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gdallegdalle
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fix: take absstep into account for FiniteDiff (#812)
* Add tests * Fix * Changelog
1 parent 272eeb5 commit 0124a0e

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Lines changed: 61 additions & 9 deletions

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‎DifferentiationInterface/CHANGELOG.md‎

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@@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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### Fixed
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- Take `absstep` into account for FiniteDiff ([#812])
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- Make basis work for `CuArray` ([#810])
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## [0.7.0]
@@ -39,6 +40,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
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[0.6.54]: https://github.com/JuliaDiff/DifferentiationInterface.jl/compare/DifferentiationInterface-v0.6.53...DifferentiationInterface-v0.6.54
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[0.6.53]: https://github.com/JuliaDiff/DifferentiationInterface.jl/compare/DifferentiationInterface-v0.6.52...DifferentiationInterface-v0.6.53
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[#812]: https://github.com/JuliaDiff/DifferentiationInterface.jl/pull/812
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[#810]: https://github.com/JuliaDiff/DifferentiationInterface.jl/pull/810
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[#799]: https://github.com/JuliaDiff/DifferentiationInterface.jl/pull/799
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[#795]: https://github.com/JuliaDiff/DifferentiationInterface.jl/pull/795

‎DifferentiationInterface/ext/DifferentiationInterfaceFiniteDiffExt/onearg.jl‎

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Original file line numberDiff line numberDiff line change
@@ -27,7 +27,7 @@ function DI.prepare_pushforward_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffOneArgPushforwardPrep(_sig, cache, relstep, absstep, dir)
@@ -144,7 +144,7 @@ function DI.prepare_derivative_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffOneArgDerivativePrep(_sig, cache, relstep, absstep, dir)
@@ -269,7 +269,7 @@ function DI.prepare_gradient_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffGradientPrep(_sig, cache, relstep, absstep, dir)
@@ -359,7 +359,7 @@ function DI.prepare_jacobian_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffOneArgJacobianPrep(_sig, cache, relstep, absstep, dir)
@@ -465,8 +465,16 @@ function DI.prepare_hessian_nokwarg(
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else
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backend.relstep
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end
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absstep_g = isnothing(backend.absstep) ? relstep_g : backend.absstep
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absstep_h = isnothing(backend.absstep) ? relstep_h : backend.absstep
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absstep_g = if isnothing(backend.absstep)
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relstep_g
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else
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backend.absstep
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end
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absstep_h = if isnothing(backend.absstep)
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relstep_h
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else
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backend.absstep
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end
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return FiniteDiffHessianPrep(
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_sig, gradient_cache, hessian_cache, relstep_g, absstep_g, relstep_h, absstep_h
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)

‎DifferentiationInterface/ext/DifferentiationInterfaceFiniteDiffExt/twoarg.jl‎

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Original file line numberDiff line numberDiff line change
@@ -31,7 +31,7 @@ function DI.prepare_pushforward_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffTwoArgPushforwardPrep(_sig, cache, relstep, absstep, dir)
@@ -175,7 +175,7 @@ function DI.prepare_derivative_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffTwoArgDerivativePrep(_sig, cache, relstep, absstep, dir)
@@ -295,7 +295,7 @@ function DI.prepare_jacobian_nokwarg(
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absstep = if isnothing(backend.absstep)
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relstep
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else
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backend.relstep
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backend.absstep
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end
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dir = backend.dir
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return FiniteDiffTwoArgJacobianPrep(_sig, cache, relstep, absstep, dir)

‎DifferentiationInterface/test/Back/FiniteDiff/test.jl‎

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@@ -72,3 +72,45 @@ end
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logging=LOGGING,
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)
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end;
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@testset "Step size" begin # fix 811
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backend = AutoFiniteDiff(; absstep=1000, relstep=0.1)
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preps = [
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prepare_pushforward(identity, backend, 1.0, (1.0,)),
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prepare_pushforward(copyto!, [0.0], backend, [1.0], ([1.0],)),
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prepare_derivative(identity, backend, 1.0),
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prepare_derivative((y, x) -> y .= x, [0.0], backend, 1.0),
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prepare_gradient(sum, backend, [1.0]),
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prepare_jacobian(identity, backend, [1.0]),
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prepare_jacobian(copyto!, [0.0], backend, [1.0]),
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]
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for prep in preps
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@test prep.relstep == 0.1
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@test prep.absstep == 1000
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end
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prep = prepare_hessian(sum, backend, [1.0])
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@test prep.absstep_g == 1000
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@test prep.absstep_h == 1000
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@test prep.relstep_g == 0.1
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@test prep.relstep_h == 0.1
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backend = AutoFiniteDiff(; relstep=0.1)
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preps = [
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prepare_pushforward(identity, backend, 1.0, (1.0,)),
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prepare_pushforward(copyto!, [0.0], backend, [1.0], ([1.0],)),
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prepare_derivative(identity, backend, 1.0),
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prepare_derivative((y, x) -> y .= x, [0.0], backend, 1.0),
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prepare_gradient(sum, backend, [1.0]),
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prepare_jacobian(identity, backend, [1.0]),
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prepare_jacobian(copyto!, [0.0], backend, [1.0]),
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]
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for prep in preps
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@test prep.relstep == 0.1
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@test prep.absstep == 0.1
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end
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prep = prepare_hessian(sum, backend, [1.0])
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@test prep.absstep_g == 0.1
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@test prep.absstep_h == 0.1
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@test prep.relstep_g == 0.1
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@test prep.relstep_h == 0.1
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end

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