Revert "Fix broadcast_indices (#22130)"

This reverts commit fb81c34.
And adds a test for the bug this causes.

Author: vtjnash

base/broadcast.jl

@@ -45,12 +45,13 @@ promote_containertype(::Type{T}, ::Type{T}) where {T} = T
 ## Calculate the broadcast indices of the arguments, or error if incompatible
 # array inputs
 broadcast_indices() = ()
-broadcast_indices(A) = broadcast_indices(containertype(A), A)
+broadcast_indices(A) = _broadcast_indices(containertype(A), A)
 @inline broadcast_indices(A, B...) = broadcast_shape(broadcast_indices(A), broadcast_indices(B...))
-broadcast_indices(::ScalarType, A) = ()
-broadcast_indices(::Type{Tuple}, A) = (OneTo(length(A)),)
-broadcast_indices(::Type{Array}, A::Ref) = ()
-broadcast_indices(::Type{Array}, A) = indices(A)
+_broadcast_indices(::Type, A) = error("_containertype definition requires a corresponding _broadcast_indices definition")
+_broadcast_indices(::ScalarType, A) = ()
+_broadcast_indices(::Type{Tuple}, A) = (OneTo(length(A)),)
+_broadcast_indices(::Type{Array}, A::Ref) = ()
+_broadcast_indices(::Type{Array}, A) = indices(A)
 
 # shape (i.e., tuple-of-indices) inputs
 broadcast_shape(shape::Tuple) = shape

base/sparse/higherorderfns.jl

@@ -6,7 +6,8 @@ module HigherOrderFns
 # particularly map[!]/broadcast[!] for SparseVectors and SparseMatrixCSCs at present.
 import Base: map, map!, broadcast, broadcast!
 import Base.Broadcast: _containertype, promote_containertype,
-                       broadcast_indices, broadcast_c, broadcast_c!
+                       broadcast_indices, _broadcast_indices,
+                       broadcast_c, broadcast_c!
 
 using Base: front, tail, to_shape
 using ..SparseArrays: SparseVector, SparseMatrixCSC, AbstractSparseVector,
@@ -900,7 +901,7 @@ end
 # (10) broadcast[!] over combinations of broadcast scalars and sparse vectors/matrices
 
 # broadcast shape promotion for combinations of sparse arrays and other types
-broadcast_indices(::Type{AbstractSparseArray}, A) = indices(A)
+_broadcast_indices(::Type{AbstractSparseArray}, A) = indices(A)
 # broadcast container type promotion for combinations of sparse arrays and other types
 _containertype(::Type{<:SparseVecOrMat}) = AbstractSparseArray
 # combinations of sparse arrays with broadcast scalars should yield sparse arrays
@@ -984,7 +985,7 @@ struct PromoteToSparse end
 # broadcast containertype definitions for structured matrices
 StructuredMatrix = Union{Diagonal,Bidiagonal,Tridiagonal,SymTridiagonal}
 _containertype(::Type{<:StructuredMatrix}) = PromoteToSparse
-broadcast_indices(::Type{PromoteToSparse}, A) = indices(A)
+_broadcast_indices(::Type{PromoteToSparse}, A) = indices(A)
 
 # combinations explicitly involving Tuples and PromoteToSparse collections
 # divert to the generic AbstractArray broadcast code

test/broadcast.jl

@@ -419,7 +419,6 @@ struct Array19745{T,N} <: AbstractArray{T,N}
     data::Array{T,N}
 end
 Base.getindex(A::Array19745, i::Integer...) = A.data[i...]
-Base.setindex!(A::Array19745, v::Any, i::Integer...) = setindex!(A.data, v, i...)
 Base.size(A::Array19745) = size(A.data)
 
 Base.Broadcast._containertype{T<:Array19745}(::Type{T}) = Array19745
@@ -436,12 +435,8 @@ Base.Broadcast.broadcast_indices(::Type{Array19745}, A::Ref) = ()
 getfield19745(x::Array19745) = x.data
 getfield19745(x)             = x
 
-function Base.Broadcast.broadcast_c(f, ::Type{Array19745}, A, Bs...)
-    T     = Base.Broadcast._broadcast_eltype(f, A, Bs...)
-    shape = Base.Broadcast.broadcast_indices(A, Bs...)
-    dest = Array19745(Array{T}(Base.index_lengths(shape...)))
-    return broadcast!(f, dest, A, Bs...)
-end
+Base.Broadcast.broadcast_c(f, ::Type{Array19745}, A, Bs...) =
+    Array19745(Base.Broadcast.broadcast_c(f, Array, getfield19745(A), map(getfield19745, Bs)...))
 
 @testset "broadcasting for custom AbstractArray" begin
     a  = randn(10)
@@ -520,3 +515,6 @@ let t = (0, 1, 2)
     o = 1
     @test @inferred(broadcast(+, t, o)) == (1, 2, 3)
 end
+
+# issue #22130
+@test convert.(Any, [1, 2]) == [1, 2]