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ChrisRackauckasChrisRackauckas
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Merge pull request SciML#1197 from jClugstor/move_to_SciMLBase
Move utilities to SciMLBase
2 parents 89c4664 + f845a85 commit f9157be

16 files changed

+59
-1374
lines changed

‎Project.toml‎

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@@ -51,7 +51,6 @@ Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
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[extensions]
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DiffEqBaseCUDAExt = "CUDA"
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DiffEqBaseChainRulesCoreExt = "ChainRulesCore"
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DiffEqBaseDistributionsExt = "Distributions"
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DiffEqBaseEnzymeExt = ["ChainRulesCore", "Enzyme"]
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DiffEqBaseForwardDiffExt = ["ForwardDiff"]
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DiffEqBaseGTPSAExt = "GTPSA"

‎ext/DiffEqBaseDistributionsExt.jl‎

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‎ext/DiffEqBaseForwardDiffExt.jl‎

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‎ext/DiffEqBaseGTPSAExt.jl‎

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@@ -1,7 +1,8 @@
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module DiffEqBaseGTPSAExt
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using DiffEqBase
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import DiffEqBase: value, ODE_DEFAULT_NORM
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import DiffEqBase: ODE_DEFAULT_NORM
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import SciMLBase: value, unitfulvalue
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using GTPSA
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value(x::TPS) = scalar(x)

‎ext/DiffEqBaseMeasurementsExt.jl‎

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@@ -4,18 +4,6 @@ using DiffEqBase
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import DiffEqBase: value
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using Measurements
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function DiffEqBase.promote_u0(u0::AbstractArray{<:Measurements.Measurement},
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p::AbstractArray{<:Measurements.Measurement}, t0)
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u0
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end
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DiffEqBase.promote_u0(u0, p::AbstractArray{<:Measurements.Measurement}, t0) = eltype(p).(u0)
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value(x::Type{Measurements.Measurement{T}}) where {T} = T
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value(x::Measurements.Measurement) = Measurements.value(x)
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unitfulvalue(x::Type{Measurements.Measurement{T}}) where {T} = T
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unitfulvalue(x::Measurements.Measurement) = Measurements.value(x)
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# Support adaptive steps should be errorless
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@inline function DiffEqBase.ODE_DEFAULT_NORM(
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u::AbstractArray{

‎ext/DiffEqBaseMonteCarloMeasurementsExt.jl‎

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@@ -4,34 +4,6 @@ using DiffEqBase
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import DiffEqBase: value
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using MonteCarloMeasurements
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function DiffEqBase.promote_u0(
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u0::AbstractArray{
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<:MonteCarloMeasurements.AbstractParticles,
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},
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p::AbstractArray{<:MonteCarloMeasurements.AbstractParticles},
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t0)
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u0
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end
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function DiffEqBase.promote_u0(u0,
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p::AbstractArray{<:MonteCarloMeasurements.AbstractParticles},
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t0)
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eltype(p).(u0)
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end
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function DiffEqBase.promote_u0(::Nothing,
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p::AbstractArray{<:MonteCarloMeasurements.AbstractParticles},
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t0)
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return nothing
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end
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DiffEqBase.value(x::Type{MonteCarloMeasurements.AbstractParticles{T, N}}) where {T, N} = T
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DiffEqBase.value(x::MonteCarloMeasurements.AbstractParticles) = mean(x.particles)
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function DiffEqBase.unitfulvalue(x::Type{MonteCarloMeasurements.AbstractParticles{
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T, N}}) where {T, N}
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T
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end
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DiffEqBase.unitfulvalue(x::MonteCarloMeasurements.AbstractParticles) = mean(x.particles)
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# Support adaptive steps should be errorless
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@inline function DiffEqBase.ODE_DEFAULT_NORM(
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u::AbstractArray{

‎ext/DiffEqBaseMooncakeExt.jl‎

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@@ -29,18 +29,4 @@ import Mooncake: rrule!!, CoDual, zero_fcodual, @is_primitive,
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},
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true,)
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@zero_adjoint MinimalCtx Tuple{typeof(DiffEqBase.numargs), Any}
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@is_primitive MinimalCtx Tuple{
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typeof(DiffEqBase.set_mooncakeoriginator_if_mooncake), SciMLBase.ChainRulesOriginator
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}
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@mooncake_overlay DiffEqBase.set_mooncakeoriginator_if_mooncake(x::SciMLBase.ADOriginator) = SciMLBase.MooncakeOriginator()
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function rrule!!(
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f::CoDual{typeof(DiffEqBase.set_mooncakeoriginator_if_mooncake)},
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X::CoDual{SciMLBase.ChainRulesOriginator}
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)
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return zero_fcodual(SciMLBase.MooncakeOriginator()), NoPullback(f, X)
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end
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end

