-
Notifications
You must be signed in to change notification settings - Fork 5
/
Copy path1.6.0-DEV-22b5d93b2b.log
1232 lines (1180 loc) · 58.6 KB
/
1.6.0-DEV-22b5d93b2b.log
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
Julia Version 1.6.0-DEV.1069
Commit 22b5d93b2b (2020-09-28 17:33 UTC)
Platform Info:
OS: Linux (x86_64-linux-gnu)
CPU: Intel(R) Xeon(R) Silver 4114 CPU @ 2.20GHz
WORD_SIZE: 64
LIBM: libopenlibm
LLVM: libLLVM-10.0.1 (ORCJIT, skylake-avx512)
Environment:
JULIA_DEPOT_PATH = ::/usr/local/share/julia
JULIA_NUM_THREADS = 2
Resolving package versions...
Installed CodecZlib ──────────────────── v0.7.0
Installed Zlib_jll ───────────────────── v1.2.11+16
Installed Zstd_jll ───────────────────── v1.4.5+1
Installed Blosc_jll ──────────────────── v1.14.3+1
Installed Compat ─────────────────────── v3.17.0
Installed TranscodingStreams ─────────── v0.9.5
Installed FFTW ───────────────────────── v1.2.4
Installed HDF5 ───────────────────────── v0.13.6
Installed Conda ──────────────────────── v1.4.1
Installed CompilerSupportLibraries_jll ─ v0.3.3+0
Installed VersionParsing ─────────────── v1.2.0
Installed BufferedStreams ────────────── v1.0.0
Installed HDF5_jll ───────────────────── v1.10.5+6
Installed AbstractFFTs ───────────────── v0.5.0
Installed FFTW_jll ───────────────────── v3.3.9+5
Installed URIParser ──────────────────── v0.4.1
Installed SpecialFunctions ───────────── v0.10.3
Installed OpenSpecFun_jll ────────────── v0.5.3+3
Installed Parsers ────────────────────── v1.0.10
Installed Reexport ───────────────────── v0.2.0
Installed JSON ───────────────────────── v0.21.1
Installed IntelOpenMP_jll ────────────── v2018.0.3+0
Installed MacroTools ─────────────────── v0.5.5
Installed Blosc ──────────────────────── v0.7.0
Installed BinDeps ────────────────────── v1.0.1
Installed CMake ──────────────────────── v1.2.0
Installed MAT ────────────────────────── v0.8.1
Installed Lz4_jll ────────────────────── v1.9.2+2
Installed MKL_jll ────────────────────── v2020.2.254+0
Installed ADCME ──────────────────────── v0.5.12
Installed PyCall ─────────────────────── v1.92.0
Updating `~/.julia/environments/v1.6/Project.toml`
[07b341a0] + ADCME v0.5.12
Updating `~/.julia/environments/v1.6/Manifest.toml`
[07b341a0] + ADCME v0.5.12
[621f4979] + AbstractFFTs v0.5.0
[9e28174c] + BinDeps v1.0.1
[a74b3585] + Blosc v0.7.0
[0b7ba130] + Blosc_jll v1.14.3+1
[e1450e63] + BufferedStreams v1.0.0
[631607c0] + CMake v1.2.0
[944b1d66] + CodecZlib v0.7.0
[34da2185] + Compat v3.17.0
[e66e0078] + CompilerSupportLibraries_jll v0.3.3+0
[8f4d0f93] + Conda v1.4.1
[7a1cc6ca] + FFTW v1.2.4
[f5851436] + FFTW_jll v3.3.9+5
[f67ccb44] + HDF5 v0.13.6
[0234f1f7] + HDF5_jll v1.10.5+6
[1d5cc7b8] + IntelOpenMP_jll v2018.0.3+0
[682c06a0] + JSON v0.21.1
[5ced341a] + Lz4_jll v1.9.2+2
[23992714] + MAT v0.8.1
[856f044c] + MKL_jll v2020.2.254+0
[1914dd2f] + MacroTools v0.5.5
[efe28fd5] + OpenSpecFun_jll v0.5.3+3
[69de0a69] + Parsers v1.0.10
[438e738f] + PyCall v1.92.0
[189a3867] + Reexport v0.2.0
[276daf66] + SpecialFunctions v0.10.3
[3bb67fe8] + TranscodingStreams v0.9.5
[30578b45] + URIParser v0.4.1
[81def892] + VersionParsing v1.2.0
[83775a58] + Zlib_jll v1.2.11+16
[3161d3a3] + Zstd_jll v1.4.5+1
[56f22d72] + Artifacts
[2a0f44e3] + Base64
[ade2ca70] + Dates
[8bb1440f] + DelimitedFiles
[8ba89e20] + Distributed
[b77e0a4c] + InteractiveUtils
[76f85450] + LibGit2
[8f399da3] + Libdl
[37e2e46d] + LinearAlgebra
[56ddb016] + Logging
[d6f4376e] + Markdown
[a63ad114] + Mmap
[44cfe95a] + Pkg
[de0858da] + Printf
[3fa0cd96] + REPL
[9a3f8284] + Random
[ea8e919c] + SHA
[9e88b42a] + Serialization
[1a1011a3] + SharedArrays
[6462fe0b] + Sockets
[2f01184e] + SparseArrays
[10745b16] + Statistics
[fa267f1f] + TOML
[8dfed614] + Test
[cf7118a7] + UUIDs
[4ec0a83e] + Unicode
Building Conda ─→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/7a58bb32ce5d85f8bf7559aa7c2842f9aecf52fc/build.log`
Building PyCall → `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/b4e471a2b1739dba687d22d3293aa16bc5f3925b/build.log`
Building CMake ─→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/50a8b41d2c562fccd9ab841085fc7d1e2706da82/build.log`
Building HDF5 ──→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/0713cbabdf855852dfab3ce6447c87145f3d9ea8/build.log`
