About stdtest.py

Does stdtest.py have to use original pickle file that you provided?
Or this script only depends on the output?
Based on the demo.sh, it seems that data/academic_toy/academic_toy.pickle are still used in stdtest.py.
Do you have additional instruction on how to implement this code on training or evaluating other dataset?
Hope to hear from you soon.
Thanks,

Yes, stdtests.py requires my pickle format, because I compressed information other than the network itself (e.g. labels) in it. I'll release the academic network and labels in a clean format, and encourage you to implement your own testing code, rather than digging into superfluous code in stdtests.py that I wrote for my own convenience.

Hi Zhou,
I also met with the stdtest.py problem. I got the clean academic_network data, when I tried to reproduce the results on your paper, I found there's no academic_network.pickle which was essential for stdtest.py.
Could you please kindly offer the academic_network.pickle which was used in your experiment, or show me  how to construct this file?
Hope to hear from you soon.
Thanks
Chen Baiyang

Hi, @ChenBaiyang
We've posted in the "Data Sets" section a google drive link of the preprocessed pickle file for the full (though with an ambiguous name, sorry about that) academic dataset.
If I remember correctly, the dataset in the above link should be identical to the clean dataset.
Feel free to contact me if there are any problems with the pickle file.
Lekui Zhou

Dear Zhou,
I ran the experiments on the full academic dataset, and your offered academic_full.pickle. Here are the results I got from running the stdtest.py (based on 100 iterations pretraining and 10 times repeated testting).

