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Revert "Improve GPU functionality (#780)"
This reverts commit 2b2b380.
1 parent 2b2b380 commit 317e089

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+45
-347
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5 files changed

+45
-347
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‎Project.toml

+1-3
Original file line numberDiff line numberDiff line change
@@ -54,7 +54,6 @@ Interfaces = "0.3"
5454
IntervalSets = "0.5, 0.6, 0.7"
5555
InvertedIndices = "1"
5656
IteratorInterfaceExtensions = "1"
57-
JLArrays = "0.1"
5857
LinearAlgebra = "1"
5958
Makie = "0.19, 0.20, 0.21"
6059
OffsetArrays = "1"
@@ -86,7 +85,6 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
8685
Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
8786
ImageFiltering = "6a3955dd-da59-5b1f-98d4-e7296123deb5"
8887
ImageTransformations = "02fcd773-0e25-5acc-982a-7f6622650795"
89-
JLArrays = "27aeb0d3-9eb9-45fb-866b-73c2ecf80fcb"
9088
Makie = "ee78f7c6-11fb-53f2-987a-cfe4a2b5a57a"
9189
OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
9290
Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
@@ -97,4 +95,4 @@ Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
9795
Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
9896

9997
[targets]
100-
test = ["Aqua", "ArrayInterface", "BenchmarkTools", "CategoricalArrays", "ColorTypes", "Combinatorics", "CoordinateTransformations", "DataFrames", "Distributions", "Documenter", "ImageFiltering", "ImageTransformations", "JLArrays", "CairoMakie", "OffsetArrays", "Plots", "Random", "SafeTestsets", "StatsPlots", "Test", "Unitful"]
98+
test = ["Aqua", "ArrayInterface", "BenchmarkTools", "CategoricalArrays", "ColorTypes", "Combinatorics", "CoordinateTransformations", "DataFrames", "Distributions", "Documenter", "ImageFiltering", "ImageTransformations", "CairoMakie", "OffsetArrays", "Plots", "Random", "SafeTestsets", "StatsPlots", "Test", "Unitful"]

‎src/array/broadcast.jl

+16-14
Original file line numberDiff line numberDiff line change
@@ -47,24 +47,26 @@ function Broadcast.copy(bc::Broadcasted{DimensionalStyle{S}}) where S
4747
end
4848

4949
function Base.copyto!(dest::AbstractArray, bc::Broadcasted{DimensionalStyle{S}}) where S
50-
#TODO: this will cause a comparisson to happen twice. We should avoid that
51-
comparedims(dims(dest), _broadcasted_dims(bc); ignore_length_one=true, order=true)
50+
_dims = comparedims(dims(dest), _broadcasted_dims(bc); ignore_length_one=true, order=true)
5251
copyto!(dest, _unwrap_broadcasted(bc))
53-
return dest
52+
A = _firstdimarray(bc)
53+
if A isa Nothing || _dims isa Nothing
54+
dest
55+
else
56+
rebuild(A, dest, _dims, refdims(A))
57+
end
5458
end
55-
56-
57-
@inline function Base.Broadcast.materialize!(dest::AbstractDimArray, bc::Base.Broadcast.Broadcasted{<:Any})
58-
# needed because we need to check whether the dims are compatible in dest which are already
59-
# stripped when sent to copyto!
60-
comparedims(dims(dest), _broadcasted_dims(bc); ignore_length_one=true, order=true)
61-
style = DimensionalData.DimensionalStyle(Base.Broadcast.combine_styles(parent(dest), bc))
62-
Base.Broadcast.materialize!(style, parent(dest), bc)
63-
return dest
59+
function Base.copyto!(dest::AbstractDimArray, bc::Broadcasted{DimensionalStyle{S}}) where S
60+
_dims = comparedims(dims(dest), _broadcasted_dims(bc); ignore_length_one=true, order=true)
61+
copyto!(parent(dest), _unwrap_broadcasted(bc))
62+
A = _firstdimarray(bc)
63+
if A isa Nothing || _dims isa Nothing
64+
dest
65+
else
66+
rebuild(A, parent(dest), _dims, refdims(A))
67+
end
6468
end
6569

