Update to new API (#169)

* Update to new API:

* Fixed bound

* Update Project.toml

Co-Authored-By: Nick Robinson <[email protected]>

* Update Project.toml

* Update Project.toml

Co-Authored-By: Nick Robinson <[email protected]>

* Update Project.toml

Co-Authored-By: Nick Robinson <[email protected]>

* Bump

* Sort out version

* Require tests pass on 1.3

* Re-disable 1.3 because #149

* Oops

Co-authored-by: Nick Robinson <[email protected]>

Project.toml

@@ -1,6 +1,6 @@
 name = "ChainRules"
 uuid = "082447d4-558c-5d27-93f4-14fc19e9eca2"
-version = "0.3.4"
+version = "0.4.0"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
@@ -10,12 +10,12 @@ Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 
 [compat]
-ChainRulesCore = "0.6.1"
-ChainRulesTestUtils = "0.1.3"
-FiniteDifferences = "^0.7"
+ChainRulesCore = "0.7.0"
+ChainRulesTestUtils = "0.2"
+FiniteDifferences = "0.7"
 Reexport = "0.2"
 Requires = "0.5.2, 1"
-julia = "^1.0"
+julia = "1"
 
 [extras]
 ChainRulesTestUtils = "cdddcdb0-9152-4a09-a978-84456f9df70a"

src/rulesets/Base/base.jl

@@ -107,7 +107,7 @@
 
 # product rule requires special care for arguments where `mul` is non-commutative
 
-function frule(::typeof(*), x::Number, y::Number, _, Δx, Δy)
+function frule((_, Δx, Δy), ::typeof(*), x::Number, y::Number)
     # Optimized version of `Δx .* y .+ x .* Δy`. Also, it is potentially more
     # accurate on machines with FMA instructions, since there are only two
     # rounding operations, one in `muladd/fma` and the other in `*`.
@@ -122,7 +122,7 @@ function rrule(::typeof(*), x::Number, y::Number)
     return x * y, times_pullback
 end
 
-function frule(::typeof(identity), x, _, ẏ)
+function frule((_, ẏ), ::typeof(identity), x)
     return x, ẏ
 end
 

src/rulesets/Base/broadcast.jl

@@ -7,14 +7,14 @@ https://github.com/JuliaLang/julia/issues/22129.
 function _cast_diff(f, x)
     function element_rule(u)
         dself = Zero()
-        fu, du = frule(f, u, dself, One())
+        fu, du = frule((dself, One()), f, u)
         fu, extern(du)
     end
     results = broadcast(element_rule, x)
     return first.(results), last.(results)
 end
 
-function frule(::typeof(broadcast), f, x, _, Δf, Δx)
+function frule((_, Δf, Δx), ::typeof(broadcast), f, x)
     Ω, ∂x = _cast_diff(f, x)
     return Ω, Δx .* ∂x
 end

src/rulesets/Base/mapreduce.jl

@@ -50,7 +50,7 @@ end
 ##### `sum`
 #####
 
-function frule(::typeof(sum), x, _, ẋ)
+function frule((_, ẋ), ::typeof(sum), x)
     return sum(x), sum(ẋ)
 end
 

src/rulesets/LinearAlgebra/blas.jl

@@ -11,7 +11,7 @@ _zeros(x) = fill!(similar(x), zero(eltype(x)))
 ##### `BLAS.dot`
 #####
 
-frule(::typeof(BLAS.dot), x, y, Δself, Δx, Δy) = frule(dot, x, y, Δself, Δx, Δy)
+frule((Δself, Δx, Δy), ::typeof(BLAS.dot), x, y) = frule((Δself, Δx, Δy), dot, x, y)
 
 rrule(::typeof(BLAS.dot), x, y) = rrule(dot, x, y)
 
@@ -35,7 +35,7 @@ end
 ##### `BLAS.nrm2`
 #####
 
-function frule(::typeof(BLAS.nrm2), x, _, Δx)
+function frule((_, Δx), ::typeof(BLAS.nrm2), x)
     Ω = BLAS.nrm2(x)
     return Ω, sum(Δx .* @thunk(x * inv(Ω)))
 end
@@ -67,7 +67,7 @@ end
 ##### `BLAS.asum`
 #####
 
-function frule(::typeof(BLAS.asum), x, _, Δx)
+function frule((_, Δx), ::typeof(BLAS.asum), x)
     return BLAS.asum(x), sum(sign.(x) .* Δx)
 end
 

src/rulesets/LinearAlgebra/dense.jl

@@ -8,7 +8,7 @@ const SquareMatrix{T} = Union{Diagonal{T},AbstractTriangular{T}}
 ##### `dot`
 #####
 
-function frule(::typeof(dot), x, y, _, Δx, Δy)
+function frule((_, Δx, Δy), ::typeof(dot), x, y)
     return dot(x, y), sum(Δx .* y) + sum(x .* Δy)
 end
 
@@ -23,7 +23,7 @@ end
 ##### `inv`
 #####
 
-function frule(::typeof(inv), x::AbstractArray, _, Δx)
+function frule((_, Δx), ::typeof(inv), x::AbstractArray)
     Ω = inv(x)
     return Ω, -Ω * Δx * Ω
 end
@@ -40,7 +40,7 @@ end
 ##### `det`
 #####
 
-function frule(::typeof(det), x, _, ẋ)
+function frule((_, ẋ), ::typeof(det), x)
     Ω = det(x)
     # TODO Performance optimization: probably there is an efficent
     # way to compute this trace without during the full compution within
@@ -59,7 +59,7 @@ end
 ##### `logdet`
 #####
 
-function frule(::typeof(logdet), x, _, Δx)
+function frule((_, Δx), ::typeof(logdet), x)
     Ω = logdet(x)
     return Ω, tr(inv(x) * Δx)
 end
@@ -76,7 +76,7 @@ end
 ##### `trace`
 #####
 
-function frule(::typeof(tr), x, _, Δx)
+function frule((_, Δx), ::typeof(tr), x)
     return tr(x), tr(Δx)
 end
 

test/rulesets/Base/base.jl

@@ -149,7 +149,7 @@
             _, x̄ = pb(10.5)
             @test extern(x̄) == 0
 
-            _, ẏ = frule(sign, 0.0, Zero(), 10.5)
+            _, ẏ = frule((Zero(), 10.5), sign, 0.0)
             @test extern(ẏ) == 0
         end
     end

test/rulesets/Base/broadcast.jl

@@ -19,7 +19,7 @@
         end
         @testset "frule" begin
             x = rand(3, 3)
-            y, ẏ = frule(broadcast, sin, x, Zero(), Zero(), One())
+            y, ẏ = frule((Zero(), Zero(), One()), broadcast, sin, x)
             @test y == sin.(x)
             @test extern(ẏ) == cos.(x)
         end