Make AbstractArray reshape method less specific

[jishnub]

Since this method is meant to be a fallback, this should be less specific than other methods in both the array type and the axis type. This fixes an ambiguity error while using OffsetArrays and FillArrays together:

julia> reshape(Fill(2,6), big(2), :)
ERROR: MethodError: reshape(::Fill{Int64, 1, Tuple{Base.OneTo{Int64}}}, ::Tuple{BigInt, Colon}) is ambiguous.

Candidates:
  reshape(A::AbstractArray, inds::Tuple{Union{Colon, Integer, AbstractUnitRange}, Vararg{Union{Colon, Integer, AbstractUnitRange}}})
    @ OffsetArrays ~/Dropbox/JuliaPackages/OffsetArrays.jl/src/OffsetArrays.jl:352
  reshape(parent::AbstractFill, dims::Tuple{Vararg{Union{Colon, Integer}}})
    @ FillArrays ~/Dropbox/JuliaPackages/FillArrays.jl/src/FillArrays.jl:253

Possible fix, define
  reshape(::AbstractFill, ::Tuple{Union{Colon, Integer}, Vararg{Union{Colon, Integer}}})

After this PR

julia> reshape(Fill(2,6), big(2), :)
2×3 Fill{Int64}, with entries equal to 2

[codecov]

Codecov Report

Merging #333 (79e70d0) into master (0929e07) will not change coverage.
The diff coverage is 100.00%.

@@           Coverage Diff           @@
##           master     #333   +/-   ##
=======================================
  Coverage   98.67%   98.67%           
=======================================
  Files           5        5           
  Lines         452      452           
=======================================
  Hits          446      446           
  Misses          6        6           

Impacted Files	Coverage Δ
src/OffsetArrays.jl	98.29% <100.00%> (ø)

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[timholy]

The only potential problem with that is that Tuple{} <: Tuple{Vararg{T}}. Do we have a test for a 0d reshape?

[jishnub]

Yes, I have added a test for that in this PR. That works because Base defines reshape for Tuple{Vararg{Int}}, which is more specific than Tuple{Vararg{OffsetAxis}}.

[timholy]

Shoot, I missed that. Thanks for doing this! This is subtle design and you've clearly mastered it.

[jishnub]

Test failure on v1.0 is due to JuliaMath/IntegerMathUtils.jl#5, and would hopefully be fixed by JuliaRegistries/General#86557