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DArray: Improve 0-dim support #528

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Merged
merged 1 commit into from
Jun 5, 2024
Merged

DArray: Improve 0-dim support #528

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28 changes: 23 additions & 5 deletions src/array/darray.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,7 @@ ArrayDomain(xs::NTuple{N,Base.OneTo}) where N =
ArrayDomain{N,NTuple{N,UnitRange{Int}}}(ntuple(i->UnitRange(xs[i]), N))
ArrayDomain(xs::NTuple{N,Int}) where N =
ArrayDomain{N,NTuple{N,UnitRange{Int}}}(ntuple(i->xs[i]:xs[i], N))
ArrayDomain(::Tuple{}) = ArrayDomain{0,Tuple{}}(())
ArrayDomain(xs...) = ArrayDomain((xs...,))
ArrayDomain(xs::Array) = ArrayDomain((xs...,))

Expand All @@ -31,6 +32,7 @@ chunks(a::ArrayDomain{N}) where {N} = DomainBlocks(

(==)(a::ArrayDomain, b::ArrayDomain) = indexes(a) == indexes(b)
Base.getindex(arr::AbstractArray, d::ArrayDomain) = arr[indexes(d)...]
Base.getindex(arr::AbstractArray{T,0} where T, d::ArrayDomain{0}) = arr

function intersect(a::ArrayDomain, b::ArrayDomain)
if a === b
Expand Down Expand Up @@ -145,7 +147,6 @@ const WrappedDVector{T} = WrappedDArray{T,1}
const DMatrix{T} = DArray{T,2}
const DVector{T} = DArray{T,1}


# mainly for backwards-compatibility
DArray{T, N}(domain, subdomains, chunks, partitioning, concat=cat) where {T,N} =
DArray(T, domain, subdomains, chunks, partitioning, concat)
Expand Down Expand Up @@ -178,6 +179,10 @@ function Base.collect(d::DArray; tree=false)
return Array{eltype(d)}(undef, size(d)...)
end

if ndims(d) == 0
return fetch(a.chunks[1])
end

dimcatfuncs = [(x...) -> d.concat(x..., dims=i) for i in 1:ndims(d)]
if tree
collect(fetch(treereduce_nd(map(x -> ((args...,) -> Dagger.@spawn x(args...)) , dimcatfuncs), a.chunks)))
Expand Down Expand Up @@ -214,6 +219,7 @@ else
Base.alignment(io::IO, x::ColorElement) =
Base.alignment(io, something(x.value, "..."))
#end
Base.show(io::IO, x::ColorElement) = show(io, MIME("text/plain"), x)
struct ColorArray{T,N} <: DenseArray{T,N}
A::DArray{T,N}
color_map::Vector{Symbol}
Expand Down Expand Up @@ -261,9 +267,21 @@ function Base.getindex(A::ColorArray{T,N}, idxs::Dims{S}) where {T,N,S}
end
end
function Base.show(io::IO, ::MIME"text/plain", A::DArray{T,N}) where {T,N}
write(io, string(DArray{T,N}))
write(io, string(size(A)))
write(io, " with $(join(size(A.chunks), 'x')) partitions of size $(join(A.partitioning.blocksize, 'x')):")
if N == 1
write(io, "$(length(A))-element ")
write(io, string(DVector{T}))
elseif N == 2
write(io, string(DMatrix{T}))
elseif N == 0
write(io, "0-dimensional ")
write(io, "DArray{$T, $N}")
else
write(io, "$(join(size(A), 'x')) ")
write(io, "DArray{$T, $N}")
end
nparts = N > 0 ? size(A.chunks) : 1
partsize = N > 0 ? A.partitioning.blocksize : 1
write(io, " with $(join(nparts, 'x')) partitions of size $(join(partsize, 'x')):")
pct_complete = 100 * (sum(c->c isa Chunk ? true : isready(c), A.chunks) / length(A.chunks))
if pct_complete < 100
println(io)
Expand Down Expand Up @@ -472,7 +490,7 @@ struct AutoBlocks end
function auto_blocks(dims::Dims{N}) where N
# TODO: Allow other partitioning schemes
np = num_processors()
p = cld(dims[end], np)
p = N > 0 ? cld(dims[end], np) : 1
return Blocks(ntuple(i->i == N ? p : dims[i], N))
end
auto_blocks(A::AbstractArray{T,N}) where {T,N} = auto_blocks(size(A))
Expand Down
42 changes: 32 additions & 10 deletions test/array/allocation.jl
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Original file line number Diff line number Diff line change
@@ -1,9 +1,16 @@
@testset "DVector/DMatrix/DArray constructor" begin
for T in [Float32, Float64, Int32, Int64]
F = fill(one(T))
V = rand(T, 64)
M = rand(T, 64, 64)
A = rand(T, 64, 64, 64)

