Mercurial > repos > public > sbplib_julia

comparison test/LazyTensors/LazyTensors_test.jl @ 711:df88aee35bb9 feature/selectable_tests

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
Switch to _test.jl suffix
author Jonatan Werpers <jonatan@werpers.com>
date Sat, 20 Feb 2021 20:45:40 +0100
parents test/LazyTensors/testLazyTensors.jl@44fa9a171557
children
comparison
equal deleted inserted replaced
710:44fa9a171557 711:df88aee35bb9
1 using Test
2 using Sbplib.LazyTensors
3 using Sbplib.RegionIndices
4
5 using Tullio
6
7 @testset "LazyTensors" begin
8
9 @testset "Generic Mapping methods" begin
10 struct DummyMapping{T,R,D} <: TensorMapping{T,R,D} end
11 LazyTensors.apply(m::DummyMapping{T,R,D}, v, I::Vararg{Any,R}) where {T,R,D} = :apply
12 @test range_dim(DummyMapping{Int,2,3}()) == 2
13 @test domain_dim(DummyMapping{Int,2,3}()) == 3
14 @test apply(DummyMapping{Int,2,3}(), zeros(Int, (0,0,0)),0,0) == :apply
15 @test eltype(DummyMapping{Int,2,3}()) == Int
16 @test eltype(DummyMapping{Float64,2,3}()) == Float64
17 end
18
19 @testset "Mapping transpose" begin
20 struct DummyMapping{T,R,D} <: TensorMapping{T,R,D} end
21
22 LazyTensors.apply(m::DummyMapping{T,R}, v, I::Vararg{Any,R}) where {T,R} = :apply
23 LazyTensors.apply_transpose(m::DummyMapping{T,R,D}, v, I::Vararg{Any,D}) where {T,R,D} = :apply_transpose
24
25 LazyTensors.range_size(m::DummyMapping) = :range_size
26 LazyTensors.domain_size(m::DummyMapping) = :domain_size
27
28 m = DummyMapping{Float64,2,3}()
29 @test m' isa TensorMapping{Float64, 3,2}
30 @test m'' == m
31 @test apply(m',zeros(Float64,(0,0)), 0, 0, 0) == :apply_transpose
32 @test apply(m'',zeros(Float64,(0,0,0)), 0, 0) == :apply
33 @test apply_transpose(m', zeros(Float64,(0,0,0)), 0, 0) == :apply
34
35 @test range_size(m') == :domain_size
36 @test domain_size(m') == :range_size
37 end
38
39 @testset "TensorApplication" begin
40 struct SizeDoublingMapping{T,R,D} <: TensorMapping{T,R,D}
41 domain_size::NTuple{D,Int}
42 end
43
44 LazyTensors.apply(m::SizeDoublingMapping{T,R}, v, i::Vararg{Any,R}) where {T,R} = (:apply,v,i)
45 LazyTensors.range_size(m::SizeDoublingMapping) = 2 .* m.domain_size
46 LazyTensors.domain_size(m::SizeDoublingMapping) = m.domain_size
47
48
49 m = SizeDoublingMapping{Int, 1, 1}((3,))
50 v = [0,1,2]
51 @test m*v isa AbstractVector{Int}
52 @test size(m*v) == 2 .*size(v)
53 @test (m*v)[0] == (:apply,v,(0,))
54 @test m*m*v isa AbstractVector{Int}
55 @test (m*m*v)[1] == (:apply,m*v,(1,))
56 @test (m*m*v)[3] == (:apply,m*v,(3,))
57 @test (m*m*v)[6] == (:apply,m*v,(6,))
58 @test_broken BoundsError == (m*m*v)[0]
59 @test_broken BoundsError == (m*m*v)[7]
60 @test_throws MethodError m*m
61
62 m = SizeDoublingMapping{Int, 2, 1}((3,))
63 @test_throws MethodError m*ones(Int,2,2)
64 @test_throws MethodError m*m*v
65
66 m = SizeDoublingMapping{Float64, 2, 2}((3,3))
67 v = ones(3,3)
68 @test size(m*v) == 2 .*size(v)
69 @test (m*v)[1,2] == (:apply,v,(1,2))
