V0.1.2 (#9)

* add keyword arguments in frule (#8) * Update ForwardDiffChainRules.jl add keyword arguments in frule * Update runtests.jl update kwargs test * Update src/ForwardDiffChainRules.jl Co-authored-by: Mohamed Tarek <[email protected]> * Update runtests.jl keywords should have default values Co-authored-by: ThummeTo <[email protected]> Co-authored-by: Mohamed Tarek <[email protected]> * updated test (keyword argeuments) * rm derivative along keyword Co-authored-by: Xiaoming Fu <[email protected]> Co-authored-by: Mohamed Tarek <[email protected]>
ThummeTo · Dec 12, 2022 · 1ee1f68 · 1ee1f68 · ThummeTo · Dec 12, 2022
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Showing 3 changed files with 8 additions and 8 deletions.
diff --git a/Project.toml b/Project.toml
@@ -1,7 +1,7 @@
 name = "ForwardDiffChainRules"
 uuid = "c9556dd2-1aed-4cfe-8560-1557cf593001"
 authors = ["MT <[email protected]>", "TT <[email protected]>"]
-version = "0.1.1"
+version = "0.1.2"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

diff --git a/src/ForwardDiffChainRules.jl b/src/ForwardDiffChainRules.jl
@@ -66,7 +66,7 @@ function _fd_frule(sig)
             flat_ypartials1, _ = ForwardDiffChainRules.DifferentiableFlatten.flatten(ypartials1)
             flat_ypartials = hcat(reshape(flat_ypartials1, :, 1), ntuple(Val(CS - 1)) do i
                 xpartialsi = unflattenx(flat_xpartials[:, i+1])
-                _, ypartialsi = ChainRulesCore.frule((NoTangent(), xpartialsi...), f, xprimals...)
+                _, ypartialsi = ChainRulesCore.frule((NoTangent(), xpartialsi...), f, xprimals...; ks...)
                 return ForwardDiffChainRules.DifferentiableFlatten.flatten(ypartialsi)[1]
             end...)
 

diff --git a/test/runtests.jl b/test/runtests.jl
@@ -169,15 +169,15 @@ SOFTWARE.
         @test norm(g - I) < 1e-6
     end
     @testset "kwargs" begin
-        fkwarg(x; a = 2.0) = x * a
+        fkwarg(x1, x2; a = 2.0) = x1 * x2 * a
         frule_count = 0
-        function ChainRulesCore.frule((_, Δx), ::typeof(fkwarg), x::Real; a = 2.0)
+        function ChainRulesCore.frule((_, Δx1, Δx2), ::typeof(fkwarg), x1::Real, x2::Real; a)
             global frule_count += 1
             println("frule was called")
-            return fkwarg(x; a), a * Δx
+            return fkwarg(x1, x2; a), a * x2 * Δx1 + a * x1 * Δx2
         end
-        @ForwardDiff_frule fkwarg(x::ForwardDiff.Dual; kwargs...)
-        @test ForwardDiff.derivative(x -> fkwarg(x, a = 3.0), 2.0) == 3
-        @test frule_count == 1
+        @ForwardDiff_frule fkwarg(x1::ForwardDiff.Dual, x2::ForwardDiff.Dual; kwargs...)
+        @test ForwardDiff.gradient(x -> fkwarg(x[1], x[2], a = 3.0), [1.0, 2.0]) == [6, 3]
+        @test frule_count == 2
     end
 end