Guillermo González de Garibay

@essenciary I'm willing to do a simple pull request for fixing this, but I need to understand your rationale for using `@fetch` to run as a process instead of a...

``` julia> vec(VectorOfArray([rand(3), rand(5)])) ERROR: ArgumentError: number of rows of each array must match (got [3, 5]) Stacktrace: [1] _typed_hcat(#unused#::Type{Float64}, A::Vector{Vector{Float64}}) @ Base ./abstractarray.jl:1518 [2] reduce(#unused#::typeof(hcat), A::Vector{Vector{Float64}}) @ Base ./abstractarray.jl:1572...

I am a bit late here but I've run the benchmark. It works for me on AutoGrad's master branch and julia 0.6. This is what I get: ``` @btime agrad_loss∇($(w,...

I've tried the same but with an `ArrayPartition` in an `ODEProblem` and it works fine, so I assume it is something specific to `SteadyStateProblem`.

I've made some progress and it is looking like an issue with the `similar` method on `ArrayPartition`, and nothing in `DiffEqSensitivity`. `result = similar(ydual, valtype(eltype(ydual)), length(ydual), N)` is returning something...

Ok, the issue is definitely on `ArrayPartition` because `dims` are getting ignored here https://github.com/SciML/RecursiveArrayTools.jl/blob/734999e278ab5a6f9197669df155341d284b26fd/src/array_partition.jl#L31 I think we can close this here unless you want to move the issue to `RecursiveArrayTools`.