Building FFTW ──→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/8b7c16b56936047ca41bf25effa137ae0b381ae8/build.log`
Building ADCME ─→ `~/.julia/scratchspaces/44cfe95a-1eb2-52ea-b672-e2afdf69b78f/75cced9fa2823c1212528caf9c0eed055ccb734a/build.log`
Testing ADCME
Status `/tmp/jl_4daPoa/Project.toml`
[07b341a0] ADCME v0.5.12
[631607c0] CMake v1.2.0
[7a1cc6ca] FFTW v1.2.4
[23992714] MAT v0.8.1
[76087f3c] NLopt v0.6.0
[429524aa] Optim v1.2.0
[438e738f] PyCall v1.92.0
[d330b81b] PyPlot v2.9.0
[276daf66] SpecialFunctions v0.10.3
[76f85450] LibGit2
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[44cfe95a] Pkg
[9a3f8284] Random
[2f01184e] SparseArrays
[10745b16] Statistics
[8dfed614] Test
Status `/tmp/jl_4daPoa/Manifest.toml`
[07b341a0] ADCME v0.5.12
[621f4979] AbstractFFTs v0.5.0
[4fba245c] ArrayInterface v2.13.3
[9e28174c] BinDeps v1.0.1
[a74b3585] Blosc v0.7.0
[0b7ba130] Blosc_jll v1.14.3+1
[e1450e63] BufferedStreams v1.0.0
[631607c0] CMake v1.2.0
[944b1d66] CodecZlib v0.7.0
[3da002f7] ColorTypes v0.10.9
[5ae59095] Colors v0.12.4
[bbf7d656] CommonSubexpressions v0.3.0
[34da2185] Compat v3.17.0
[e66e0078] CompilerSupportLibraries_jll v0.3.3+0
[8f4d0f93] Conda v1.4.1
[9a962f9c] DataAPI v1.3.0
[864edb3b] DataStructures v0.18.6
[163ba53b] DiffResults v1.0.2
[b552c78f] DiffRules v1.0.1
[7a1cc6ca] FFTW v1.2.4
[f5851436] FFTW_jll v3.3.9+5
[1a297f60] FillArrays v0.9.6
[6a86dc24] FiniteDiff v2.7.0
[53c48c17] FixedPointNumbers v0.8.4
[f6369f11] ForwardDiff v0.10.12
[f67ccb44] HDF5 v0.13.6
[0234f1f7] HDF5_jll v1.10.5+6
[1d5cc7b8] IntelOpenMP_jll v2018.0.3+0
[682c06a0] JSON v0.21.1
[b964fa9f] LaTeXStrings v1.2.0
[d3d80556] LineSearches v7.1.0
[5ced341a] Lz4_jll v1.9.2+2
[23992714] MAT v0.8.1
[856f044c] MKL_jll v2020.2.254+0
[1914dd2f] MacroTools v0.5.5
[fdba3010] MathProgBase v0.7.8
[e1d29d7a] Missings v0.4.4
[d41bc354] NLSolversBase v7.7.0
[76087f3c] NLopt v0.6.0
[079eb43e] NLopt_jll v2.6.2+0
[77ba4419] NaNMath v0.3.4
[efe28fd5] OpenSpecFun_jll v0.5.3+3
[429524aa] Optim v1.2.0
[bac558e1] OrderedCollections v1.3.1
[d96e819e] Parameters v0.12.1
[69de0a69] Parsers v1.0.10
[85a6dd25] PositiveFactorizations v0.2.3
[438e738f] PyCall v1.92.0
[d330b81b] PyPlot v2.9.0
[189a3867] Reexport v0.2.0
[ae029012] Requires v1.0.3
[a2af1166] SortingAlgorithms v0.3.1
[276daf66] SpecialFunctions v0.10.3
[90137ffa] StaticArrays v0.12.4
[2913bbd2] StatsBase v0.33.1
[3bb67fe8] TranscodingStreams v0.9.5
[30578b45] URIParser v0.4.1
[3a884ed6] UnPack v1.0.2
[81def892] VersionParsing v1.2.0
[83775a58] Zlib_jll v1.2.11+16
[3161d3a3] Zstd_jll v1.4.5+1
[56f22d72] Artifacts
[2a0f44e3] Base64
[ade2ca70] Dates
[8bb1440f] DelimitedFiles
[8ba89e20] Distributed
[b77e0a4c] InteractiveUtils
[76f85450] LibGit2
[8f399da3] Libdl
[37e2e46d] LinearAlgebra
[56ddb016] Logging
[d6f4376e] Markdown
[a63ad114] Mmap
[44cfe95a] Pkg
[de0858da] Printf
[3fa0cd96] REPL
[9a3f8284] Random
[ea8e919c] SHA
[9e88b42a] Serialization
[1a1011a3] SharedArrays
[6462fe0b] Sockets
[2f01184e] SparseArrays
[10745b16] Statistics
[fa267f1f] TOML
[8dfed614] Test
[cf7118a7] UUIDs
[4ec0a83e] Unicode
Testing Running tests...
WARNING: Method definition size(PyCall.PyObject) in module PyCall at /home/pkgeval/.julia/packages/PyCall/l64G5/src/PyCall.jl:809 overwritten in module ADCME at /home/pkgeval/.julia/packages/ADCME/PJIHk/src/variable.jl:212.
** incremental compilation may be fatally broken for this module **
WARNING: Method definition length(PyCall.PyObject) in module PyCall at /home/pkgeval/.julia/packages/PyCall/l64G5/src/PyCall.jl:808 overwritten in module ADCME at /home/pkgeval/.julia/packages/ADCME/PJIHk/src/variable.jl:236.
** incremental compilation may be fatally broken for this module **
WARNING: Method definition lastindex(PyCall.PyObject) in module PyCall at deprecated.jl:70 overwritten in module ADCME at /home/pkgeval/.julia/packages/ADCME/PJIHk/src/variable.jl:424.
** incremental compilation may be fatally broken for this module **
WARNING: Method definition *(PyCall.PyObject, PyCall.PyObject) in module PyCall at /home/pkgeval/.julia/packages/PyCall/l64G5/src/pyoperators.jl:11 overwritten in module ADCME at /home/pkgeval/.julia/packages/ADCME/PJIHk/src/ops.jl:102.
** incremental compilation may be fatally broken for this module **
[ Info: You are using ADCME for the first time. Precompiling built-in custom operators may take some time...