70
71 struct ScalingOperator{T,D} <: TensorMapping{T,D,D}
72 λ::T
73 size::NTuple{D,Int}
74 end
75
76 LazyTensors.apply(m::ScalingOperator{T,D}, v, I::Vararg{Any,D}) where {T,D} = m.λ*v[I...]
77 LazyTensors.range_size(m::ScalingOperator) = m.size
78 LazyTensors.domain_size(m::ScalingOperator) = m.size
79
80 m = ScalingOperator{Int,1}(2,(3,))
81 v = [1,2,3]
82 @test m*v isa AbstractVector
83 @test m*v == [2,4,6]
84
85 m = ScalingOperator{Int,2}(2,(2,2))
86 v = [[1 2];[3 4]]
87 @test m*v == [[2 4];[6 8]]
88 @test (m*v)[2,1] == 6
89 end
90
91 @testset "TensorMapping binary operations" begin
92 struct ScalarMapping{T,R,D} <: TensorMapping{T,R,D}
93 λ::T
94 range_size::NTuple{R,Int}
95 domain_size::NTuple{D,Int}
96 end
97
98 LazyTensors.apply(m::ScalarMapping{T,R}, v, I::Vararg{Any,R}) where {T,R} = m.λ*v[I...]
99 LazyTensors.range_size(m::ScalarMapping) = m.domain_size
100 LazyTensors.domain_size(m::ScalarMapping) = m.range_size
101
102 A = ScalarMapping{Float64,1,1}(2.0, (3,), (3,))
103 B = ScalarMapping{Float64,1,1}(3.0, (3,), (3,))
104
105 v = [1.1,1.2,1.3]
106 for i ∈ eachindex(v)
107 @test ((A+B)*v)[i] == 2*v[i] + 3*v[i]
108 end
109
110 for i ∈ eachindex(v)
111 @test ((A-B)*v)[i] == 2*v[i] - 3*v[i]
112 end
113
114 @test range_size(A+B) == range_size(A) == range_size(B)
115 @test domain_size(A+B) == domain_size(A) == domain_size(B)
116 end
117
118 @testset "LazyArray" begin
119 @testset "LazyConstantArray" begin
120 @test LazyTensors.LazyConstantArray(3,(3,2)) isa LazyArray{Int,2}
121
122 lca = LazyTensors.LazyConstantArray(3.0,(3,2))
123 @test eltype(lca) == Float64
124 @test ndims(lca) == 2
125 @test size(lca) == (3,2)
126 @test lca[2] == 3.0
127 end
128 struct DummyArray{T,D, T1<:AbstractArray{T,D}} <: LazyArray{T,D}
129 data::T1
130 end
131 Base.size(v::DummyArray) = size(v.data)
132 Base.getindex(v::DummyArray{T,D}, I::Vararg{Int,D}) where {T,D} = v.data[I...]
133
134 # Test lazy operations
135 v1 = [1, 2.3, 4]
136 v2 = [1., 2, 3]
137 s = 3.4
138 r_add_v = v1 .+ v2
139 r_sub_v = v1 .- v2
140 r_times_v = v1 .* v2
141 r_div_v = v1 ./ v2
142 r_add_s = v1 .+ s
143 r_sub_s = v1 .- s
144 r_times_s = v1 .* s
145 r_div_s = v1 ./ s
146 @test isa(v1 +̃ v2, LazyArray)
147 @test isa(v1 -̃ v2, LazyArray)
148 @test isa(v1 *̃ v2, LazyArray)
149 @test isa(v1 /̃ v2, LazyArray)
150 @test isa(v1 +̃ s, LazyArray)
151 @test isa(v1 -̃ s, LazyArray)
152 @test isa(v1 *̃ s, LazyArray)
153 @test isa(v1 /̃ s, LazyArray)
154 @test isa(s +̃ v1, LazyArray)
155 @test isa(s -̃ v1, LazyArray)
156 @test isa(s *̃ v1, LazyArray)
157 @test isa(s /̃ v1, LazyArray)
158 for i ∈ eachindex(v1)
