Accept more general Integer sizes in reshape (#55521)

This PR generalizes the `reshape` methods to accept `Integer`s instead
of `Int`s, and adds a `_reshape_uncolon` method for `Integer` arguments.
The current `_reshape_uncolon` method that accepts `Int`s 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 `Int`s pass through that method.

The call sequence would now go like this:
```julia
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 `Integer`s to `Int`s in the actual reshaping step. However,
`BigInt` sizes that may be converted to `Int`s will work now:
```julia
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 `Int`s 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`.

---------

Co-authored-by: Neven Sajko <[email protected]>

base/reshapedarray.jl

@@ -121,37 +121,56 @@ reshape
 
 reshape(parent::AbstractArray, dims::IntOrInd...) = reshape(parent, dims)
 reshape(parent::AbstractArray, shp::Tuple{Union{Integer,OneTo}, Vararg{Union{Integer,OneTo}}}) = reshape(parent, to_shape(shp))
+reshape(parent::AbstractArray, dims::Tuple{Integer, Vararg{Integer}}) = reshape(parent, map(Int, dims))
 reshape(parent::AbstractArray, dims::Dims)        = _reshape(parent, dims)
 
 # Allow missing dimensions with Colon():
 reshape(parent::AbstractVector, ::Colon) = parent
 reshape(parent::AbstractVector, ::Tuple{Colon}) = parent
 reshape(parent::AbstractArray, dims::Int...) = reshape(parent, dims)
-reshape(parent::AbstractArray, dims::Union{Int,Colon}...) = reshape(parent, dims)
-reshape(parent::AbstractArray, dims::Tuple{Vararg{Union{Int,Colon}}}) = reshape(parent, _reshape_uncolon(parent, dims))
-@inline function _reshape_uncolon(A, dims)
-    @noinline throw1(dims) = throw(DimensionMismatch(string("new dimensions $(dims) ",
-        "may have at most one omitted dimension specified by `Colon()`")))
-    @noinline throw2(A, dims) = throw(DimensionMismatch(string("array size $(length(A)) ",
-        "must be divisible by the product of the new dimensions $dims")))
-    pre = _before_colon(dims...)::Tuple{Vararg{Int}}
+reshape(parent::AbstractArray, dims::Integer...) = reshape(parent, dims)
+reshape(parent::AbstractArray, dims::Union{Integer,Colon}...) = reshape(parent, dims)
+reshape(parent::AbstractArray, dims::Tuple{Vararg{Union{Integer,Colon}}}) = reshape(parent, _reshape_uncolon(parent, dims))
+
+@noinline throw1(dims) = throw(DimensionMismatch(LazyString("new dimensions ", dims,
+        " may have at most one omitted dimension specified by `Colon()`")))
+@noinline throw2(lenA, dims) = throw(DimensionMismatch(string("array size ", lenA,
+    " must be divisible by the product of the new dimensions ", dims)))
+
+@inline function _reshape_uncolon(A, _dims::Tuple{Vararg{Union{Integer, Colon}}})
+    # promote the dims to `Int` at least
+    dims = map(x -> x isa Colon ? x : promote_type(typeof(x), Int)(x), _dims)
+    pre = _before_colon(dims...)
     post = _after_colon(dims...)
     _any_colon(post...) && throw1(dims)
-    post::Tuple{Vararg{Int}}
     len = length(A)
-    sz, is_exact = if iszero(len)
-        (0, true)
+    _reshape_uncolon_computesize(len, dims, pre, post)
+end
+@inline function _reshape_uncolon_computesize(len::Int, dims, pre::Tuple{Vararg{Int}}, post::Tuple{Vararg{Int}})
+    sz = if iszero(len)
+        0
     else
         let pr = Core.checked_dims(pre..., post...)  # safe product
-            if iszero(pr)
-                throw2(A, dims)
-            end
-            (quo, rem) = divrem(len, pr)
-            (Int(quo), iszero(rem))
+            quo = _reshape_uncolon_computesize_nonempty(len, dims, pr)
+            convert(Int, quo)
         end
-    end::Tuple{Int,Bool}
-    is_exact || throw2(A, dims)
-    (pre..., sz, post...)::Tuple{Int,Vararg{Int}}
+    end
+    (pre..., sz, post...)
+end
+@inline function _reshape_uncolon_computesize(len, dims, pre, post)
+    pr = prod((pre..., post...))
+    sz = if iszero(len)
+        promote(len, pr)[1] # zero of the correct type
+    else
+        _reshape_uncolon_computesize_nonempty(len, dims, pr)
+    end
+    (pre..., sz, post...)
+end
+@inline function _reshape_uncolon_computesize_nonempty(len, dims, pr)
+    iszero(pr) && throw2(len, dims)
+    (quo, rem) = divrem(len, pr)
+    iszero(rem) || throw2(len, dims)
+    quo
 end
 @inline _any_colon() = false
 @inline _any_colon(dim::Colon, tail...) = true