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /home/pkgeval/.julia/adcme/bin/x86_64-conda_cos6-linux-gnu-gcc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /home/pkgeval/.julia/adcme/bin/x86_64-conda_cos6-linux-gnu-g++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
JULIA=/opt/julia/bin/julia
┌ Warning: Cannot load /home/pkgeval/.julia/packages/ADCME/PJIHk/deps/CustomOps/build/libadcme.so. Please recompile the shared library by `ADCME.precompile()` for using custom operators.
└ @ ADCME ~/.julia/packages/ADCME/PJIHk/src/ADCME.jl:95
Python path=/home/pkgeval/.julia/adcme/bin/python
PREFIXDIR=/home/pkgeval/.julia/adcme/lib/Libraries
TF_INC=/home/pkgeval/.julia/adcme/lib/python3.7/site-packages/tensorflow_core/include
TF_ABI=1
TF_LIB_FILE=/home/pkgeval/.julia/adcme/lib/python3.7/site-packages/tensorflow_core/libtensorflow_framework.so.1
MPI_INCLUDE_PATH and/or MPI_C_LIBRARIES is not set. MPI operators are not compiled.
-- Found OpenMP_C: -fopenmp (found version "4.0")
-- Found OpenMP_CXX: -fopenmp (found version "4.0")
-- Found OpenMP: TRUE (found version "4.0")
OPENMP Found
-- Configuring done
-- Generating done
-- Build files have been written to: /home/pkgeval/.julia/packages/ADCME/PJIHk/deps/CustomOps/build
[1/19] Building CXX object CMakeFiles/adcme.dir/OT/src/sinkhorn.cpp.o
[2/19] Building CXX object CMakeFiles/adcme.dir/PrintTensor/PrintTensor.cpp.o
[3/19] Building CXX object CMakeFiles/adcme.dir/SparseAccumulate/SparseAccumulator.cpp.o
[4/19] Building CXX object CMakeFiles/adcme.dir/TriSolve/TriSolve.cpp.o
[5/19] Building CXX object CMakeFiles/adcme.dir/SparseAccumulate/Impl.cpp.o
[6/19] Building CXX object CMakeFiles/adcme.dir/SparseToDense/SparseToDense.cpp.o
[7/19] Building CXX object CMakeFiles/adcme.dir/SparseConcate/SparseConcate.cpp.o
[8/19] Building CXX object CMakeFiles/adcme.dir/SparseFactorizationSolve/lru_cache.cpp.o
[9/19] Building CXX object CMakeFiles/adcme.dir/TriLu/TriLu.cpp.o
[10/19] Building CXX object CMakeFiles/adcme.dir/SparseScatterUpdate/SparseScatterUpdate.cpp.o
[11/19] Building CXX object CMakeFiles/adcme.dir/OT/SinkhornKnopp/SinkhornKnopp.cpp.o
[12/19] Building CXX object CMakeFiles/adcme.dir/SparseIndexing/SparseIndexing.cpp.o
[13/19] Building CXX object CMakeFiles/adcme.dir/SparseMatMul/SparseMatMul.cpp.o
[14/19] Building CXX object CMakeFiles/adcme.dir/SparseFactorizationSolve/Solve/Solve.cpp.o
[15/19] Building CXX object CMakeFiles/adcme.dir/SolveBatchedRhs/SolveBatchedRhs.cpp.o
[16/19] Building CXX object CMakeFiles/adcme.dir/SparseFactorizationSolve/Factorization/SparseFactorization.cpp.o
[17/19] Building CXX object CMakeFiles/adcme.dir/SparseLeastSquare/SparseLeastSquare.cpp.o
[18/19] Building CXX object CMakeFiles/adcme.dir/SparseSolver/SparseSolver.cpp.o
[19/19] Linking CXX shared library libadcme.so
Collecting package metadata (current_repodata.json): ...working... done
Solving environment: ...working... done
## Package Plan ##
environment location: /home/pkgeval/.julia/adcme
added / updated specs:
- matplotlib
The following packages will be downloaded:
package | build
---------------------------|-----------------
ca-certificates-2020.7.22 | 0 132 KB anaconda
certifi-2020.6.20 | py37_0 159 KB anaconda
conda-4.8.5 | py37_0 3.1 MB anaconda
matplotlib-3.3.1 | 0 24 KB anaconda
openssl-1.1.1h | h7b6447c_0 3.8 MB anaconda
------------------------------------------------------------
Total: 7.2 MB
The following packages will be UPDATED:
ca-certificates conda-forge::ca-certificates-2020.6.2~ --> anaconda::ca-certificates-2020.7.22-0
conda conda-forge::conda-4.8.4-py37hc8dfbb8~ --> anaconda::conda-4.8.5-py37_0
openssl conda-forge::openssl-1.1.1g-h516909a_1 --> anaconda::openssl-1.1.1h-h7b6447c_0
The following packages will be SUPERSEDED by a higher-priority channel:
certifi conda-forge::certifi-2020.6.20-py37hc~ --> anaconda::certifi-2020.6.20-py37_0
matplotlib pkgs/main --> anaconda
Downloading and Extracting Packages
matplotlib-3.3.1 | 24 KB | | 0% matplotlib-3.3.1 | 24 KB | ########## | 100% matplotlib-3.3.1 | 24 KB | ########## | 100%
ca-certificates-2020 | 132 KB | | 0% ca-certificates-2020 | 132 KB | ########## | 100% ca-certificates-2020 | 132 KB | ########## | 100%
certifi-2020.6.20 | 159 KB | | 0% certifi-2020.6.20 | 159 KB | ########## | 100%
conda-4.8.5 | 3.1 MB | | 0% conda-4.8.5 | 3.1 MB | ######### | 91% conda-4.8.5 | 3.1 MB | ########## | 100%
openssl-1.1.1h | 3.8 MB | | 0% openssl-1.1.1h | 3.8 MB | ########## | 100% openssl-1.1.1h | 3.8 MB | ########## | 100%
Preparing transaction: ...working... done
Verifying transaction: ...working... done
Executing transaction: ...working... done
Matplotlib is building the font cache; this may take a moment.
