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Remove extra derivative overloads #800

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Remove extra derivative overloads #800

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342b62a
Remove extra derivative overloads
ChrisRackauckas Jan 20, 2023
b0d8a99
Update src/DiffEqFlux.jl
ChrisRackauckas Jan 20, 2023
d275f57
fix project.toml
ChrisRackauckas Jan 20, 2023
1790189
remove forwarddiff
ChrisRackauckas Jan 20, 2023
b9bc7ab
Merge remote-tracking branch 'origin/derivative_overloads' into deriv…
ChrisRackauckas Jan 20, 2023
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4 changes: 0 additions & 4 deletions Project.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@ DiffEqBase = "2b5f629d-d688-5b77-993f-72d75c75574e"
Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
DistributionsAD = "ced4e74d-a319-5a8a-b0ac-84af2272839c"
Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c"
ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
Functors = "d9f16b24-f501-4c13-a1f2-28368ffc5196"
LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
Expand All @@ -28,7 +27,6 @@ SciMLBase = "0bca4576-84f4-4d90-8ffe-ffa030f20462"
SciMLSensitivity = "1ed8b502-d754-442c-8d5d-10ac956f44a1"
TerminalLoggers = "5d786b92-1e48-4d6f-9151-6b4477ca9bed"
Zygote = "e88e6eb3-aa80-5325-afca-941959d7151f"
ZygoteRules = "700de1a5-db45-46bc-99cf-38207098b444"

[compat]
Adapt = "3"
Expand All @@ -39,7 +37,6 @@ DiffEqBase = "6.41"
Distributions = "0.23, 0.24, 0.25"
DistributionsAD = "0.6"
Flux = "0.12, 0.13"
ForwardDiff = "0.10"
Functors = "0.4"
LoggingExtras = "0.4, 1"
Lux = "0.4"
Expand All @@ -50,5 +47,4 @@ SciMLBase = "1"
SciMLSensitivity = "7"
TerminalLoggers = "0.1"
Zygote = "0.5, 0.6"
ZygoteRules = "0.2"
julia = "1.5"
22 changes: 2 additions & 20 deletions src/DiffEqFlux.jl
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Expand Up @@ -2,9 +2,9 @@ module DiffEqFlux

using Adapt, Base.Iterators, ConsoleProgressMonitor, DataInterpolations,
DiffEqBase, Distributions, DistributionsAD,
ForwardDiff, LinearAlgebra, Lux,
LinearAlgebra, Lux,
Logging, LoggingExtras, Printf, ProgressLogging, Random, RecursiveArrayTools,
Reexport, SciMLBase, TerminalLoggers, Zygote, ZygoteRules
Reexport, SciMLBase, TerminalLoggers, Zygote

@reexport using SciMLSensitivity
@reexport using Flux
Expand All @@ -14,24 +14,6 @@ import ChainRulesCore

gpu_or_cpu(x) = Array

# ForwardDiff integration

ZygoteRules.@adjoint function ForwardDiff.Dual{T}(x, ẋ::Tuple) where {T}
@assert length(ẋ) == 1
ForwardDiff.Dual{T}(x, ẋ), ḋ -> (ḋ.partials[1], (ḋ.value,))
end

ZygoteRules.@adjoint ZygoteRules.literal_getproperty(d::ForwardDiff.Dual{T}, ::Val{:partials}) where {T} =
d.partials, ṗ -> (ForwardDiff.Dual{T}(ṗ[1], 0),)

ZygoteRules.@adjoint ZygoteRules.literal_getproperty(d::ForwardDiff.Dual{T}, ::Val{:value}) where {T} =
d.value, ẋ -> (ForwardDiff.Dual{T}(0, ẋ),)

ZygoteRules.@adjoint ZygoteRules.literal_getproperty(A::Tridiagonal, ::Val{:dl}) = A.dl, y -> Tridiagonal(dl, zeros(length(d)), zeros(length(du)),)
ZygoteRules.@adjoint ZygoteRules.literal_getproperty(A::Tridiagonal, ::Val{:d}) = A.d, y -> Tridiagonal(zeros(length(dl)), d, zeros(length(du)),)
ZygoteRules.@adjoint ZygoteRules.literal_getproperty(A::Tridiagonal, ::Val{:du}) = A.dl, y -> Tridiagonal(zeros(length(dl)), zeros(length(d), du),)
ZygoteRules.@adjoint Tridiagonal(dl, d, du) = Tridiagonal(dl, d, du), p̄ -> (diag(p̄[2:end, 1:end-1]), diag(p̄), diag(p̄[1:end-1, 2:end]))

include("ffjord.jl")
include("neural_de.jl")
include("spline_layer.jl")
Expand Down