# DArray ctor (empty)
DF = DArray(F, Blocks(()))
@test DF isa DArray{T,0}
@test collect(DF) == F
@test size(DF) == size(F)

# DVector ctor
DV = DVector(V, Blocks(8))
@test DV isa DVector{T}
Expand All @@ -26,7 +33,8 @@ end

@testset "random" begin
for T in [Float32, Float64, Int32, Int64]
for dims in [(100,),
for dims in [(),
(100,),
(100, 100),
(100, 100, 100)]
dist = Blocks(ntuple(i->10, length(dims))...)
Expand All @@ -53,10 +61,9 @@ end
@test AXn isa Array{T,length(dims)}
@test AXn == collect(Xn)
@test AXn != collect(randn(dist, T, dims...))
@test !all(AXn .> 0)
end

if length(dims) <= 2
if 1 <= length(dims) <= 2
# sprand
Xsp = sprand(dist, T, dims..., 0.1)
@test Xsp isa DArray{T,length(dims)}
Expand All @@ -76,7 +83,8 @@ end
@testset "ones/zeros" begin
for T in [Float32, Float64, Int32, Int64]
for (fn, value) in [(ones, one(T)), (zeros, zero(T))]
for dims in [(100,),
for dims in [(),
(100,),
(100, 100),
(100, 100, 100)]
dist = Blocks(ntuple(i->10, length(dims))...)
Expand Down Expand Up @@ -119,11 +127,16 @@ end
for i in 1:(length(dims)-1)
@test part_size[i] == 100
end
@test part_size[end] == cld(100, np)
if length(dims) > 0
@test part_size[end] == cld(100, np)
else
@test part_size == ()
end
@test size(DA) == ntuple(i->100, length(dims))
end

for dims in [(100,),
for dims in [(),
(100,),
(100, 100),
(100, 100, 100)]
fn = if length(dims) == 1
Expand All @@ -133,15 +146,23 @@ end
else
DArray
end
DA = fn(rand(dims...), AutoBlocks())
if length(dims) > 0
DA = fn(rand(dims...), AutoBlocks())
else
DA = fn(fill(rand()), AutoBlocks())
end
test_auto_blocks(DA, dims)

DA = distribute(rand(dims...), AutoBlocks())
if length(dims) > 0
DA = distribute(rand(dims...), AutoBlocks())
else
DA = distribute(fill(rand()), AutoBlocks())
end
test_auto_blocks(DA, dims)

for fn in [rand, randn, sprand, ones, zeros]
if fn === sprand
if length(dims) > 2
if length(dims) > 2 || length(dims) == 0
continue
end
DA = fn(AutoBlocks(), dims..., 0.1)
Expand All @@ -155,7 +176,8 @@ end

@testset "Constructor variants" begin
for fn in [ones, zeros, rand, randn, sprand]
for dims in [(100,),
for dims in [(),
(100,),
(100, 100),
(100, 100, 100)]
for dist in [Blocks(ntuple(i->10, length(dims))...),
Expand Down