Fix and test type inference of jacobian (#200)

* Fix and test type inference of `jacobian`

* Update Project.toml

Author: devmotion

Project.toml

@@ -1,6 +1,6 @@
 name = "FiniteDifferences"
 uuid = "26cc04aa-876d-5657-8c51-4c34ba976000"
-version = "0.12.20"
+version = "0.12.21"
 
 [deps]
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"

src/grad.jl

@@ -21,7 +21,7 @@ function jacobian(fdm, f, x::Vector{<:Real}; len=nothing)
             return ret
         end
     end
-    return (hcat(ẏs...), )
+    return (reduce(hcat, ẏs), )
 end
 
 function jacobian(fdm, f, x; len=nothing)

test/grad.jl

@@ -9,8 +9,8 @@ using FiniteDifferences: grad, jacobian, _jvp, jvp, j′vp, _j′vp, to_vec
             ẋ, ẏ = randn(rng, T, N), randn(rng, T, M)
             xy, ẋẏ = vcat(x, y), vcat(ẋ, ẏ)
             ż_manual = _jvp(fdm, (xy)->sum(sin, xy), xy, ẋẏ)[1]
-            ż_auto = jvp(fdm, x->sum(sin, x[1]) + sum(sin, x[2]), ((x, y), (ẋ, ẏ)))
-            ż_multi = jvp(fdm, (x, y)->sum(sin, x) + sum(sin, y), (x, ẋ), (y, ẏ))
+            ż_auto = @inferred(jvp(fdm, x->sum(sin, x[1]) + sum(sin, x[2]), ((x, y), (ẋ, ẏ))))
+            ż_multi = @inferred(jvp(fdm, (x, y)->sum(sin, x) + sum(sin, y), (x, ẋ), (y, ẏ)))
             @test ż_manual ≈ ż_auto
             @test ż_manual ≈ ż_multi
         end
@@ -52,7 +52,7 @@ using FiniteDifferences: grad, jacobian, _jvp, jvp, j′vp, _j′vp, to_vec
         @assert length(ȳ) == length(f(x))
 
         # Check that the jacobian is as expected.
-        J_fdm = jacobian(fdm, f, x)[1]
+        J_fdm = @inferred(jacobian(fdm, f, x))[1]
         @test size(J_fdm) == (length(ȳ), length(x))
         @test J_fdm ≈ J_exact
         @test J_fdm == jacobian(fdm, f, x)[1]
@@ -79,7 +79,8 @@ using FiniteDifferences: grad, jacobian, _jvp, jvp, j′vp, _j′vp, to_vec
         @test Ac == A
 
         # Prevent regression against https://github.com/JuliaDiff/FiniteDifferences.jl/issues/67
-        J = first(jacobian(fdm, identity, x))
+        # Type inference: https://github.com/JuliaDiff/FiniteDifferences.jl/issues/199
+        J = first(@inferred(jacobian(fdm, identity, x)))
         @test J ≈ one(Matrix{T}(undef, size(J)))
     end