sudo+ssh://yons@<IP_ADDRESS>:22/home/yons/anaconda3/envs/ympy27/bin/python -u /home/yons/ym/DT/main.py
Warning: passing language='c++' to cythonize() is deprecated. Instead, put "# distutils: language=c++" in your .pyx or .pxd file(s)
running build_ext
Using TensorFlow backend.
updating cache file for prefix /tmp/academic.cache
merging graph from year 0 to 3
converting into graph nsize: 51060, esize: 1198, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 2 to 5
converting into graph nsize: 51060, esize: 1965, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 4 to 7
converting into graph nsize: 51060, esize: 3183, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 6 to 9
converting into graph nsize: 51060, esize: 4883, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 8 to 11
converting into graph nsize: 51060, esize: 8218, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 10 to 13
converting into graph nsize: 51060, esize: 12946, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 12 to 15
converting into graph nsize: 51060, esize: 18316, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 14 to 17
converting into graph nsize: 51060, esize: 24695, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 16 to 19
converting into graph nsize: 51060, esize: 31720, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 18 to 21
converting into graph nsize: 51060, esize: 40351, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 20 to 23
converting into graph nsize: 51060, esize: 50699, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 22 to 25
converting into graph nsize: 51060, esize: 72125, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 24 to 27
converting into graph nsize: 51060, esize: 101686, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 26 to 29
converting into graph nsize: 51060, esize: 134741, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 28 to 31
converting into graph nsize: 51060, esize: 147329, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
cache file /tmp/academic.cache updated
654055 edges in pretraining graphs
generating validation set
1308110 validation samples generated
sample round 0, target #samples 654055
506726 samples processed, 416839 succeeded with avg try cnt 1.79014199727
sample round 1, target #samples 237216
335812 samples processed, 288353 succeeded with avg try cnt 1.51324244936
epoch 0: 99% completed, cur loss: 2.069 training completed, total loss<PHONE_NUMBER>12, validation score 0.675
sample round 0, target #samples 654055
506726 samples processed, 416911 succeeded with avg try cnt 1.78721117936
sample round 1, target #samples 237144
332580 samples processed, 283606 succeeded with avg try cnt 1.56556631383
epoch 1: 99% completed, cur loss: 0.947 training completed, total loss<PHONE_NUMBER>93, validation score 0.728
sample round 0, target #samples 654055
506726 samples processed, 417133 succeeded with avg try cnt 1.78445723546
sample round 1, target #samples 236922
331841 samples processed, 261569 succeeded with avg try cnt 2.11877554297
epoch 2: 99% completed, cur loss: 0.646 training completed, total loss 92.755889833, validation score 0.756
sample round 0, target #samples 654055
506726 samples processed, 416726 succeeded with avg try cnt 1.79194722671
sample round 1, target #samples 237329
334706 samples processed, 291644 succeeded with avg try cnt 1.4043594245
epoch 3: 99% completed, cur loss: 0.515 training completed, total loss 71.1527889967, validation score 0.772
sample round 0, target #samples 654055
506726 samples processed, 416707 succeeded with avg try cnt 1.79144578805
sample round 1, target #samples 237348
333557 samples processed, 263819 succeeded with avg try cnt 2.09569439654
epoch 4: 99% completed, cur loss: 0.439 training completed, total loss 59.0625114739, validation score 0.784
sample round 0, target #samples 654055
506726 samples processed, 416502 succeeded with avg try cnt 1.79160244128
sample round 1, target #samples 237553
335083 samples processed, 270561 succeeded with avg try cnt 1.95904805201
epoch 5: 99% completed, cur loss: 0.391 training completed, total loss 51.3192759156, validation score 0.792
sample round 0, target #samples 654055
506726 samples processed, 416596 succeeded with avg try cnt 1.79267203718
sample round 1, target #samples 237459
335467 samples processed, 277054 succeeded with avg try cnt 1.78802327344
epoch 6: 99% completed, cur loss: 0.346 training completed, total loss 45.8155831695, validation score 0.799
sample round 0, target #samples 654055
506726 samples processed, 416600 succeeded with avg try cnt 1.7942318771
sample round 1, target #samples 237455
335505 samples processed, 286478 succeeded with avg try cnt 1.55429736315
epoch 7: 99% completed, cur loss: 0.305 training completed, total loss 41.4113515019, validation score 0.804
sample round 0, target #samples 654055
506726 samples processed, 416888 succeeded with avg try cnt 1.78908004068
sample round 1, target #samples 237167
334665 samples processed, 291558 succeeded with avg try cnt 1.41134525549
epoch 8: 99% completed, cur loss: 0.294 training completed, total loss 38.0732320845, validation score 0.809
sample round 0, target #samples 654055
506726 samples processed, 416851 succeeded with avg try cnt 1.78709658847
sample round 1, target #samples 237204