159 @test (v1 +̃ v2)[i] == r_add_v[i]
160 @test (v1 -̃ v2)[i] == r_sub_v[i]
161 @test (v1 *̃ v2)[i] == r_times_v[i]
162 @test (v1 /̃ v2)[i] == r_div_v[i]
163 @test (v1 +̃ s)[i] == r_add_s[i]
164 @test (v1 -̃ s)[i] == r_sub_s[i]
165 @test (v1 *̃ s)[i] == r_times_s[i]
166 @test (v1 /̃ s)[i] == r_div_s[i]
167 @test (s +̃ v1)[i] == r_add_s[i]
168 @test (s -̃ v1)[i] == -r_sub_s[i]
169 @test (s *̃ v1)[i] == r_times_s[i]
170 @test (s /̃ v1)[i] == 1/r_div_s[i]
171 end
172 @test_throws BoundsError (v1 +̃ v2)[4]
173 v2 = [1., 2, 3, 4]
174 # Test that size of arrays is asserted when not specified inbounds
175 # TODO: Replace these errors with SizeMismatch
176 @test_throws DimensionMismatch v1 +̃ v2
177
178 # Test operations on LazyArray
179 v1 = DummyArray([1, 2.3, 4])
180 v2 = [1., 2, 3]
181 @test isa(v1 + v2, LazyArray)
182 @test isa(v2 + v1, LazyArray)
183 @test isa(v1 - v2, LazyArray)
184 @test isa(v2 - v1, LazyArray)
185 for i ∈ eachindex(v2)
186 @test (v1 + v2)[i] == (v2 + v1)[i] == r_add_v[i]
187 @test (v1 - v2)[i] == -(v2 - v1)[i] == r_sub_v[i]
188 end
189 @test_throws BoundsError (v1 + v2)[4]
190 v2 = [1., 2, 3, 4]
191 # Test that size of arrays is asserted when not specified inbounds
192 # TODO: Replace these errors with SizeMismatch
193 @test_throws DimensionMismatch v1 + v2
194 end
195
196
197 @testset "LazyFunctionArray" begin
198 @test LazyFunctionArray(i->i^2, (3,)) == [1,4,9]
199 @test LazyFunctionArray((i,j)->i*j, (3,2)) == [
200 1 2;
201 2 4;
202 3 6;
203 ]
204
205 @test size(LazyFunctionArray(i->i^2, (3,))) == (3,)
206 @test size(LazyFunctionArray((i,j)->i*j, (3,2))) == (3,2)
207
208 @inferred LazyFunctionArray(i->i^2, (3,))[2]
209
210 @test_throws BoundsError LazyFunctionArray(i->i^2, (3,))[4]
211 @test_throws BoundsError LazyFunctionArray((i,j)->i*j, (3,2))[4,2]
212 @test_throws BoundsError LazyFunctionArray((i,j)->i*j, (3,2))[2,3]
213
214 end
215
216 @testset "TensorMappingComposition" begin
217 A = rand(2,3)
218 B = rand(3,4)
219
220 Ã = LazyLinearMap(A, (1,), (2,))
221 B̃ = LazyLinearMap(B, (1,), (2,))
222
223 @test Ã∘B̃ isa TensorMappingComposition
224 @test range_size(Ã∘B̃) == (2,)
225 @test domain_size(Ã∘B̃) == (4,)
226 @test_throws SizeMismatch B̃∘Ã
227
228 # @test @inbounds B̃∘Ã # Should not error even though dimensions don't match. (Since ]test runs with forced boundschecking this is currently not testable 2020-10-16)
229
230 v = rand(4)
231 @test Ã∘B̃*v ≈ A*B*v rtol=1e-14
232
233 v = rand(2)
234 @test (Ã∘B̃)'*v ≈ B'*A'*v rtol=1e-14
235 end
236
237 @testset "LazyLinearMap" begin
238 # Test a standard matrix-vector product
239 # mapping vectors of size 4 to vectors of size 3.
