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backport primal fix (#94)
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* Get primal type from primal when fixing composites (#93)

* Get primal type from primal when fixing composites

* removed unused type alias

* Update src/testers.jl

Co-authored-by: Simeon Schaub <[email protected]>

Co-authored-by: Simeon Schaub <[email protected]>

* bump version

Co-authored-by: Simeon Schaub <[email protected]>
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oxinabox and simeonschaub authored Dec 21, 2020
1 parent 33ef407 commit 0ea68c1
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Showing 3 changed files with 31 additions and 9 deletions.
2 changes: 1 addition & 1 deletion Project.toml
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
name = "ChainRulesTestUtils"
uuid = "cdddcdb0-9152-4a09-a978-84456f9df70a"
version = "0.5.9"
version = "0.5.10"

[deps]
ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
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17 changes: 9 additions & 8 deletions src/testers.jl
Original file line number Diff line number Diff line change
Expand Up @@ -70,19 +70,20 @@ function _make_j′vp_call(fdm, f, ȳ, xs, ignores)
@assert length(fd) == length(arginds)

for (dx, ind) in zip(fd, arginds)
args[ind] = _maybe_fix_to_composite(dx)
args[ind] = _maybe_fix_to_composite(xs[ind], dx)
end
return (args...,)
end

"""
_make_jvp_call(fdm, f, xs, ẋs, ignores)
_make_jvp_call(fdm, f, y, xs, ẋs, ignores)
Call `FiniteDifferences.jvp`, with the option to ignore certain `xs`.
# Arguments
- `fdm::FiniteDifferenceMethod`: How to numerically differentiate `f`.
- `f`: The function to differentiate.
- `y`: The primal output `y=f(xs...)` or at least something of the right type
- `xs`: Inputs to `f`, such that `y = f(xs...)`.
- `ẋs`: The directional derivatives of `xs` w.r.t. some real number `t`.
- `ignores`: Collection of `Bool`s, the same length as `xs` and `ẋs`.
Expand All @@ -91,21 +92,21 @@ Call `FiniteDifferences.jvp`, with the option to ignore certain `xs`.
# Returns
- `Ω̇`: Derivative of output w.r.t. `t` estimated by finite differencing.
"""
function _make_jvp_call(fdm, f, xs, ẋs, ignores)
function _make_jvp_call(fdm, f, y, xs, ẋs, ignores)
f2 = _wrap_function(f, xs, ignores)

ignores = collect(ignores)
all(ignores) && return ntuple(_->nothing, length(xs))
sigargs = zip(xs[.!ignores], ẋs[.!ignores])
return _maybe_fix_to_composite(jvp(fdm, f2, sigargs...))
return _maybe_fix_to_composite(y, jvp(fdm, f2, sigargs...))
end

# TODO: remove after https://github.com/JuliaDiff/FiniteDifferences.jl/issues/97
# For functions which return a tuple, FD returns a tuple to represent the differential. Tuple
# is not a natural differential, because it doesn't overload +, so make it a Composite.
_maybe_fix_to_composite(x::Tuple) = Composite{typeof(x)}(x...)
_maybe_fix_to_composite(x::NamedTuple) = Composite{typeof(x)}(;x...)
_maybe_fix_to_composite(x) = x
_maybe_fix_to_composite(::P, x::Tuple) where {P} = Composite{P}(x...)
_maybe_fix_to_composite(::P, x::NamedTuple) where {P} = Composite{P}(;x...)
_maybe_fix_to_composite(::Any, x) = x

"""
test_scalar(f, z; rtol=1e-9, atol=1e-9, fdm=central_fdm(5, 1), fkwargs=NamedTuple(), kwargs...)
Expand Down Expand Up @@ -197,7 +198,7 @@ function frule_test(f, xẋs::Tuple{Any, Any}...; rtol=1e-9, atol=1e-9, fdm=_fdm

ẋs_is_ignored = ẋs .== nothing
# Correctness testing via finite differencing.
dΩ_fd = _make_jvp_call(fdm, (xs...) -> f(deepcopy(xs)...; deepcopy(fkwargs)...), xs, ẋs, ẋs_is_ignored)
dΩ_fd = _make_jvp_call(fdm, (xs...) -> f(deepcopy(xs)...; deepcopy(fkwargs)...), Ω, xs, ẋs, ẋs_is_ignored)
check_equal(dΩ_ad, dΩ_fd; isapprox_kwargs...)


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21 changes: 21 additions & 0 deletions test/testers.jl
Original file line number Diff line number Diff line change
Expand Up @@ -386,4 +386,25 @@ end
@test fails(()->rrule_test(my_identity2, 4.1, (2.2, 3.3)))
end
end


@testset "Tuple primal that is not equal to differential backing" begin
# https://github.com/JuliaMath/SpecialFunctions.jl/issues/288
forwards_trouble(x) = (1, 2.0*x)
@scalar_rule(forwards_trouble(v), Zero(), 2.0)
frule_test(forwards_trouble, (2.5, 2.1))

rev_trouble((x,y)) = y
function ChainRulesCore.rrule(::typeof(rev_trouble), (x,y)::P) where P
rev_trouble_pullback(ȳ) = (NO_FIELDS, Composite{P}(Zero(), ȳ))
return y, rev_trouble_pullback
end
rrule_test(
rev_trouble, 2.5,
(
(3, 3.0),
Composite{Tuple{Int, Float64}}(Zero(), 1.0)
)
)
end
end

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Registration pull request created: JuliaRegistries/General/26747

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.5.10 -m "<description of version>" 0ea68c131d4fbba6907641bb7ccc9d5326cfec25
git push origin v0.5.10

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