Error computing j′vp of a scalar -> matrix function

I can't compute the j′vp for the function p -> x^p on FiniteDifferences v0.10.0, where x is a matrix and p is a scalar:

julia> using FiniteDifferences

julia> fdm = central_fdm(5, 1);

julia> x = [1.0 2.0; 3.0 4.0]; # real input

julia> x^3.0 # real output 
2×2 Array{Float64,2}:
 37.0   54.0
 81.0  118.0

julia> seed = [1.0 1.0; 1.0 1.0]; # real seed

julia> j′vp(fdm, p -> x^p, seed, 3.0)  # but an error is raised that one of the vectors has length 8?
ERROR: DimensionMismatch("dimensions must match: a has dims (Base.OneTo(8),), b has dims (Base.OneTo(4),), mismatch at 1")
Stacktrace:
 [1] promote_shape at ./indices.jl:178 [inlined]
 [2] promote_shape at ./indices.jl:169 [inlined]
 [3] +(::Array{Float64,1}, ::Array{Float64,1}) at ./arraymath.jl:45
 [4] add_sum(::Array{Float64,1}, ::Array{Float64,1}) at ./reduce.jl:21
 [5] _mapreduce(::FiniteDifferences.var"#22#24"{FiniteDifferences.var"#49#51"{Int64,Base.var"#64#65"{Base.var"#64#65"{Base.var"#64#65"{typeof(first),typeof(to_vec)},var"#7#8"},FiniteDifferences.var"#Real_from_vec#30"},Array{Float64,1}},Float64,UnitRange{Int64},Array{Float64,1},Float64}, ::typeof(Base.add_sum), ::IndexLinear, ::Base.OneTo{Int64}) at ./reduce.jl:403
 [6] _mapreduce_dim(::Function, ::Function, ::NamedTuple{(),Tuple{}}, ::Base.OneTo{Int64}, ::Colon) at ./reducedim.jl:312
 [7] #mapreduce#580 at ./reducedim.jl:307 [inlined]
 [8] mapreduce at ./reducedim.jl:307 [inlined]
 [9] _sum at ./reducedim.jl:657 [inlined]
 [10] #sum#584 at ./reducedim.jl:653 [inlined]
 [11] sum at ./reducedim.jl:653 [inlined]
 [12] fdm(::FiniteDifferences.Central{UnitRange{Int64},Array{Float64,1}}, ::FiniteDifferences.var"#49#51"{Int64,Base.var"#64#65"{Base.var"#64#65"{Base.var"#64#65"{typeof(first),typeof(to_vec)},var"#7#8"},FiniteDifferences.var"#Real_from_vec#30"},Array{Float64,1}}, ::Float64, ::Val{true}; condition::Int64, bound::Float64, eps::Float64, adapt::Int64, max_step::Float64) at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/methods.jl:270
 [13] fdm(::FiniteDifferences.Central{UnitRange{Int64},Array{Float64,1}}, ::FiniteDifferences.var"#49#51"{Int64,Base.var"#64#65"{Base.var"#64#65"{Base.var"#64#65"{typeof(first),typeof(to_vec)},var"#7#8"},FiniteDifferences.var"#Real_from_vec#30"},Array{Float64,1}}, ::Float64, ::Val{true}) at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/methods.jl:229
 [14] #fdm#25 at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/methods.jl:281 [inlined]
 [15] fdm at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/methods.jl:281 [inlined] (repeats 2 times)
 [16] #_#7 at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/methods.jl:93 [inlined]
 [17] Central at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/methods.jl:93 [inlined]
 [18] #48 at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/grad.jl:16 [inlined]
 [19] iterate at ./generator.jl:47 [inlined]
 [20] _collect(::Base.OneTo{Int64}, ::Base.Generator{Base.OneTo{Int64},FiniteDifferences.var"#48#50"{FiniteDifferences.Central{UnitRange{Int64},Array{Float64,1}},Base.var"#64#65"{Base.var"#64#65"{Base.var"#64#65"{typeof(first),typeof(to_vec)},var"#7#8"},FiniteDifferences.var"#Real_from_vec#30"},Array{Float64,1}}}, ::Base.EltypeUnknown, ::Base.HasShape{1}) at ./array.jl:678
 [21] collect_similar(::Base.OneTo{Int64}, ::Base.Generator{Base.OneTo{Int64},FiniteDifferences.var"#48#50"{FiniteDifferences.Central{UnitRange{Int64},Array{Float64,1}},Base.var"#64#65"{Base.var"#64#65"{Base.var"#64#65"{typeof(first),typeof(to_vec)},var"#7#8"},FiniteDifferences.var"#Real_from_vec#30"},Array{Float64,1}}}) at ./array.jl:607
 [22] map(::Function, ::Base.OneTo{Int64}) at ./abstractarray.jl:2072
 [23] #jacobian#47 at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/grad.jl:15 [inlined]
 [24] jacobian at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/grad.jl:10 [inlined]
 [25] _j′vp(::FiniteDifferences.Central{UnitRange{Int64},Array{Float64,1}}, ::Function, ::Array{Float64,1}, ::Array{Float64,1}) at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/grad.jl:79
 [26] j′vp(::FiniteDifferences.Central{UnitRange{Int64},Array{Float64,1}}, ::Function, ::Array{Float64,2}, ::Float64) at /Users/saxen/.julia/packages/FiniteDifferences/VHfqf/src/grad.jl:73
 [27] top-level scope at REPL[16]:1

 julia> j′vp(fdm, p -> p*x, seed, 3.0) # this scalar -> matrix function is fine
 (10.000000000000309,)

julia> j′vp(fdm, x->x^3.0, seed, x) # this matrix -> matrix function is also fine
([51.00000000000287 86.99999999999915; 66.9999999999964 110.9999999999985],)

Run the scalar-to-matrix j′vp reproduction from the issue, then inspect the j′vp and jacobian paths in src/grad.jl and the finite-difference evaluation in src/methods.jl. Done means the p -> x^p case no longer raises DimensionMismatch while the scalar-to-matrix and matrix-to-matrix examples continue to work.