240 A = rand(3,4)
241 Ã = LazyLinearMap(A, (1,), (2,))
242 v = rand(4)
243 w = rand(3)
244
245 @test à isa LazyLinearMap{T,1,1} where T
246 @test à isa TensorMapping{T,1,1} where T
247 @test range_size(Ã) == (3,)
248 @test domain_size(Ã) == (4,)
249
250 @test Ã*ones(4) ≈ A*ones(4) atol=5e-13
251 @test Ã*v ≈ A*v atol=5e-13
252 @test Ã'*w ≈ A'*w
253
254 A = rand(2,3,4)
255 @test_throws DomainError LazyLinearMap(A, (3,1), (2,))
256
257 # Test more exotic mappings
258 B = rand(3,4,2)
259 # Map vectors of size 2 to matrices of size (3,4)
260 B̃ = LazyLinearMap(B, (1,2), (3,))
261 v = rand(2)
262
263 @test range_size(B̃) == (3,4)
264 @test domain_size(B̃) == (2,)
265 @test B̃ isa TensorMapping{T,2,1} where T
266 @test B̃*ones(2) ≈ B[:,:,1] + B[:,:,2] atol=5e-13
267 @test B̃*v ≈ B[:,:,1]*v[1] + B[:,:,2]*v[2] atol=5e-13
268
269 # Map matrices of size (3,2) to vectors of size 4
270 B̃ = LazyLinearMap(B, (2,), (1,3))
271 v = rand(3,2)
272
273 @test range_size(B̃) == (4,)
274 @test domain_size(B̃) == (3,2)
275 @test B̃ isa TensorMapping{T,1,2} where T
276 @test B̃*ones(3,2) ≈ B[1,:,1] + B[2,:,1] + B[3,:,1] +
277 B[1,:,2] + B[2,:,2] + B[3,:,2] atol=5e-13
278 @test B̃*v ≈ B[1,:,1]*v[1,1] + B[2,:,1]*v[2,1] + B[3,:,1]*v[3,1] +
279 B[1,:,2]v[1,2] + B[2,:,2]*v[2,2] + B[3,:,2]*v[3,2] atol=5e-13
280
281
282 # TODO:
283 # @inferred (B̃*v)[2]
284 end
285
286
287 @testset "IdentityMapping" begin
288 @test IdentityMapping{Float64}((4,5)) isa IdentityMapping{T,2} where T
289 @test IdentityMapping{Float64}((4,5)) isa TensorMapping{T,2,2} where T
290 @test IdentityMapping{Float64}((4,5)) == IdentityMapping{Float64}(4,5)
291
292 @test IdentityMapping(3,2) isa IdentityMapping{Float64,2}
293
294 for sz ∈ [(4,5),(3,),(5,6,4)]
295 I = IdentityMapping{Float64}(sz)
296 v = rand(sz...)
297 @test I*v == v
298 @test I'*v == v
299
300 @test range_size(I) == sz
301 @test domain_size(I) == sz
302 end
303
304 I = IdentityMapping{Float64}((4,5))
305 v = rand(4,5)
306 @inferred (I*v)[3,2]
307 @inferred (I'*v)[3,2]
308 @inferred range_size(I)
309
310 @inferred range_dim(I)
311 @inferred domain_dim(I)
312
313 Ã = rand(4,2)
314 A = LazyLinearMap(Ã,(1,),(2,))
315 I1 = IdentityMapping{Float64}(2)
316 I2 = IdentityMapping{Float64}(4)
317 @test A∘I1 == A
318 @test I2∘A == A
319 @test I1∘I1 == I1
320 @test_throws SizeMismatch I1∘A
321 @test_throws SizeMismatch A∘I2
322 @test_throws SizeMismatch I1∘I2
323 end
324
325 @testset "InflatedTensorMapping" begin
326 I(sz...) = IdentityMapping(sz...)
327
328 Ã = rand(4,2)
329 B̃ = rand(4,2,3)
330 C̃ = rand(4,2,3)
331
332 A = LazyLinearMap(Ã,(1,),(2,))
333 B = LazyLinearMap(B̃,(1,2),(3,))
334 C = LazyLinearMap(C̃,(1,),(2,3))
335
336 @testset "Constructors" begin
337 @test InflatedTensorMapping(I(3,2), A, I(4)) isa TensorMapping{Float64, 4, 4}
338 @test InflatedTensorMapping(I(3,2), B, I(4)) isa TensorMapping{Float64, 5, 4}
339 @test InflatedTensorMapping(I(3), C, I(2,3)) isa TensorMapping{Float64, 4, 5}
340 @test InflatedTensorMapping(C, I(2,3)) isa TensorMapping{Float64, 3, 4}
341 @test InflatedTensorMapping(I(3), C) isa TensorMapping{Float64, 2, 3}
342 @test InflatedTensorMapping(I(3), I(2,3)) isa TensorMapping{Float64, 3, 3}
343 end
344
345 @testset "Range and domain size" begin
346 @test range_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,4,4)
347 @test domain_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,2,4)
348
349 @test range_size(InflatedTensorMapping(I(3,2), B, I(4))) == (3,2,4,2,4)
350 @test domain_size(InflatedTensorMapping(I(3,2), B, I(4))) == (3,2,3,4)
351
352 @test range_size(InflatedTensorMapping(I(3), C, I(2,3))) == (3,4,2,3)
353 @test domain_size(InflatedTensorMapping(I(3), C, I(2,3))) == (3,2,3,2,3)
354
355 @inferred range_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,4,4)
356 @inferred domain_size(InflatedTensorMapping(I(3,2), A, I(4))) == (3,2,2,4)
357 end
358
359 @testset "Application" begin
360 # Testing regular application and transposed application with inflation "before", "after" and "before and after".