66-
67-
6870
function Base.similar(bc::Broadcast.Broadcasted{DimensionalStyle{S}}, ::Type{T}) where {S,T}
6971
A = _firstdimarray(bc)
7072
rebuildsliced(A, similar(_unwrap_broadcasted(bc), T, axes(bc)...), axes(bc), Symbol(""))

‎src/array/methods.jl

+19-3
Original file line numberDiff line numberDiff line change
@@ -53,9 +53,25 @@ for (m, f) in ((:Statistics, :median), (:Base, :any), (:Base, :all))
5353
end
5454
end
5555

56-
function Base.mapreduce(f, op, A::AbstractDimArray; dims=Base.Colon(), kw...)
57-
dims === Colon() && return mapreduce(f, op, parent(A); kw...)
58-
rebuild(A, mapreduce(f, op, parent(A); dims=dimnum(A, dims), kw...), reducedims(A, dims))
56+
# These are not exported but it makes a lot of things easier using them
57+
function Base._mapreduce_dim(f, op, nt::NamedTuple{(),<:Tuple}, A::AbstractDimArray, dims)
58+
rebuild(A, Base._mapreduce_dim(f, op, nt, parent(A), dimnum(A, _astuple(dims))), reducedims(A, dims))
59+
end
60+
function Base._mapreduce_dim(f, op, nt::NamedTuple{(),<:Tuple}, A::AbstractDimArray, dims::Colon)
61+
Base._mapreduce_dim(f, op, nt, parent(A), dims)
62+
end
63+
function Base._mapreduce_dim(f, op, nt, A::AbstractDimArray, dims)
64+
rebuild(A, Base._mapreduce_dim(f, op, nt, parent(A), dimnum(A, dims)), reducedims(A, dims))
65+
end
66+
function Base._mapreduce_dim(f, op, nt, A::AbstractDimArray, dims::Colon)
67+
rebuild(A, Base._mapreduce_dim(f, op, nt, parent(A), dimnum(A, dims)), reducedims(A, dims))
68+
end
69+
70+
function Base._mapreduce_dim(f, op, nt::Base._InitialValue, A::AbstractDimArray, dims)
71+
rebuild(A, Base._mapreduce_dim(f, op, nt, parent(A), dimnum(A, dims)), reducedims(A, dims))
72+
end
73+
function Base._mapreduce_dim(f, op, nt::Base._InitialValue, A::AbstractDimArray, dims::Colon)
74+
Base._mapreduce_dim(f, op, nt, parent(A), dims)
5975
end
6076

6177

‎test/broadcast.jl

+6-112
Original file line numberDiff line numberDiff line change
@@ -1,11 +1,10 @@
11
using DimensionalData, Test
2-
using JLArrays
2+
33
using DimensionalData: NoLookup
44

55
# Tests taken from NamedDims. Thanks @oxinabox
66

77
da = ones(X(3))
8-
dajl = rebuild(da, JLArray(parent(da)));
98
@test Base.BroadcastStyle(typeof(da)) isa DimensionalData.DimensionalStyle
109

1110
@testset "standard case" begin
@@ -20,35 +19,18 @@ end
2019
@test da2 .* da2[:, 1:1] == [1, 4, 9, 16] * (1:2:8)'
2120
end
2221

23-
@testset "JLArray broadcast over length one dimension" begin
24-
da2 = DimArray(JLArray((1:4) * (1:2:8)'), (X, Y))
25-
@test Array(da2 .* da2[:, 1:1]) == [1, 4, 9, 16] * (1:2:8)'
26-
end
27-
2822
@testset "in place" begin
2923
@test parent(da .= 1 .* da .+ 7) == 8 * ones(3)
3024
@test dims(da .= 1 .* da .+ 7) == dims(da)
3125
end
3226

33-
@testset "JLArray in place" begin
34-
@test Array(parent(dajl .= 1 .* dajl .+ 7)) == 8 * ones(3)
35-
@test dims(dajl .= 1 .* dajl .+ 7) == dims(da)
36-
end
37-
3827
@testset "Dimension disagreement" begin
3928
@test_throws DimensionMismatch begin
4029
DimArray(zeros(3, 3, 3), (X, Y, Z)) .+
4130
DimArray(ones(3, 3, 3), (Y, Z, X))
4231
end
4332
end
4433

