Accept more general Integer sizes in reshape

[jishnub]

This PR generalizes the reshape methods to accept Integers instead of Ints, and adds a _reshape_uncolon method for Integer arguments. The current _reshape_uncolon method that accepts Ints is left unchanged to ensure that the inferred types are not impacted. I've also tried to ensure that most Integer subtypes in Base that may be safely converted to Ints pass through that method.

The call sequence would now go like this:

reshape(A, ::Tuple{Vararg{Union{Integer, Colon}}}) -> reshape(A, ::Tuple{Vararg{Integer}}) -> reshape(A, ::Tuple{Vararg{Int}}) (fallback)

This lets packages define reshape(A::CustomArray, ::Tuple{Integer, Vararg{Integer}}) without having to implement _reshape_uncolon by themselves (or having to call internal Base functions, as in JuliaArrays/FillArrays.jl#373). reshape calls involving a Colon would convert this to an Integer in Base, and then pass the Integer sizes to the custom method defined in the package.

This PR does not resolve issues like #40076 because this still converts Integers to Ints in the actual reshaping step. However, BigInt sizes that may be converted to Ints will work now:

julia> reshape(1:4, big(2), big(2))
2×2 reshape(::UnitRange{Int64}, 2, 2) with eltype Int64:
 1  3
 2  4

julia> reshape(1:4, big(1), :)
1×4 reshape(::UnitRange{Int64}, 1, 4) with eltype Int64:
 1  2  3  4

Note that the reshape method with Integer sizes explicitly converts these to Ints to avoid self-recursion (as opposed to calling to_shape to carry out the conversion implicitly). In the future, we may want to decide what to do with types or values that can't be converted to an Int.

[nsajko]

Fixes #17372

[jishnub]

Gentle bump

[jishnub]

Gentle bump

[jishnub]

Gentle bump

[jishnub]

@nsajko Could you suggest a way to simplify the methods here without widening the inference results? In particular, what were the type-assertions in _reshape_uncolon achieving, and are there tests for these improvements?