361 # The inflated tensor mappings are chosen to preserve, reduce and increase the dimension of the result compared to the input.
362 tests = [
363 (
364 InflatedTensorMapping(I(3,2), A, I(4)),
365 (v-> @tullio res[a,b,c,d] := Ã[c,i]*v[a,b,i,d]), # Expected result of apply
366 (v-> @tullio res[a,b,c,d] := Ã[i,c]*v[a,b,i,d]), # Expected result of apply_transpose
367 ),
368 (
369 InflatedTensorMapping(I(3,2), B, I(4)),
370 (v-> @tullio res[a,b,c,d,e] := B̃[c,d,i]*v[a,b,i,e]),
371 (v-> @tullio res[a,b,c,d] := B̃[i,j,c]*v[a,b,i,j,d]),
372 ),
373 (
374 InflatedTensorMapping(I(3,2), C, I(4)),
375 (v-> @tullio res[a,b,c,d] := C̃[c,i,j]*v[a,b,i,j,d]),
376 (v-> @tullio res[a,b,c,d,e] := C̃[i,c,d]*v[a,b,i,e]),
377 ),
378 (
379 InflatedTensorMapping(I(3,2), A),
380 (v-> @tullio res[a,b,c] := Ã[c,i]*v[a,b,i]),
381 (v-> @tullio res[a,b,c] := Ã[i,c]*v[a,b,i]),
382 ),
383 (
384 InflatedTensorMapping(I(3,2), B),
385 (v-> @tullio res[a,b,c,d] := B̃[c,d,i]*v[a,b,i]),
386 (v-> @tullio res[a,b,c] := B̃[i,j,c]*v[a,b,i,j]),
387 ),
388 (
389 InflatedTensorMapping(I(3,2), C),
390 (v-> @tullio res[a,b,c] := C̃[c,i,j]*v[a,b,i,j]),
391 (v-> @tullio res[a,b,c,d] := C̃[i,c,d]*v[a,b,i]),
392 ),
393 (
394 InflatedTensorMapping(A,I(4)),
395 (v-> @tullio res[a,b] := Ã[a,i]*v[i,b]),
396 (v-> @tullio res[a,b] := Ã[i,a]*v[i,b]),
397 ),
398 (
399 InflatedTensorMapping(B,I(4)),
400 (v-> @tullio res[a,b,c] := B̃[a,b,i]*v[i,c]),
401 (v-> @tullio res[a,b] := B̃[i,j,a]*v[i,j,b]),
402 ),
403 (
404 InflatedTensorMapping(C,I(4)),
405 (v-> @tullio res[a,b] := C̃[a,i,j]*v[i,j,b]),
406 (v-> @tullio res[a,b,c] := C̃[i,a,b]*v[i,c]),
407 ),
408 ]
409
410 @testset "apply" begin
411 for i ∈ 1:length(tests)
412 tm = tests[i][1]
413 v = rand(domain_size(tm)...)
414 true_value = tests[i][2](v)
415 @test tm*v ≈ true_value rtol=1e-14
416 end
417 end
418
419 @testset "apply_transpose" begin
420 for i ∈ 1:length(tests)
421 tm = tests[i][1]
422 v = rand(range_size(tm)...)
423 true_value = tests[i][3](v)
424 @test tm'*v ≈ true_value rtol=1e-14
425 end
426 end
427
428 @testset "Inference of application" begin
429 struct ScalingOperator{T,D} <: TensorMapping{T,D,D}
430 λ::T
431 size::NTuple{D,Int}
432 end
433
434 LazyTensors.apply(m::ScalingOperator{T,D}, v, I::Vararg{Any,D}) where {T,D} = m.λ*v[I...]
435 LazyTensors.range_size(m::ScalingOperator) = m.size
436 LazyTensors.domain_size(m::ScalingOperator) = m.size
437
438 tm = InflatedTensorMapping(I(2,3),ScalingOperator(2.0, (3,2)),I(3,4))
439 v = rand(domain_size(tm)...)