2020-09-28 21:53:35.474491: I tensorflow/core/platform/cpu_feature_guard.cc:145] This TensorFlow binary is optimized with Intel(R) MKL-DNN to use the following CPU instructions in performance critical operations: SSE4.1 SSE4.2 AVX AVX2 AVX512F FMA
To enable them in non-MKL-DNN operations, rebuild TensorFlow with the appropriate compiler flags.
2020-09-28 21:53:35.488695: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2200000000 Hz
2020-09-28 21:53:35.492954: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x60362f0 initialized for platform Host (this does not guarantee that XLA will be used). Devices:
2020-09-28 21:53:35.493009: I tensorflow/compiler/xla/service/service.cc:176] StreamExecutor device (0): Host, Default Version
[✔️] Julia version
[✔️] TensorFlow version
[✔️] TensorFlow-Probability version
[✔️] Python executable file
[✘] Julia path (Optional)
[Reason]
`julia` outputs nothing. This will break custom operator compilation.
[Instruction]
Add your julia binary path to your environment path, e.g. (Unix systems)
export PATH=/opt/julia/bin:$PATH
For convenience, you can add the above line to your `~/.bashrc` (Linux) or `~/.bash_profile` (Apple).
For Windows, you need to add it to system environment.
[✘] Dynamic library path (Optional)
[Reason]
/home/pkgeval/.julia/adcme/lib is not in LD_LIBRARY_PATH. This MAY break custom operator compilation. However, in most cases, ADCME automatic fixes this problem for you.
[Instruction]
Add your dynamic library path path to your environment path, e.g. (Unix systems)
export LD_LIBRARY_PATH=/home/pkgeval/.julia/adcme/lib:$LD_LIBRARY_PATH
For convenience, you can add the above line to your `~/.bashrc` (Linux or Apple).
For Windows, you need to add it to PATH instead of LD_LIBRARY_PATH.
[✔️] Memory Address Length = 64
[✘] Binaries path
[Reason]
/home/pkgeval/.julia/adcme/bin is not in PATH. This path contains compatible tools such as a GCC compiler, `cmake`, `make`, or any other tools you want to use directly from terminal.
However, setting the path is NOT a requirement, and ADCME works totally fine without any action.
[Instruction]
(Optional) Add your binary path to your environment path, e.g. (Unix systems)
export PATH=/home/pkgeval/.julia/adcme/bin:$PATH
For convenience, you can add the above line to your `~/.bashrc` (Linux) or `~/.bash_profile` (Apple).
For Windows, you need to add it to system environment.
[✘] GPU Support (Optional)
[Reason]
ADCME is not compiled against GPU.
[Instruction]
If you intend to use GPU, set ENV["GPU"] = 1 and then rebuild ADCME.
Dependency file is located at: /home/pkgeval/.julia/packages/ADCME/PJIHk/src/../deps/deps.jl
OMP: Info #212: KMP_AFFINITY: decoding x2APIC ids.
OMP: Info #210: KMP_AFFINITY: Affinity capable, using global cpuid leaf 11 info
OMP: Info #154: KMP_AFFINITY: Initial OS proc set respected: 0-39
OMP: Info #156: KMP_AFFINITY: 40 available OS procs
OMP: Info #157: KMP_AFFINITY: Uniform topology
OMP: Info #179: KMP_AFFINITY: 2 packages x 10 cores/pkg x 2 threads/core (20 total cores)
OMP: Info #214: KMP_AFFINITY: OS proc to physical thread map:
OMP: Info #171: KMP_AFFINITY: OS proc 0 maps to package 0 core 0 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 20 maps to package 0 core 0 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 1 maps to package 0 core 1 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 21 maps to package 0 core 1 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 2 maps to package 0 core 2 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 22 maps to package 0 core 2 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 3 maps to package 0 core 3 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 23 maps to package 0 core 3 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 4 maps to package 0 core 4 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 24 maps to package 0 core 4 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 5 maps to package 0 core 8 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 25 maps to package 0 core 8 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 6 maps to package 0 core 9 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 26 maps to package 0 core 9 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 7 maps to package 0 core 10 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 27 maps to package 0 core 10 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 8 maps to package 0 core 11 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 28 maps to package 0 core 11 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 9 maps to package 0 core 12 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 29 maps to package 0 core 12 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 10 maps to package 1 core 0 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 30 maps to package 1 core 0 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 11 maps to package 1 core 1 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 31 maps to package 1 core 1 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 12 maps to package 1 core 2 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 32 maps to package 1 core 2 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 13 maps to package 1 core 3 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 33 maps to package 1 core 3 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 14 maps to package 1 core 4 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 34 maps to package 1 core 4 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 15 maps to package 1 core 8 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 35 maps to package 1 core 8 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 16 maps to package 1 core 9 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 36 maps to package 1 core 9 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 17 maps to package 1 core 10 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 37 maps to package 1 core 10 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 18 maps to package 1 core 11 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 38 maps to package 1 core 11 thread 1
OMP: Info #171: KMP_AFFINITY: OS proc 19 maps to package 1 core 12 thread 0
OMP: Info #171: KMP_AFFINITY: OS proc 39 maps to package 1 core 12 thread 1
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 4263 thread 0 bound to OS proc set 0
2020-09-28 21:53:35.876602: I tensorflow/core/common_runtime/process_util.cc:115] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.
Test Summary: | Pass Total
indexing for rank 3 tensors | 3 3
[ Info: Copy "/home/pkgeval/.julia/packages/ADCME/PJIHk/src/../deps/AdeptCMakeLists.txt" to "/home/pkgeval/.julia/adcme/lib/Adept-2/adept/CMakeLists.txt" ...
[ Info: Remove /home/pkgeval/.julia/adcme/lib/Adept-2/adept/build ...
[ Info: Make /home/pkgeval/.julia/adcme/lib/Adept-2/adept/build ...
[ Info: Change directory into /home/pkgeval/.julia/adcme/lib/Adept-2/adept/build ...
[ Info: Cmake ...
