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improve cat inferrability #45028

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Apr 25, 2022
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improve cat inferrability #45028

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33 changes: 15 additions & 18 deletions base/abstractarray.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -1716,23 +1716,16 @@ end
_cs(d, a, b) = (a == b ? a : throw(DimensionMismatch(
"mismatch in dimension $d (expected $a got $b)")))

function dims2cat(::Val{dims}) where dims
if any(≤(0), dims)
throw(ArgumentError("All cat dimensions must be positive integers, but got $dims"))
end
ntuple(in(dims), maximum(dims))
end

dims2cat(::Val{dims}) where dims = dims2cat(dims)
function dims2cat(dims)
if any(≤(0), dims)
throw(ArgumentError("All cat dimensions must be positive integers, but got $dims"))
end
ntuple(in(dims), maximum(dims))
end

_cat(dims, X...) = cat_t(promote_eltypeof(X...), X...; dims=dims)
_cat(dims, X...) = _cat_t(dims, promote_eltypeof(X...), X...)

@inline cat_t(::Type{T}, X...; dims) where {T} = _cat_t(dims, T, X...)
@inline function _cat_t(dims, ::Type{T}, X...) where {T}
catdims = dims2cat(dims)
shape = cat_size_shape(catdims, X...)
Expand All @@ -1742,6 +1735,9 @@ _cat(dims, X...) = cat_t(promote_eltypeof(X...), X...; dims=dims)
end
return __cat(A, shape, catdims, X...)
end
# this version of `cat_t` is not very kind for inference and so its usage should be avoided,
# nevertheless it is here just for compat after https://github.com/JuliaLang/julia/pull/45028
@inline cat_t(::Type{T}, X...; dims) where {T} = _cat_t(dims, T, X...)

# Why isn't this called `__cat!`?
__cat(A, shape, catdims, X...) = __cat_offset!(A, shape, catdims, ntuple(zero, length(shape)), X...)
Expand Down Expand Up @@ -1880,8 +1876,8 @@ julia> reduce(hcat, vs)
"""
hcat(X...) = cat(X...; dims=Val(2))

typed_vcat(::Type{T}, X...) where T = cat_t(T, X...; dims=Val(1))
typed_hcat(::Type{T}, X...) where T = cat_t(T, X...; dims=Val(2))
typed_vcat(::Type{T}, X...) where T = _cat_t(Val(1), T, X...)
typed_hcat(::Type{T}, X...) where T = _cat_t(Val(2), T, X...)

