remove rand_tangent from ChainRulesTestUtils and use the one from FiniteDifferences (#147)

Author: mzgubic

Project.toml

@@ -1,6 +1,6 @@
 name = "ChainRulesTestUtils"
 uuid = "cdddcdb0-9152-4a09-a978-84456f9df70a"
-version = "0.6.9"
+version = "0.6.10"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

docs/src/index.md

@@ -116,11 +116,11 @@ Test.DefaultTestSet("test_scalar: relu at -0.5", Any[Test.DefaultTestSet("with t
 ## Specifying Tangents
 [`test_frule`](@ref) and [`test_rrule`](@ref) allow you to specify the tangents used for testing.
 This is done by passing in `x ⊢ Δx`, where `x` is the primal and `Δx` is the tangent, in the place of the primal inputs.
-If this is not done the tangent will be automatically generated via [`ChainRulesTestUtils.rand_tangent`](@ref).
+If this is not done the tangent will be automatically generated via `FiniteDifferences.rand_tangent`.
 A special case of this is that if you specify it as `x ⊢ DoesNotExist()` then finite differencing will not be used on that input.
 Similarly, by setting the `output_tangent` keyword argument, you can specify the tangent for the primal output.
 
-This can be useful when the default provided [`ChainRulesTestUtils.rand_tangent`](@ref) doesn't produce the desired tangent for your type.
+This can be useful when the default provided `FiniteDifferences.rand_tangent` doesn't produce the desired tangent for your type.
 For example the default tangent for an `Int` is `DoesNotExist()`.
 Which is correct e.g. when the `Int` represents a discrete integer like in indexing.
 But if you are testing something where the `Int` is actually a special case of a real number, then you would want to specify the tangent as a `Float64`.
@@ -161,7 +161,3 @@ which should have passed the test.
 Modules = [ChainRulesTestUtils]
 Private = false
 ```
-
-```@docs
-ChainRulesTestUtils.rand_tangent
-```

src/ChainRulesTestUtils.jl

@@ -9,6 +9,8 @@ using LinearAlgebra
 using Random
 using Test
 
+import FiniteDifferences: rand_tangent
+
 const _fdm = central_fdm(5, 1; max_range=1e-2)
 
 export TestIterator

src/generate_tangent.jl

@@ -3,7 +3,7 @@
 
 Use this in the place of a tangent/cotangent in [`test_frule`](@ref) or
 [`test_rrule`](@ref) to have that tangent/cotangent generated automatically based on the
-primal. Uses [`rand_tangent`](@ref)
+primal. Uses `FiniteDifferences.rand_tangent`.
 """
 struct Auto end
 
@@ -38,47 +38,3 @@ This function is idempotent. If you pass it a `PrimalAndTangent` it doesn't chan
 """
 auto_primal_and_tangent(primal; rng=Random.GLOBAL_RNG) = primal ⊢ rand_tangent(rng, primal)
 auto_primal_and_tangent(both::PrimalAndTangent; kwargs...) = both
-
-"""
-    rand_tangent([rng::AbstractRNG,] x)
-
-Returns a randomly generated tangent vector appropriate for the primal value `x`.
-"""
-rand_tangent(x) = rand_tangent(Random.GLOBAL_RNG, x)
-
-function rand_tangent(rng::AbstractRNG, x::Union{Symbol, AbstractChar, AbstractString})
-    return DoesNotExist()
-end
-
-rand_tangent(rng::AbstractRNG, x::Integer) = DoesNotExist()
-
-rand_tangent(rng::AbstractRNG, x::T) where {T<:Number} = randn(rng, T)
-
-# ref: https://github.com/JuliaLang/julia/issues/17629
-rand_tangent(rng::AbstractRNG, ::BigFloat) = big(randn(rng))
-
-rand_tangent(rng::AbstractRNG, x::StridedArray) = rand_tangent.(Ref(rng), x)
-
-function rand_tangent(rng::AbstractRNG, x::T) where {T<:Tuple}
-    return Composite{T}(rand_tangent.(Ref(rng), x)...)
-end
-
-function rand_tangent(rng::AbstractRNG, xs::T) where {T<:NamedTuple}
-    return Composite{T}(; map(x -> rand_tangent(rng, x), xs)...)
-end
-
-function rand_tangent(rng::AbstractRNG, x::T) where {T}
-    if !isstructtype(T)
-        throw(ArgumentError("Non-struct types are not supported by this fallback."))
-    end
-
-    field_names = fieldnames(T)
-    if length(field_names) > 0
-        tangents = map(field_names) do field_name
-            rand_tangent(rng, getfield(x, field_name))
-        end
-        return Composite{T}(; NamedTuple{field_names}(tangents)...)
-    else
-        return NO_FIELDS
-    end
-end

test/generate_tangent.jl

@@ -92,7 +92,7 @@
     @testset "rand_tangent" begin
         data = randn(2, 3, 4)
         iter = TestIterator(data, Base.SizeUnknown(), Base.EltypeUnknown())
-        ∂iter = rand_tangent(iter)
+        ∂iter = FiniteDifferences.rand_tangent(iter)
         @test ∂iter isa typeof(iter)
         @test size(∂iter.data) == size(iter.data)
         @test eltype(∂iter.data) === eltype(iter.data)

test/iterator.jl

@@ -1,12 +1,12 @@
 using ChainRulesCore
 using ChainRulesTestUtils
+using FiniteDifferences
 using LinearAlgebra
 using Random
 using Test
 
 @testset "ChainRulesTestUtils.jl" begin
     include("meta_testing_tools.jl")
-    include("generate_tangent.jl")
     include("iterator.jl")
     include("check_result.jl")
     include("testers.jl")