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /home/pkgeval/.julia/adcme/bin/x86_64-conda_cos6-linux-gnu-gcc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /home/pkgeval/.julia/adcme/bin/x86_64-conda_cos6-linux-gnu-g++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
JULIA=/opt/julia/bin/julia
Python path=/home/pkgeval/.julia/adcme/bin/python
PREFIXDIR=/home/pkgeval/.julia/adcme/lib/Libraries
TF_INC=/home/pkgeval/.julia/adcme/lib/python3.7/site-packages/tensorflow_core/include
TF_ABI=1
TF_LIB_FILE=/home/pkgeval/.julia/adcme/lib/python3.7/site-packages/tensorflow_core/libtensorflow_framework.so.1
Use openblas library /home/pkgeval/.julia/adcme/lib/libopenblas.so
-- Configuring done
-- Generating done
-- Build files have been written to: /home/pkgeval/.julia/adcme/lib/Adept-2/adept/build
[ Info: Make ...
[1/12] Building CXX object CMakeFiles/adept.dir/StackStorageOrig.cpp.o
[2/12] Building CXX object CMakeFiles/adept.dir/cppblas.cpp.o
[3/12] Building CXX object CMakeFiles/adept.dir/settings.cpp.o
[4/12] Building CXX object CMakeFiles/adept.dir/Storage.cpp.o
[5/12] Building CXX object CMakeFiles/adept.dir/index.cpp.o
[6/12] Building CXX object CMakeFiles/adept.dir/Array.cpp.o
[7/12] Building CXX object CMakeFiles/adept.dir/Stack.cpp.o
[8/12] Building CXX object CMakeFiles/adept.dir/inv.cpp.o
[9/12] Building CXX object CMakeFiles/adept.dir/vector_utilities.cpp.o
[10/12] Building CXX object CMakeFiles/adept.dir/jacobian.cpp.o
[11/12] Building CXX object CMakeFiles/adept.dir/solve.cpp.o
[12/12] Linking CXX shared library /home/pkgeval/.julia/adcme/lib/libadept.so
∘ Add the following lines to CMakeLists.txt
include_directories(${LIBDIR}/Adept-2/include)
find_library(ADEPT_LIB_FILE adept HINTS ${LIBDIR})
find_library(LIBOPENBLAS openblas HINTS ${LIBDIR})
message("ADEPT_LIB_FILE=${ADEPT_LIB_FILE}")
message("LIBOPENBLAS=${LIBOPENBLAS}")
∘ Add `${ADEPT_LIB_FILE}` and `${LIBOPENBLAS}` to `target_link_libraries`
-- The C compiler identification is GNU 5.4.0
-- The CXX compiler identification is GNU 5.4.0
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Check for working C compiler: /home/pkgeval/.julia/adcme/bin/x86_64-conda_cos6-linux-gnu-gcc - skipped
-- Detecting C compile features
-- Detecting C compile features - done
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Check for working CXX compiler: /home/pkgeval/.julia/adcme/bin/x86_64-conda_cos6-linux-gnu-g++ - skipped
-- Detecting CXX compile features
-- Detecting CXX compile features - done
JULIA=/opt/julia/bin/julia
Python path=/home/pkgeval/.julia/adcme/bin/python
PREFIXDIR=/home/pkgeval/.julia/adcme/lib/Libraries
TF_INC=/home/pkgeval/.julia/adcme/lib/python3.7/site-packages/tensorflow_core/include
TF_ABI=1
TF_LIB_FILE=/home/pkgeval/.julia/adcme/lib/python3.7/site-packages/tensorflow_core/libtensorflow_framework.so.1
ADEPT_LIB_FILE=/home/pkgeval/.julia/adcme/lib/libadept.so
-- Configuring done
-- Generating done
-- Build files have been written to: /home/pkgeval/.julia/packages/ADCME/PJIHk/deps/Plugin/ExtendedNN/build
[1/2] Building CXX object CMakeFiles/ExtendedNn.dir/ExtendedNn.cpp.o
[2/2] Linking CXX shared library libExtendedNn.so
Load library operator (with gradient, multiple outputs = true): /home/pkgeval/.julia/packages/ADCME/PJIHk/deps/Plugin/ExtendedNN/build/libExtendedNn.so ==> extended_nn
Test Summary: | Pass Total
fcx | 4 4
Test Summary: | Pass Total
dropout | 2 2
Test Summary: | Pass Total
sparse_constructor | 7 7
Test Summary: | Pass Total
sparse_arithmetic | 4 4
Test Summary: | Pass Total
sparse_adjoint | 1 1
Test Summary: | Pass Total
sparse_mul | 6 6
Test Summary: | Pass Total
sparse_vcat_hcat | 2 2
Test Summary: | Pass Total
sparse_indexing | 3 3
Test Summary: | Pass Total
sparse_solve | 1 1
k = 1
k = 2
k = 3
k = 4
k = 5
k = 6
k = 7
k = 8
k = 9
k = 10
v = [0.4649123373322992, 0.8003020228561573, 0.09897206809689307, 0.5552492548635317, 0.7962910964535579, 0.4320006289846088, 0.8106712618377903, 0.6572114320684403, 0.771846563406918, 0.5637829373280854]
2020-09-28 21:54:46.218190: I ../SparseAccumulate/Impl.cpp:68] Create a new sparse assembler [Handle ID = 100] with 20 rows and tolerance 0.
2020-09-28 21:54:46.218268: I ../SparseAccumulate/Impl.cpp:69] Current sparse assembler:
2020-09-28 21:54:46.218283: I ../SparseAccumulate/Impl.cpp:74] 100 |
2020-09-28 21:54:46.218318: I ../SparseAccumulate/Impl.cpp:82] destroy_sparse_assembler
2020-09-28 21:54:46.306914: I ../SparseAccumulate/Impl.cpp:68] Create a new sparse assembler [Handle ID = 100] with 5 rows and tolerance 1.
2020-09-28 21:54:46.306971: I ../SparseAccumulate/Impl.cpp:69] Current sparse assembler:
2020-09-28 21:54:46.306979: I ../SparseAccumulate/Impl.cpp:74] 100 |
2020-09-28 21:54:46.306997: I ../SparseAccumulate/Impl.cpp:82] destroy_sparse_assembler
2020-09-28 21:54:46.417790: I ../SparseAccumulate/Impl.cpp:68] Create a new sparse assembler [Handle ID = 100] with 5 rows and tolerance 0.