45-
@testset "JLArray Dimension disagreement" begin
46-
@test_throws DimensionMismatch begin
47-
DimArray(JLArray(zeros(3, 3, 3)), (X, Y, Z)) .+
48-
DimArray(JLArray(ones(3, 3, 3)), (Y, Z, X))
49-
end
50-
end
51-
5234
@testset "dims and regular" begin
5335
da = DimArray(ones(3, 3, 3), (X, Y, Z))
5436
left_sum = da .+ ones(3, 3, 3)
@@ -59,16 +41,6 @@ end
5941
@test dims(right_sum) == dims(da)
6042
end
6143

62-
@testset "JLArray dims and regular" begin
63-
da = DimArray(JLArray(ones(3, 3, 3)), (X, Y, Z))
64-
left_sum = da .+ ones(3, 3, 3)
65-
@test Array(left_sum) == fill(2, 3, 3, 3)
66-
@test dims(left_sum) == dims(da)
67-
right_sum = ones(3, 3, 3) .+ da
68-
@test Array(right_sum) == fill(2, 3, 3, 3)
69-
@test dims(right_sum) == dims(da)
70-
end
71-
7244
@testset "changing type" begin
7345
@test (da .> 0) isa DimArray
7446
@test (da .* da .> 0) isa DimArray
@@ -79,16 +51,6 @@ end
7951
@test (rand(3) .> 1 .> 0 .* da) isa DimArray
8052
end
8153

82-
@testset "JLArray changing type" begin
83-
@test (dajl .> 0) isa DimArray
84-
@test (dajl .* dajl .> 0) isa DimArray
85-
@test (dajl .> 0 .> rand(3)) isa DimArray
86-
@test (dajl .* rand(3) .> 0.0) isa DimArray
87-
@test (0 .> dajl .> 0 .> rand(3)) isa DimArray
88-
@test (rand(3) .> dajl .> 0 .* rand(3)) isa DimArray
89-
@test (rand(3) .> 1 .> 0 .* dajl) isa DimArray
90-
end
91-
9254
@testset "trailng dimensions" begin
9355
@test zeros(X(10), Y(5)) .* zeros(X(10), Y(1)) ==
9456
zeros(X(10), Y(5)) .* zeros(X(1), Y(1)) ==
@@ -117,18 +79,6 @@ end
11779
@test dims(s .+ v .+ m) == dims(m .+ s .+ v)
11880
end
11981

120-
@testset "JLArray broadcasting" begin
121-
v = DimArray(JLArray(zeros(3,)), X)
122-
m = DimArray(JLArray(ones(3, 3)), (X, Y))
123-
s = 0
124-
@test Array(v .+ m) == ones(3, 3) == Array(m .+ v)
125-
@test Array(s .+ m) == ones(3, 3) == Array(m .+ s)
126-
@test Array(s .+ v .+ m) == ones(3, 3) == Array(m .+ s .+ v)
127-
@test dims(v .+ m) == dims(m .+ v)
128-
@test dims(s .+ m) == dims(m .+ s)
129-
@test dims(s .+ v .+ m) == dims(m .+ s .+ v)
130-
end
131-
13282
@testset "adjoint broadcasting" begin
13383
a = DimArray(reshape(1:12, (4, 3)), (X, Y))
13484
b = DimArray(1:3, Y)
@@ -138,17 +88,6 @@ end
13888
@test dims(a .* b') == dims(a)
13989
end
14090

141-
@testset "JLArray adjoint broadcasting" begin
142-
a = DimArray(JLArray(reshape(1:12, (4, 3))), (X, Y))
143-
b = DimArray(JLArray(1:3), Y)
144-
@test_throws DimensionMismatch a .* b
145-
@test_throws DimensionMismatch parent(a) .* parent(b)
146-
@test Array(parent(a) .* parent(b)') == Array(parent(a .* b'))
147-
@test dims(a .* b') == dims(a)
148-
end
149-
150-
151-
15291
@testset "Mixed array types" begin
15392
casts = (
15493
A -> DimArray(A, (X, Y)), # Named Matrix
@@ -182,26 +121,13 @@ end
182121
@test_throws DimensionMismatch ac .= ab .+ ba
183122