"""
cat(A...; dims)
Expand Down Expand Up @@ -1917,7 +1913,8 @@ julia> cat(true, trues(2,2), trues(4)', dims=(1,2))
```
"""
@inline cat(A...; dims) = _cat(dims, A...)
_cat(catdims, A::AbstractArray{T}...) where {T} = cat_t(T, A...; dims=catdims)
# `@constprop :aggressive` allows `catdims` to be propagated as constant improving return type inference
@constprop :aggressive _cat(catdims, A::AbstractArray{T}...) where {T} = _cat_t(catdims, T, A...)

# The specializations for 1 and 2 inputs are important
# especially when running with --inline=no, see #11158
Expand All @@ -1928,12 +1925,12 @@ hcat(A::AbstractArray) = cat(A; dims=Val(2))
hcat(A::AbstractArray, B::AbstractArray) = cat(A, B; dims=Val(2))
hcat(A::AbstractArray...) = cat(A...; dims=Val(2))

typed_vcat(T::Type, A::AbstractArray) = cat_t(T, A; dims=Val(1))
typed_vcat(T::Type, A::AbstractArray, B::AbstractArray) = cat_t(T, A, B; dims=Val(1))
typed_vcat(T::Type, A::AbstractArray...) = cat_t(T, A...; dims=Val(1))
typed_hcat(T::Type, A::AbstractArray) = cat_t(T, A; dims=Val(2))
typed_hcat(T::Type, A::AbstractArray, B::AbstractArray) = cat_t(T, A, B; dims=Val(2))
typed_hcat(T::Type, A::AbstractArray...) = cat_t(T, A...; dims=Val(2))
typed_vcat(T::Type, A::AbstractArray) = _cat_t(Val(1), T, A)
typed_vcat(T::Type, A::AbstractArray, B::AbstractArray) = _cat_t(Val(1), T, A, B)
typed_vcat(T::Type, A::AbstractArray...) = _cat_t(Val(1), T, A...)
typed_hcat(T::Type, A::AbstractArray) = _cat_t(Val(2), T, A)
typed_hcat(T::Type, A::AbstractArray, B::AbstractArray) = _cat_t(Val(2), T, A, B)
typed_hcat(T::Type, A::AbstractArray...) = _cat_t(Val(2), T, A...)

# 2d horizontal and vertical concatenation

Expand Down
4 changes: 2 additions & 2 deletions stdlib/LinearAlgebra/src/special.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -414,14 +414,14 @@ const _TypedDenseConcatGroup{T} = Union{Vector{T}, Adjoint{T,Vector{T}}, Transpo

promote_to_array_type(::Tuple{Vararg{Union{_DenseConcatGroup,UniformScaling}}}) = Matrix

Base._cat(dims, xs::_DenseConcatGroup...) = Base.cat_t(promote_eltype(xs...), xs...; dims=dims)
Base._cat(dims, xs::_DenseConcatGroup...) = Base._cat_t(dims, promote_eltype(xs...), xs...)
vcat(A::Vector...) = Base.typed_vcat(promote_eltype(A...), A...)
vcat(A::_DenseConcatGroup...) = Base.typed_vcat(promote_eltype(A...), A...)
hcat(A::Vector...) = Base.typed_hcat(promote_eltype(A...), A...)
hcat(A::_DenseConcatGroup...) = Base.typed_hcat(promote_eltype(A...), A...)
hvcat(rows::Tuple{Vararg{Int}}, xs::_DenseConcatGroup...) = Base.typed_hvcat(promote_eltype(xs...), rows, xs...)
# For performance, specially handle the case where the matrices/vectors have homogeneous eltype
Base._cat(dims, xs::_TypedDenseConcatGroup{T}...) where {T} = Base.cat_t(T, xs...; dims=dims)
Base._cat(dims, xs::_TypedDenseConcatGroup{T}...) where {T} = Base._cat_t(dims, T, xs...)
vcat(A::_TypedDenseConcatGroup{T}...) where {T} = Base.typed_vcat(T, A...)
hcat(A::_TypedDenseConcatGroup{T}...) where {T} = Base.typed_hcat(T, A...)
hvcat(rows::Tuple{Vararg{Int}}, xs::_TypedDenseConcatGroup{T}...) where {T} = Base.typed_hvcat(T, rows, xs...)
Expand Down
4 changes: 4 additions & 0 deletions test/abstractarray.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -733,6 +733,10 @@ function test_cat(::Type{TestAbstractArray})
cat3v(As) = cat(As...; dims=Val(3))
@test @inferred(cat3v(As)) == zeros(2, 2, 2)
@test @inferred(cat(As...; dims=Val((1,2)))) == zeros(4, 4)

r = rand(Float32, 56, 56, 64, 1);
f(r) = cat(r, r, dims=(3,))
@inferred f(r);
end

function test_ind2sub(::Type{TestAbstractArray})
Expand Down
15 changes: 3 additions & 12 deletions test/ambiguous.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -172,20 +172,11 @@ using LinearAlgebra, SparseArrays, SuiteSparse
# not using isempty so this prints more information when it fails
@testset "detect_ambiguities" begin
let ambig = Set{Any}(((m1.sig, m2.sig) for (m1, m2) in detect_ambiguities(Core, Base; recursive=true, ambiguous_bottom=false, allowed_undefineds)))
@test isempty(ambig)
expect = []
good = true
while !isempty(ambig)
sigs = pop!(ambig)
i = findfirst(==(sigs), expect)
if i === nothing
println(stderr, "push!(expect, (", sigs[1], ", ", sigs[2], "))")
good = false
continue
end
deleteat!(expect, i)
for (sig1, sig2) in ambig
@test sig1 === sig2 # print this ambiguity
good = false
end
@test isempty(expect)
@test good
end

Expand Down