2020-09-28 21:54:46.417854: I ../SparseAccumulate/Impl.cpp:69] Current sparse assembler:
2020-09-28 21:54:46.417862: I ../SparseAccumulate/Impl.cpp:74] 100 |
2020-09-28 21:54:46.417906: I ../SparseAccumulate/Impl.cpp:82] destroy_sparse_assembler
Test Summary: | Pass Total
sparse_assembler | 3 3
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = \(s::SparseTensor, o::PyObject, method::String) at sparse.jl:426
└ @ ADCME ~/.julia/packages/ADCME/PJIHk/src/sparse.jl:426
Test Summary: | Pass Total
sparse_least_square | 1 1
Test Summary: | Pass Total
sparse mat mul | 3 3
Test Summary: | Pass Total
spdiag | 3 3
Test Summary: | Pass Total
spzero | 2 2
Test Summary: | Pass Total
sparse indexing | 1 1
Test Summary: | Pass Total
sum | 3 3
Test Summary: | Pass Total
dense_to_sparse | 2 2
Test Summary: | Pass Total
spdiagm | 4 4
Test Summary: | Pass Total
hvcat | 1 1
Test Summary: | Pass Total
find | 6 6
Test Summary: | Pass Total
sparse scatter update add | 2 2
Test Summary: | Pass Total
constant sparse | 1 1
Test Summary: | Pass Total
get index | 1 1
2020-09-28 21:54:57.172481: I ../SparseFactorizationSolve/Factorization/SparseFactorization.h:32] Factorization: current matrix id= 1, maximum cache size = 999999
2020-09-28 21:54:57.215676: I ../SparseFactorizationSolve/Factorization/SparseFactorization.h:32] Factorization: current matrix id= 2, maximum cache size = 999999
Test Summary: | Pass Total
sparse_factorization_and_solve | 2 2
2020-09-28 21:54:57.331435: W tensorflow/core/framework/op_kernel.cc:1651] OP_REQUIRES failed at SparseSolver.cpp:139 : Internal: Sparse solver factorization failed.
2020-09-28 21:54:57.331983: W tensorflow/core/framework/op_kernel.cc:1651] OP_REQUIRES failed at SparseSolver.cpp:139 : Internal: Sparse solver factorization failed.
Test Summary: | Pass Total
sparse solver warning | 1 1
Test Summary: | Pass Total
sparse promote | 6 6
Test Summary: | Pass Total
trisolve | 1 1
Test Summary: | Broken Total
random | 47 47
Test Summary: | Pass Total
save and load | 1 1
Test Summary: | Pass Total
psave and pload | 1 1
tensorboard --logdir="/tmp/jl_XE9UXY" --port 0
tensorboard --logdir="/tmp/jl_4jokzT" --port 0
Test Summary: |
diary | No tests
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = macro expansion at variable.jl:17 [inlined]
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:17
Test Summary: | Pass Total
indexing | 28 28
Test Summary: | Pass Total
Variables | 4 4
Test Summary: | Pass Total
tensor | 2 2
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:64
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:64
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:64
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:64
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:64
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:64
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:64
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:64
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:64
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:64
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:64
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:64
Test Summary: | Pass Total
Hessian | 2 2
Test Summary: | Pass Total
Jacobian | 1 1
Test Summary: | Pass Total
gradients_v | 1 1
Test Summary: | Pass Total
size and length | 9 9
Test Summary: | Pass Total
copy | 1 1
Test Summary: | Pass Total
getindex | 1 1
Test Summary: | Pass Total
convert_to_tensor | 5 5
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:131
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:131
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at variable.jl:132
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/variable.jl:132
Test Summary: | Pass Total
cell | 2 2
Test Summary: | Pass Total
special matrices | 2 2
Test Summary: | Pass Total
ones/zeros like | 2 2
Test Summary: | Pass Total
gradient_magnitude | 1 1
Test Summary: | Pass Total
indexing with tensor | 6 6
Test Summary: | Pass Total
ndims | 4 4
Test Summary: | Pass Total
gradients_colocate | 1 1
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6267 thread 1 bound to OS proc set 1
Test Summary: | Pass Total
* | 27 27
Test Summary: | Pass Total
reshape | 6 6
Test Summary: | Pass Total
scatter_update | 9 9
Test Summary: | Pass Total
adjoint | 4 4
Test Summary: | Pass Total
scatter_update_pyobject | 9 9
Test Summary: | Pass Total
Operators | 14 14
Test Summary: | Pass Total
Other Operators | 1 1
Test Summary: | Pass Total
Concat and stack | 6 6
Test Summary: | Pass Total
Vectorize | 5 5
Test Summary: | Pass Total
Solve | 3 3
Test Summary: | Pass Total
diff | 3 3
Test Summary: | Pass Total
clip | 1 1
Test Summary: | Pass Total
map | 1 1
Test Summary: | Pass Total
diag | 2 2
Test Summary: | Pass Total
dot | 3 3
Test Summary: | Pass Total
prod | 1 1
Test Summary: | Pass Total
findall | 2 2
Test Summary: | Pass Total
svd | 1 1
Test Summary: | Pass Total
vector | 1 1
Test Summary: | Pass Total
repeat | 6 6
Test Summary: | Pass Total
pmap | 3 3
Test Summary: | Pass Total
reshape | 1 1
Test Summary: | Pass Total
batch mul | 1 1
Test Summary: | Pass Total
sort | 2 2
Test Summary: | Pass Total
set_shape | 3 3
Test Summary: | Pass Total
activation | 8 8
Test Summary: | Pass Total
trace | 1 1
Test Summary: | Pass Total
trilu | 22 22
Test Summary: | Pass Total
reverse | 3 3
Test Summary: | Pass Total
solve batch | 2 2
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = (::var"#45#46"{PyObject, Int64})() at core.jl:18
└ @ Main ~/.julia/packages/ADCME/PJIHk/test/core.jl:18
Test Summary: | Pass Total
control_dependency | 2 2
WARNING: Method definition body(Any, Any) in module Main at /home/pkgeval/.julia/packages/ADCME/PJIHk/test/core.jl:40 overwritten at /home/pkgeval/.julia/packages/ADCME/PJIHk/test/core.jl:73.
