Something off with broadcast of ArrayPartition with NTuple #63

julia> f = (u, p, t) -> .- u
#38 (generic function with 1 method)

julia> prb = ODEProblem(f, (1.0:5.0...,), (0.0,2.0))
ODEProblem with uType NTuple{5,Float64} and tType Float64. In-place: false
timespan: (0.0, 2.0)
u0: (1.0, 2.0, 3.0, 4.0, 5.0)

julia> sprb = solve(prb, Tsit5(), abstol=1e-17, reltol=1e-17, save_on=false)
retcode: Success
Interpolation: specialized 4th order "free" interpolation
t: 2-element Array{Float64,1}:
 0.0
 2.0
u: 2-element Array{RecursiveArrayTools.ArrayPartition{Float64,NTuple{5,Float64}},1}:
 1.02.03.04.05.0                                                                             
 0.135335283236613170.270670566473226350.40600584970983820.54134113294645270.6766764161830637

julia> sprb.u[2] .- ((1:5).*exp(-2)) #Check with the real result
(4.718447854656915e-16, 0.13533528323661365, 0.2706705664732255, 0.40600584970984, 0.541341132946451)

julia> sprb.u[2] .- 1
(-0.8646647167633869, -0.7293294335267737, -0.5939941502901618, -0.4586588670535473, -0.32332358381693627)

julia> sprb.u[2] .- (1:5)
(-0.8646647167633869, -0.7293294335267737, -0.5939941502901618, -0.4586588670535473, -0.32332358381693627)

julia> sprb.u[2] .- collect(1:5)
(-0.8646647167633869, -0.7293294335267737, -0.5939941502901618, -0.4586588670535473, -0.32332358381693627)

julia> sprb.u[2] .- sprb.u[2]
(0.0, 0.0, 0.0, 0.0, 0.0)

julia> sprb.u[2] .- sprb.u[1]
(-0.8646647167633869, -1.7293294335267737, -2.593994150290162, -3.4586588670535474, -4.323323583816936)

julia> (1:5...,) .- (1:5)
5-element Array{Int64,1}:
 0
 0
 0
 0
 0