Changelog

Author: gdalle

DifferentiationInterface/CHANGELOG.md

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

DifferentiationInterface/test/Back/FiniteDiff/test.jl

@@ -76,13 +76,13 @@ end;
 @testset "Step size" begin  # fix 811
     backend = AutoFiniteDiff(; absstep=1000, relstep=0.1)
     preps = [
-        prepare_pushforward(identity, backend, 1.0, (1.0,))
-        prepare_pushforward(copyto!, [0.0], backend, [1.0], ([1.0],))
-        prepare_derivative(identity, backend, 1.0)
-        prepare_derivative((y, x) -> y .= x, [0.0], backend, 1.0)
-        prepare_gradient(sum, backend, [1.0])
-        prepare_jacobian(identity, backend, [1.0])
-        prepare_jacobian(copyto!, [0.0], backend, [1.0])
+        prepare_pushforward(identity, backend, 1.0, (1.0,)),
+        prepare_pushforward(copyto!, [0.0], backend, [1.0], ([1.0],)),
+        prepare_derivative(identity, backend, 1.0),
+        prepare_derivative((y, x) -> y .= x, [0.0], backend, 1.0),
+        prepare_gradient(sum, backend, [1.0]),
+        prepare_jacobian(identity, backend, [1.0]),
+        prepare_jacobian(copyto!, [0.0], backend, [1.0]),
     ]
     for prep in preps
         @test prep.relstep == 0.1
@@ -96,13 +96,13 @@ end;
 
     backend = AutoFiniteDiff(; relstep=0.1)
     preps = [
-        prepare_pushforward(identity, backend, 1.0, (1.0,))
-        prepare_pushforward(copyto!, [0.0], backend, [1.0], ([1.0],))
-        prepare_derivative(identity, backend, 1.0)
-        prepare_derivative((y, x) -> y .= x, [0.0], backend, 1.0)
-        prepare_gradient(sum, backend, [1.0])
-        prepare_jacobian(identity, backend, [1.0])
-        prepare_jacobian(copyto!, [0.0], backend, [1.0])
+        prepare_pushforward(identity, backend, 1.0, (1.0,)),
+        prepare_pushforward(copyto!, [0.0], backend, [1.0], ([1.0],)),
+        prepare_derivative(identity, backend, 1.0),
+        prepare_derivative((y, x) -> y .= x, [0.0], backend, 1.0),
+        prepare_gradient(sum, backend, [1.0]),
+        prepare_jacobian(identity, backend, [1.0]),
+        prepare_jacobian(copyto!, [0.0], backend, [1.0]),
     ]
     for prep in preps
         @test prep.relstep == 0.1