Test Summary: | Pass Total
while loop | 3 3
Test Summary: | Pass Total
if_clause | 1 1
Test Summary: | Pass Total
if_else: tf.where | 2 2
Test Summary: | Pass Total
get and add collection | 1 1
Test Summary: | Pass Total
has_gpu | 1 1
2020-09-28 21:56:03.764441: I tensorflow/core/profiler/lib/profiler_session.cc:205] Profiler session started.
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6534 thread 2 bound to OS proc set 2
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6535 thread 3 bound to OS proc set 3
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6536 thread 4 bound to OS proc set 4
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6537 thread 5 bound to OS proc set 5
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6538 thread 6 bound to OS proc set 6
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6539 thread 7 bound to OS proc set 7
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6540 thread 8 bound to OS proc set 8
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6541 thread 9 bound to OS proc set 9
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6542 thread 10 bound to OS proc set 10
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6543 thread 11 bound to OS proc set 11
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6544 thread 12 bound to OS proc set 12
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6545 thread 13 bound to OS proc set 13
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6546 thread 14 bound to OS proc set 14
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6547 thread 15 bound to OS proc set 15
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6548 thread 16 bound to OS proc set 16
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6549 thread 17 bound to OS proc set 17
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6550 thread 18 bound to OS proc set 18
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6551 thread 19 bound to OS proc set 19
OMP: Info #250: KMP_AFFINITY: pid 4263 tid 6552 thread 20 bound to OS proc set 20
┌ Info: Timeline information saved in test.json
│ - Open Chrome and navigate to chrome://tracing
└ - Load the timeline file
Test Summary: |
timeline | No tests
Test Summary: | Pass Total
independent | 1 1
Test Summary: | Pass Total
run corner cases | 1 1
Test Summary: | Pass Total
@cpu @gpu | 4 4
Test Summary: | Pass Total
xavier_init | 1 1
Load library operator: /home/pkgeval/.julia/packages/ADCME/PJIHk/deps/CustomOps/build/libadcme.so ==> sparse_solver
Load library operator (with gradient, multiple outputs = false): /home/pkgeval/.julia/packages/ADCME/PJIHk/deps/CustomOps/build/libadcme.so ==> sparse_solver
Test Summary: | Pass Total
load_op | 2 2
Test Summary: | Pass Total
ae | 1 1
[ Info: (1/4)Intializing TensorArray...
[ Info: (2/4)Parsing Condition...
[ Info: (3/4)Parsing Main Loop...
[ Info: (4/4)Postprocessing Results...
Newton-Raphson with absolute tolerance = 1.0e-12 and relative tolerance = 1.0e-12
ITER 2 >>> Error = 15.652475842498529 | Relative Error = 15.652475842498529
ITER 3 >>> Error = 64.928788679993914 | Relative Error = 15.652475842498529
ITER 4 >>> Error = 15.489950495968388 | Relative Error = 64.928788679993914
ITER 5 >>> Error = 2.2725864326069174 | Relative Error = 15.489950495968388
ITER 6 >>> Error = 0.084320075161598992 | Relative Error = 2.2725864326069174
ITER 7 >>> Error = 0.00013179440739372649 | Relative Error = 0.084320075161598992
ITER 8 >>> Error = 3.2366684481841166e-10 | Relative Error = 0.00013179440739372649
ITER 9 >>> Error = 0 | Relative Error = 3.2366684481841166e-10
Test Summary: | Pass Total
register | 4 4
Test Summary: | Pass Total
list_physical_devices | 1 1
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([1.0], 5, true)
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([2.0945514815423265], 11, true)
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([0.9708700202758002], 11, true)
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([0.7390849386261854], 21, true)
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([0.9999997375751308], 19, true)
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([1.2999999999998582], 43, true)
((nrr[i]).x, (nrr[i]).iter, (nrr[i]).converged) = ([0.45840750163141014], 23, true)
Test Summary: | Pass Total
newton raphson with linesearch | 7 7
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:50
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:50
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:51
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:51
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:51
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:51
[CustomOptimizer] Number of inequalities constraints = 1, Number of equality constraints = 0
[CustomOptimizer] Total number of variables = 4
Test Summary: | Pass Total
NLopt | 1 1
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:71
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:71
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:71
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:71
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:71
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:71
[CustomOptimizer] Number of inequalities constraints = 0, Number of equality constraints = 0
[CustomOptimizer] Total number of variables = 2
[CustomOptimizer] No bounds provided, use (-∞, +∞) as default; or you need to provide bounds in the function CustomOptimizer
(f, df, c, dc, x0) = (ADCME.var"#f#494"{PyObject}(PyObject <function ExternalOptimizerInterface._make_eval_func.<locals>.eval_func at 0x7f81205228c0>), ADCME.var"#df#495"{PyObject}(PyObject <function ExternalOptimizerInterface._make_eval_func.<locals>.eval_func at 0x7f81205228c0>), ADCME.var"#c#496"{Vector{Float64}, Vector{Any}, Vector{Any}, Int64, Int64}([0.4649123373322992, 0.8003020228561573], Any[], Any[], 0, 0), ADCME.var"#dc#499"{Vector{Float64}, Vector{Any}, Vector{Any}, Int64, Int64, Int64, Int64}([0.4649123373322992, 0.8003020228561573], Any[], Any[], 0, 2, 0, 0), [0.4649123373322992, 0.8003020228561573])
Test Summary: | Pass Total
Optim | 1 1
Test Summary: | Broken Total
newton raphson | 1 1
Test Summary: | Broken Total
NonlinearConstrainedProblem | 1 1
[ Info: Optimization starts...