test/abstractarray.jl

@@ -2186,3 +2186,23 @@ end
     copyto!(A, 1, x, 1)
     @test A == axes(A,1)
 end
+
+@testset "reshape with Integer sizes" begin
+    @test reshape(1:4, big(2), big(2)) == reshape(1:4, 2, 2)
+    a = [1 2 3; 4 5 6]
+    reshaped_arrays = (
+        reshape(a, 3, 2),
+        reshape(a, (3, 2)),
+        reshape(a, big(3), big(2)),
+        reshape(a, (big(3), big(2))),
+        reshape(a, :, big(2)),
+        reshape(a, (:, big(2))),
+        reshape(a, big(3), :),
+        reshape(a, (big(3), :)),
+    )
+    @test allequal(reshaped_arrays)
+    for b ∈ reshaped_arrays
+        @test b isa Matrix{Int}
+        @test b.ref === a.ref
+    end
+end

test/offsetarray.jl

@@ -914,3 +914,14 @@ end
     b = sum(a, dims=1)
     @test b[begin] == sum(r)
 end
+
+@testset "reshape" begin
+    A0 = [1 3; 2 4]
+    A = reshape(A0, 2:3, 4:5)
+    @test axes(A) == Base.IdentityUnitRange.((2:3, 4:5))
+
+    B = reshape(A0, -10:-9, 9:10)
+    @test isa(B, OffsetArray{Int,2})
+    @test parent(B) == A0
+    @test axes(B) == Base.IdentityUnitRange.((-10:-9, 9:10))
+end

test/testhelpers/OffsetArrays.jl

@@ -529,7 +529,7 @@ _similar_axes_or_length(AT, ax::I, ::I) where {I} = similar(AT, map(_indexlength
 
 # reshape accepts a single colon
 Base.reshape(A::AbstractArray, inds::OffsetAxis...) = reshape(A, inds)
-function Base.reshape(A::AbstractArray, inds::Tuple{OffsetAxis,Vararg{OffsetAxis}})
+function Base.reshape(A::AbstractArray, inds::Tuple{Vararg{OffsetAxis}})
     AR = reshape(no_offset_view(A), map(_indexlength, inds))
     O = OffsetArray(AR, map(_offset, axes(AR), inds))
     return _popreshape(O, axes(AR), _filterreshapeinds(inds))
@@ -557,6 +557,8 @@ Base.reshape(A::OffsetArray, inds::Tuple{OffsetAxis,Vararg{OffsetAxis}}) =
     OffsetArray(_reshape(parent(A), inds), map(_toaxis, inds))
 # And for non-offset axes, we can just return a reshape of the parent directly
 Base.reshape(A::OffsetArray, inds::Tuple{Union{Integer,Base.OneTo},Vararg{Union{Integer,Base.OneTo}}}) = _reshape_nov(A, inds)
+Base.reshape(A::OffsetArray, inds::Tuple{Integer,Vararg{Integer}}) = _reshape_nov(A, inds)
+Base.reshape(A::OffsetArray, inds::Tuple{Union{Colon, Integer}, Vararg{Union{Colon, Integer}}}) = _reshape_nov(A, inds)
 Base.reshape(A::OffsetArray, inds::Dims) = _reshape_nov(A, inds)
 Base.reshape(A::OffsetVector, ::Colon) = A
 Base.reshape(A::OffsetVector, ::Tuple{Colon}) = A