440
441 @inferred apply(tm,v,1,2,3,2,2,4)
442 @inferred (tm*v)[1,2,3,2,2,4]
443 end
444 end
445
446 @testset "InflatedTensorMapping of InflatedTensorMapping" begin
447 A = ScalingOperator(2.0,(2,3))
448 itm = InflatedTensorMapping(I(3,2), A, I(4))
449 @test InflatedTensorMapping(I(4), itm, I(2)) == InflatedTensorMapping(I(4,3,2), A, I(4,2))
450 @test InflatedTensorMapping(itm, I(2)) == InflatedTensorMapping(I(3,2), A, I(4,2))
451 @test InflatedTensorMapping(I(4), itm) == InflatedTensorMapping(I(4,3,2), A, I(4))
452
453 @test InflatedTensorMapping(I(2), I(2), I(2)) isa InflatedTensorMapping # The constructor should always return its type.
454 end
455 end
456
457 @testset "split_index" begin
458 @test LazyTensors.split_index(Val(2),Val(1),Val(2),Val(2),1,2,3,4,5,6) == ((1,2,:,5,6),(3,4))
459 @test LazyTensors.split_index(Val(2),Val(3),Val(2),Val(2),1,2,3,4,5,6) == ((1,2,:,:,:,5,6),(3,4))
460 @test LazyTensors.split_index(Val(3),Val(1),Val(1),Val(2),1,2,3,4,5,6) == ((1,2,3,:,5,6),(4,))
461 @test LazyTensors.split_index(Val(3),Val(2),Val(1),Val(2),1,2,3,4,5,6) == ((1,2,3,:,:,5,6),(4,))
462 @test LazyTensors.split_index(Val(1),Val(1),Val(2),Val(3),1,2,3,4,5,6) == ((1,:,4,5,6),(2,3))
463 @test LazyTensors.split_index(Val(1),Val(2),Val(2),Val(3),1,2,3,4,5,6) == ((1,:,:,4,5,6),(2,3))
464
465 @test LazyTensors.split_index(Val(0),Val(1),Val(3),Val(3),1,2,3,4,5,6) == ((:,4,5,6),(1,2,3))
466 @test LazyTensors.split_index(Val(3),Val(1),Val(3),Val(0),1,2,3,4,5,6) == ((1,2,3,:),(4,5,6))
467
468 @inferred LazyTensors.split_index(Val(2),Val(3),Val(2),Val(2),1,2,3,2,2,4)
469 end
470
471 @testset "slice_tuple" begin
472 @test LazyTensors.slice_tuple((1,2,3),Val(1), Val(3)) == (1,2,3)
473 @test LazyTensors.slice_tuple((1,2,3,4,5,6),Val(2), Val(5)) == (2,3,4,5)
474 @test LazyTensors.slice_tuple((1,2,3,4,5,6),Val(1), Val(3)) == (1,2,3)
475 @test LazyTensors.slice_tuple((1,2,3,4,5,6),Val(4), Val(6)) == (4,5,6)
476 end
477
478 @testset "split_tuple" begin
479 @testset "2 parts" begin
480 @test LazyTensors.split_tuple((),Val(0)) == ((),())
481 @test LazyTensors.split_tuple((1,),Val(0)) == ((),(1,))
482 @test LazyTensors.split_tuple((1,),Val(1)) == ((1,),())
483
484 @test LazyTensors.split_tuple((1,2,3,4),Val(0)) == ((),(1,2,3,4))
485 @test LazyTensors.split_tuple((1,2,3,4),Val(1)) == ((1,),(2,3,4))
486 @test LazyTensors.split_tuple((1,2,3,4),Val(2)) == ((1,2),(3,4))
487 @test LazyTensors.split_tuple((1,2,3,4),Val(3)) == ((1,2,3),(4,))
488 @test LazyTensors.split_tuple((1,2,3,4),Val(4)) == ((1,2,3,4),())
489
490 @test LazyTensors.split_tuple((1,2,true,4),Val(3)) == ((1,2,true),(4,))
491
492 @inferred LazyTensors.split_tuple((1,2,3,4),Val(3))
493 @inferred LazyTensors.split_tuple((1,2,true,4),Val(3))
494 end
495
496 @testset "3 parts" begin