iter 1, current loss = 10634.22003171869
[ Info: (0, 10634.22003171869)
================== STEP 0 ==================
iter 2, current loss = 8.676432737591423e11
iter 3, current loss = 4123.656312128288
[ Info: (1, 4123.656312128288)
================== STEP 1 ==================
iter 4, current loss = 3702.6997729552263
iter 5, current loss = 2481.5630838834204
iter 6, current loss = 7480.426861414803
iter 7, current loss = 1992.4555691593985
[ Info: (2, 1992.4555691593985)
================== STEP 2 ==================
iter 8, current loss = 1986.0606203708317
iter 9, current loss = 1960.583615790924
iter 10, current loss = 1835.6655666760828
iter 11, current loss = 1272.7496657192617
iter 12, current loss = 0.028776369768125077
iter 13, current loss = 1.0874829505961052e-18
[ Info: (3, 1.0874829505961052e-18)
================== STEP 3 ==================
iter 14, current loss = 5.486674537667579e-18
iter 15, current loss = 9.050543019506827e-19
[ Info: (4, 9.050543019506827e-19)
================== STEP 4 ==================
iter 16, current loss = 8.761170304278346e-21
iter 17, current loss = 1.1138015816027781e-17
iter 18, current loss = 1.4938750517825842e-29
[ Info: (5, 1.4938750517825842e-29)
================== STEP 5 ==================
Test Summary: | Pass Total
Custom BFGS! | 1 1
[ Info: Optimization starts...
iter 0, current loss=4.0
iter 1, current loss=1.0
================ STEP 0 ===============
Test Summary: | Pass Total
var_to_bounds | 1 1
┌ Warning: θ is not a PyObject, no gradients is available
└ @ ADCME ~/.julia/packages/ADCME/PJIHk/src/optim.jl:591
Test Summary: | Pass Total
newton_raphson_with_grad | 3 3
Test Summary: | Pass Total
pack and unpack | 2 2
Test Summary: | Pass Total
search direction | 1 1
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:300
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:300
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:300
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:300
┌ Warning: `getindex(o::PyObject, i::Integer)` is deprecated, use `get(o, i - 1)` instead.
│ caller = top-level scope at optim.jl:300
└ @ Core ~/.julia/packages/ADCME/PJIHk/test/optim.jl:300
[ Info: Optimization starts...
iter 1, current loss = 28.41729747790481
[ Info: (0, 28.41729747790481)
================== STEP 0 ==================
iter 2, current loss = 1.1069366543495706e11
iter 3, current loss = 28.412742454118913
iter 4, current loss = 1.723211300789566
[ Info: (1, 1.723211300789566)
================== STEP 1 ==================
iter 5, current loss = 0.2739946615860164
iter 6, current loss = 8.567494101542145
iter 7, current loss = 0.16075847410234018
[ Info: (2, 0.16075847410234018)
================== STEP 2 ==================
iter 8, current loss = 0.1518543972641549
iter 9, current loss = 0.26295565100345203
iter 10, current loss = 0.15175312473821834
[ Info: (3, 0.15175312473821834)
================== STEP 3 ==================
iter 11, current loss = 0.15126156242834612
iter 12, current loss = 0.14930938238569216
iter 13, current loss = 0.13992331874399966
iter 14, current loss = 0.11027113088862417
iter 15, current loss = 3.439949902890042
iter 16, current loss = 0.11018476256343399
[ Info: (4, 0.11018476256343399)
================== STEP 4 ==================
iter 17, current loss = 0.08172510244318566
iter 18, current loss = 0.4328883738411806
iter 19, current loss = 0.07778089554483077
[ Info: (5, 0.07778089554483077)
================== STEP 5 ==================
iter 20, current loss = 0.04017746015520486
iter 21, current loss = 0.08763702734682494
iter 22, current loss = 0.06419482423813563
iter 23, current loss = 0.04860471252914524
[ Info: (6, 0.04860471252914524)
================== STEP 6 ==================
iter 24, current loss = 0.22442449531786166
iter 25, current loss = 0.029708946103095473
iter 26, current loss = 0.015429143539202692
iter 27, current loss = 0.008424366062625907
[ Info: (7, 0.008424366062625907)
================== STEP 7 ==================
iter 28, current loss = 0.03889607597641182
iter 29, current loss = 0.00606558353127956
[ Info: (8, 0.00606558353127956)
================== STEP 8 ==================
iter 30, current loss = 0.004544433751361965
iter 31, current loss = 0.0045388921673296615
[ Info: (9, 0.0045388921673296615)
================== STEP 9 ==================
iter 32, current loss = 0.003656701276021206
iter 33, current loss = 0.001375687111375002
iter 34, current loss = 0.033327767165928765
iter 35, current loss = 0.0010326467652415163
[ Info: (10, 0.0010326467652415163)
================== STEP 10 ==================
iter 36, current loss = 0.0002730805768349832
iter 37, current loss = 0.00025696368762457514
[ Info: (11, 0.00025696368762457514)
================== STEP 11 ==================
iter 38, current loss = 1.503802154230343e-5
iter 39, current loss = 0.004973163587208659
iter 40, current loss = 1.2173742948039803e-5
[ Info: (12, 1.2173742948039803e-5)
================== STEP 12 ==================
iter 41, current loss = 5.822263828398199e-7
iter 42, current loss = 9.366697481183564e-5
iter 43, current loss = 3.0605244274886564e-8
[ Info: (13, 3.0605244274886564e-8)
================== STEP 13 ==================
iter 44, current loss = 7.935883095643877e-10
iter 45, current loss = 2.5745906440287696e-10
[ Info: (14, 2.5745906440287696e-10)
================== STEP 14 ==================
iter 46, current loss = 3.7607937186639854e-14
iter 47, current loss = 2.4853328844872664e-16
[ Info: (15, 2.4853328844872664e-16)
================== STEP 15 ==================
iter 48, current loss = 6.219167597684727e-22
iter 49, current loss = 3.960852972351894e-15
iter 50, current loss = 2.2637904419272444e-24
[ Info: (16, 2.2637904419272444e-24)
================== STEP 16 ==================
iter 51, current loss = 1.232595164407831e-30
iter 52, current loss = 1.9721522630525295e-31
[ Info: (17, 1.9721522630525295e-31)
================== STEP 17 ==================
[ Info: Optimization starts...
iter 1, current loss = 28.41729747790481
[ Info: (0, 28.41729747790481)
================== STEP 0 ==================
iter 2, current loss = 1.596769500416049e8
iter 3, current loss = 28.294412585773195
iter 4, current loss = 1.7183807678785405
[ Info: (1, 1.7183807678785405)
================== STEP 1 ==================