184123
# check that dest is written into:
185-
z .= ab .+ ba'
124+
@test dims(z .= ab .+ ba') == dims(ab .+ ba')
186125
@test z == (ab.data .+ ba.data')
187-
end
188126

189-
@testset "JLArray in-place assignment .=" begin
190-
ab = DimArray(JLArray(rand(2,2)), (X, Y))
191-
ba = DimArray(JLArray(rand(2,2)), (Y, X))
192-
ac = DimArray(JLArray(rand(2,2)), (X, Z))
193-
a_ = DimArray(JLArray(rand(2,2)), (X(), DimensionalData.AnonDim()))
194-
z = JLArray(zeros(2,2))
195-
196-
@test_throws DimensionMismatch z .= ab .+ ba
197-
@test_throws DimensionMismatch z .= ab .+ ac
198-
@test_throws DimensionMismatch a_ .= ab .+ ac
199-
@test_throws DimensionMismatch ab .= a_ .+ ac
200-
@test_throws DimensionMismatch ac .= ab .+ ba
201-
202-
# check that dest is written into:
203-
z .= ab .+ ba'
204-
@test z == (ab.data .+ ba.data')
127+
@test dims(z .= ab .+ a_) ==
128+
(X(NoLookup(Base.OneTo(2))), Y(NoLookup(Base.OneTo(2))))
129+
@test dims(a_ .= ba' .+ ab) ==
130+
(X(NoLookup(Base.OneTo(2))), Y(NoLookup(Base.OneTo(2))))
205131
end
206132

207133
@testset "assign using named indexing and dotview" begin
@@ -211,13 +137,6 @@ end
211137
@test A == [1.0 1.0; 2.0 2.0; 7.0 7.0]
212138
end
213139

214-
@testset "JLArray assign using named indexing and dotview" begin
215-
A = DimArray(JLArray(zeros(3,2)), (X, Y))
216-
A[X=1:2] .= JLArray([1, 2])
217-
A[X=3] .= 7
218-
@test Array(A) == [1.0 1.0; 2.0 2.0; 7.0 7.0]
219-
end
220-
221140
@testset "0-dimensional array broadcasting" begin
222141
x = DimArray(fill(3), ())
223142
y = DimArray(fill(4), ())
@@ -249,31 +168,6 @@ end
249168
@test A[DimSelectors(sub)] == C[DimSelectors(sub)]
250169
end
251170

252-
@testset "JLArray DimIndices broadcasting" begin
253-
ds = X(1.0:0.2:2.0), Y(10:2:20)
254-
_A = (rand(ds))
255-
_B = (zeros(ds))
256-
_C = (zeros(ds))
257-
258-
A = rebuild(_A, JLArray(parent(_A)))
259-
B = rebuild(_B, JLArray(parent(_B)))
260-
C = rebuild(_C, JLArray(parent(_C)))
261-
262-
B[DimIndices(B)] .+= A
263-
C[DimSelectors(C)] .+= A
264-
@test Array(A) == Array(B) == Array(C)
265-
sub = A[1:4, 1:3]
266-
B .= 0
267-
C .= 0
268-
B[DimIndices(sub)] .+= sub
269-
C[DimSelectors(sub)] .+= sub
270-
@test Array(A[DimIndices(sub)]) == Array(B[DimIndices(sub)]) == Array(C[DimIndices(sub)])
271-
sub = A[2:4, 2:5]
272-
C .= 0
273-
C[DimSelectors(sub)] .+= sub
274-
@test Array(A[DimSelectors(sub)]) == Array(C[DimSelectors(sub)])
275-
end
276-
277171
# @testset "Competing Wrappers" begin
278172
# da = DimArray(ones(4), X)
279173
# ta = TrackedArray(5 * ones(4))

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