‎ext/DiffEqBaseReverseDiffExt.jl‎

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@@ -5,57 +5,6 @@ import DiffEqBase: value
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import ReverseDiff
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import DiffEqBase.ArrayInterface
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function DiffEqBase.anyeltypedual(::Type{T},
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::Type{Val{counter}} = Val{0}) where {counter} where {
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V, D, N, VA, DA, T <: ReverseDiff.TrackedArray{V, D, N, VA, DA}}
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DiffEqBase.anyeltypedual(V, Val{counter})
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end
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DiffEqBase.value(x::Type{ReverseDiff.TrackedReal{V, D, O}}) where {V, D, O} = V
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function DiffEqBase.value(x::Type{
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ReverseDiff.TrackedArray{V, D, N, VA, DA},
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}) where {V, D,
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N, VA,
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DA}
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Array{V, N}
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end
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DiffEqBase.value(x::ReverseDiff.TrackedReal) = x.value
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DiffEqBase.value(x::ReverseDiff.TrackedArray) = x.value
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DiffEqBase.unitfulvalue(x::Type{ReverseDiff.TrackedReal{V, D, O}}) where {V, D, O} = V
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function DiffEqBase.unitfulvalue(x::Type{
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ReverseDiff.TrackedArray{V, D, N, VA, DA},
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}) where {V, D,
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N, VA,
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DA}
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Array{V, N}
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end
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DiffEqBase.unitfulvalue(x::ReverseDiff.TrackedReal) = x.value
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DiffEqBase.unitfulvalue(x::ReverseDiff.TrackedArray) = x.value
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# Force TrackedArray from TrackedReal when reshaping W\b
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DiffEqBase._reshape(v::AbstractVector{<:ReverseDiff.TrackedReal}, siz) = reduce(vcat, v)
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DiffEqBase.promote_u0(u0::ReverseDiff.TrackedArray, p::ReverseDiff.TrackedArray, t0) = u0
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function DiffEqBase.promote_u0(u0::AbstractArray{<:ReverseDiff.TrackedReal},
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p::ReverseDiff.TrackedArray, t0)
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u0
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end
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function DiffEqBase.promote_u0(u0::ReverseDiff.TrackedArray,
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p::AbstractArray{<:ReverseDiff.TrackedReal}, t0)
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u0
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end
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function DiffEqBase.promote_u0(u0::AbstractArray{<:ReverseDiff.TrackedReal},
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p::AbstractArray{<:ReverseDiff.TrackedReal}, t0)
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u0
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end
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DiffEqBase.promote_u0(u0, p::ReverseDiff.TrackedArray, t0) = ReverseDiff.track(u0)
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function DiffEqBase.promote_u0(
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u0, p::ReverseDiff.TrackedArray{T}, t0) where {T <: ReverseDiff.ForwardDiff.Dual}
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ReverseDiff.track(T.(u0))
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end
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DiffEqBase.promote_u0(u0, p::AbstractArray{<:ReverseDiff.TrackedReal}, t0) = eltype(p).(u0)
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# Support adaptive with non-tracked time
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@inline function DiffEqBase.ODE_DEFAULT_NORM(u::ReverseDiff.TrackedArray, t)
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sqrt(sum(abs2, DiffEqBase.value(u)) / length(u))

‎ext/DiffEqBaseTrackerExt.jl‎

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@@ -4,36 +4,6 @@ using DiffEqBase
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import DiffEqBase: value
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import Tracker
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DiffEqBase.value(x::Type{Tracker.TrackedReal{T}}) where {T} = T
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DiffEqBase.value(x::Type{Tracker.TrackedArray{T, N, A}}) where {T, N, A} = Array{T, N}
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DiffEqBase.value(x::Tracker.TrackedReal) = x.data
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DiffEqBase.value(x::Tracker.TrackedArray) = x.data
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DiffEqBase.unitfulvalue(x::Type{Tracker.TrackedReal{T}}) where {T} = T
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function DiffEqBase.unitfulvalue(x::Type{Tracker.TrackedArray{T, N, A}}) where {T, N, A}
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Array{T, N}
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end
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DiffEqBase.unitfulvalue(x::Tracker.TrackedReal) = x.data
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DiffEqBase.unitfulvalue(x::Tracker.TrackedArray) = x.data
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DiffEqBase.promote_u0(u0::Tracker.TrackedArray, p::Tracker.TrackedArray, t0) = u0
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function DiffEqBase.promote_u0(u0::AbstractArray{<:Tracker.TrackedReal},
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p::Tracker.TrackedArray, t0)
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u0
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end
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function DiffEqBase.promote_u0(u0::Tracker.TrackedArray,
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p::AbstractArray{<:Tracker.TrackedReal}, t0)
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u0
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end
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function DiffEqBase.promote_u0(u0::AbstractArray{<:Tracker.TrackedReal},
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p::AbstractArray{<:Tracker.TrackedReal}, t0)
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u0
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end
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DiffEqBase.promote_u0(u0, p::Tracker.TrackedArray, t0) = Tracker.track(u0)
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DiffEqBase.promote_u0(u0, p::AbstractArray{<:Tracker.TrackedReal}, t0) = eltype(p).(u0)
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@inline Base.any(f::Function, x::Tracker.TrackedArray) = any(f, Tracker.data(x))
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# Support adaptive with non-tracked time
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@inline function DiffEqBase.ODE_DEFAULT_NORM(u::Tracker.TrackedArray, t)
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sqrt(sum(abs2, DiffEqBase.value(u)) / length(u))

‎ext/DiffEqBaseUnitfulExt.jl‎

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module DiffEqBaseUnitfulExt
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using DiffEqBase
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import DiffEqBase: value
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import SciMLBase: unitfulvalue, value
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using Unitful
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# Support adaptive errors should be errorless for exponentiation

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