`onehotbatch(::CuArray, ...)` moves data to host

[mcabbott]

The lack of https://github.com/FluxML/Flux.jl/pull/1959 causes the following error, currently blocking https://github.com/FluxML/Flux.jl/pull/2025 :

julia> using CUDA, OneHotArrays, NNlibCUDA

julia> CUDA.allowscalar(false)

julia> x = [1, 3, 2];

julia> y = onehotbatch(x, (0,1,2,3))
4×3 OneHotMatrix(::Vector{UInt32}) with eltype Bool:
 ⋅  ⋅  ⋅
 1  ⋅  ⋅
 ⋅  ⋅  1
 ⋅  1  ⋅

julia> y2 = onehotbatch(x |> cu, (0,1,2,3))
ERROR: Scalar indexing is disallowed.

Edit: after #27, onehotbatch(x |> cu, 0:3) works, but other ways to specify the labels do not.

[chengchingwen]

I don't think that should be allowed. Taking cu should always happened AFTER taking onehotbatch. Consider the some real case where labels are non-bits types like array of strings, it doesn't make sense to take onehotbatch on gpu array. It just need to be clarified in the docs.

[mcabbott]

No strong opinions, was just trying to make Flux's tests pass. https://github.com/FluxML/OneHotArrays.jl/pull/17 is more code duplication than ideal.

[chengchingwen]

Maybe we could remove that test in Flux?

[ToucheSir]

Also no strong feelings either way, but we if we don't want to support we should add the functionality as deprecated so that it's not a breaking change on the Flux side.

[CarloLucibello]

As seen in #24 the current behavior is surprising when allowscalar(true). We should allow onehotbatch(::CuArray, ...) whenever possible and error out otherwise.

[CarloLucibello]

#27 fixes the case onehotbatch(::CuVector{<:Integer}, ::UnitRange)