497 @test LazyTensors.split_tuple((),Val(0),Val(0)) == ((),(),())
498 @test LazyTensors.split_tuple((1,2,3),Val(1), Val(1)) == ((1,),(2,),(3,))
499 @test LazyTensors.split_tuple((1,true,3),Val(1), Val(1)) == ((1,),(true,),(3,))
500
501 @test LazyTensors.split_tuple((1,2,3,4,5,6),Val(1),Val(2)) == ((1,),(2,3),(4,5,6))
502 @test LazyTensors.split_tuple((1,2,3,4,5,6),Val(3),Val(2)) == ((1,2,3),(4,5),(6,))
503
504 @inferred LazyTensors.split_tuple((1,2,3,4,5,6),Val(3),Val(2))
505 @inferred LazyTensors.split_tuple((1,true,3),Val(1), Val(1))
506 end
507 end
508
509 @testset "flatten_tuple" begin
510 @test LazyTensors.flatten_tuple((1,)) == (1,)
511 @test LazyTensors.flatten_tuple((1,2,3,4,5,6)) == (1,2,3,4,5,6)
512 @test LazyTensors.flatten_tuple((1,2,(3,4),5,6)) == (1,2,3,4,5,6)
513 @test LazyTensors.flatten_tuple((1,2,(3,(4,5)),6)) == (1,2,3,4,5,6)
514 @test LazyTensors.flatten_tuple(((1,2),(3,4),(5,),6)) == (1,2,3,4,5,6)
515 end
516
517
518 @testset "LazyOuterProduct" begin
519 struct ScalingOperator{T,D} <: TensorMapping{T,D,D}
520 λ::T
521 size::NTuple{D,Int}
522 end
523
524 LazyTensors.apply(m::ScalingOperator{T,D}, v, I::Vararg{Any,D}) where {T,D} = m.λ*v[I...]
525 LazyTensors.range_size(m::ScalingOperator) = m.size
526 LazyTensors.domain_size(m::ScalingOperator) = m.size
527
528 A = ScalingOperator(2.0, (5,))
529 B = ScalingOperator(3.0, (3,))
530 C = ScalingOperator(5.0, (3,2))
531
532 AB = LazyOuterProduct(A,B)
533 @test AB isa TensorMapping{T,2,2} where T
534 @test range_size(AB) == (5,3)
535 @test domain_size(AB) == (5,3)
536
537 v = rand(range_size(AB)...)
538 @test AB*v == 6*v
539
540 ABC = LazyOuterProduct(A,B,C)
541
542 @test ABC isa TensorMapping{T,4,4} where T
543 @test range_size(ABC) == (5,3,3,2)
544 @test domain_size(ABC) == (5,3,3,2)
545
546 @test A⊗B == AB
547 @test A⊗B⊗C == ABC
548
549 A = rand(3,2)
550 B = rand(2,4,3)
551
552 v₁ = rand(2,4,3)
553 v₂ = rand(4,3,2)
554
555 Ã = LazyLinearMap(A,(1,),(2,))
556 B̃ = LazyLinearMap(B,(1,),(2,3))
557
558 ÃB̃ = LazyOuterProduct(Ã,B̃)
559 @tullio ABv[i,k] := A[i,j]*B[k,l,m]*v₁[j,l,m]
560 @test ÃB̃*v₁ ≈ ABv
561
562 B̃Ã = LazyOuterProduct(B̃,Ã)
563 @tullio BAv[k,i] := A[i,j]*B[k,l,m]*v₂[l,m,j]
564 @test B̃Ã*v₂ ≈ BAv
565
566 @testset "Indentity mapping arguments" begin
567 @test LazyOuterProduct(IdentityMapping(3,2), IdentityMapping(1,2)) == IdentityMapping(3,2,1,2)
568
569 Ã = LazyLinearMap(A,(1,),(2,))
570 @test LazyOuterProduct(IdentityMapping(3,2), Ã) == InflatedTensorMapping(IdentityMapping(3,2),Ã)
571 @test LazyOuterProduct(Ã, IdentityMapping(3,2)) == InflatedTensorMapping(Ã,IdentityMapping(3,2))
572
573 I1 = IdentityMapping(3,2)
574 I2 = IdentityMapping(4)
575 @test I1⊗Ã⊗I2 == InflatedTensorMapping(I1, Ã, I2)
576 end
577
578 end
579
580 end