{counter})
end

DiffEqBase.value(x::Type{ReverseDiff.TrackedReal{V, D, O}}) where {V, D, O} = V
function DiffEqBase.value(x::Type{
ReverseDiff.TrackedArray{V, D, N, VA, DA},
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2 changes: 2 additions & 0 deletions src/DiffEqBase.jl
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Expand Up @@ -101,6 +101,8 @@ import SciMLBase: solve, init, step!, solve!, __init, __solve, update_coefficien

import SciMLBase: AbstractDiffEqLinearOperator # deprecation path

import SciMLStructures

import Tricks

using Reexport
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12 changes: 12 additions & 0 deletions src/forwarddiff.jl
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Expand Up @@ -352,6 +352,12 @@ DiffEqBase.anyeltypedual(f::SciMLBase.AbstractSciMLFunction, ::Type{Val{counter}
@inline promote_u0(::Nothing, p, t0) = nothing

@inline function promote_u0(u0, p, t0)
if SciMLStructures.isscimlstructure(p)
_p = SciMLStructures.canonicalize(SciMLStructures.Tunable(), p)[1]
if _p != p
return promote_u0(u0, _p, t0)
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won't you need to restructure or replace! with this?

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No, we're not changing p. canonicalize is only used to get the tunables array, since that's what we want to dispatch off of.

end
end
Tu = eltype(u0)
if Tu <: ForwardDiff.Dual
return u0
Expand All @@ -373,6 +379,12 @@ DiffEqBase.anyeltypedual(f::SciMLBase.AbstractSciMLFunction, ::Type{Val{counter}
end

@inline function promote_u0(u0::AbstractArray{<:Complex}, p, t0)
if SciMLStructures.isscimlstructure(p)
_p = SciMLStructures.canonicalize(SciMLStructures.Tunable(), p)[1]
if _p != p
return promote_u0(u0, _p, t0)
end
end
Tu = real(eltype(u0))
if Tu <: ForwardDiff.Dual
return u0
Expand Down
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