334130 samples processed, 271931 succeeded with avg try cnt 1.89884934046
epoch 9: 99% completed, cur loss: 0.277 training completed, total loss 35.6262742281, validation score 0.813
sample round 0, target #samples 654055
506726 samples processed, 416500 succeeded with avg try cnt 1.79443697479
sample round 1, target #samples 237555
334908 samples processed, 293863 succeeded with avg try cnt 1.36109003175
epoch 10: 99% completed, cur loss: 0.250 training completed, total loss 33.4194956273, validation score 0.817
sample round 0, target #samples 654055
506726 samples processed, 416776 succeeded with avg try cnt 1.78976956447
sample round 1, target #samples 237279
333987 samples processed, 268857 succeeded with avg try cnt 1.97401220723
epoch 11: 99% completed, cur loss: 0.259 training completed, total loss 31.6063426435, validation score 0.821
sample round 0, target #samples 654055
506726 samples processed, 416899 succeeded with avg try cnt 1.79004027354
sample round 1, target #samples 237156
334155 samples processed, 283057 succeeded with avg try cnt 1.6085311439
epoch 12: 99% completed, cur loss: 0.226 training completed, total loss 30.0368994772, validation score 0.824
sample round 0, target #samples 654055
506726 samples processed, 416681 succeeded with avg try cnt 1.79124558115
sample round 1, target #samples 237374
334334 samples processed, 274327 succeeded with avg try cnt 1.83506545109
epoch 13: 99% completed, cur loss: 0.226 training completed, total loss 28.5690755844, validation score 0.827
sample round 0, target #samples 654055
506726 samples processed, 416946 succeeded with avg try cnt 1.79165167672
sample round 1, target #samples 237109
334093 samples processed, 279062 succeeded with avg try cnt 1.70276139353
epoch 14: 99% completed, cur loss: 0.206 training completed, total loss 27.524065733, validation score 0.830
sample round 0, target #samples 654055
506726 samples processed, 416708 succeeded with avg try cnt 1.79219501425
sample round 1, target #samples 237347
334420 samples processed, 287614 succeeded with avg try cnt 1.50247554013
epoch 15: 99% completed, cur loss: 0.197 training completed, total loss 26.4079041034, validation score 0.833
sample round 0, target #samples 654055
506726 samples processed, 416875 succeeded with avg try cnt 1.78821229385
sample round 1, target #samples 237180
333968 samples processed, 273749 succeeded with avg try cnt 1.84388618771
epoch 16: 99% completed, cur loss: 0.205 training completed, total loss 25.4404604137, validation score 0.836
sample round 0, target #samples 654055
506726 samples processed, 416566 succeeded with avg try cnt 1.79613554635
sample round 1, target #samples 237489
334534 samples processed, 285327 succeeded with avg try cnt 1.5583102896
epoch 17: 99% completed, cur loss: 0.191 training completed, total loss 24.519077301, validation score 0.838
sample round 0, target #samples 654055
506726 samples processed, 416726 succeeded with avg try cnt 1.78990751717
sample round 1, target #samples 237329
334175 samples processed, 282974 succeeded with avg try cnt 1.60962844643
epoch 18: 99% completed, cur loss: 0.179 training completed, total loss 23.7582446486, validation score 0.840
sample round 0, target #samples 654055
506726 samples processed, 416558 succeeded with avg try cnt 1.79326768421
sample round 1, target #samples 237497
334339 samples processed, 280192 succeeded with avg try cnt 1.68844934902
epoch 19: 99% completed, cur loss: 0.230 training completed, total loss 23.1597882062, validation score 0.842
sample round 0, target #samples 654055
506726 samples processed, 416633 succeeded with avg try cnt 1.79723401651
sample round 1, target #samples 237422
334225 samples processed, 272918 succeeded with avg try cnt 1.87224734169
epoch 20: 99% completed, cur loss: 0.176 training completed, total loss 22.4027647525, validation score 0.844
sample round 0, target #samples 654055
506726 samples processed, 416582 succeeded with avg try cnt 1.79163045931
sample round 1, target #samples 237473
334426 samples processed, 269870 succeeded with avg try cnt 1.95845036499
epoch 21: 99% completed, cur loss: 0.163 training completed, total loss 21.770785071, validation score 0.846
sample round 0, target #samples 654055
506726 samples processed, 416623 succeeded with avg try cnt 1.79075567119
sample round 1, target #samples 237432
334545 samples processed, 272768 succeeded with avg try cnt 1.88370336696
epoch 22: 99% completed, cur loss: 0.166 training completed, total loss 21.2501583546, validation score 0.848
sample round 0, target #samples 654055
506726 samples processed, 416264 succeeded with avg try cnt 1.80109257587
sample round 1, target #samples 237791
335170 samples processed, 291418 succeeded with avg try cnt 1.42596545169
epoch 23: 99% completed, cur loss: 0.158 training completed, total loss 20.6235400289, validation score 0.850
sample round 0, target #samples 654055
506726 samples processed, 416653 succeeded with avg try cnt 1.79132515547
sample round 1, target #samples 237402
334420 samples processed, 262577 succeeded with avg try cnt 2.14292569418
epoch 24: 99% completed, cur loss: 0.148 training completed, total loss 20.0883183628, validation score 0.852
sample round 0, target #samples 654055
506726 samples processed, 417053 succeeded with avg try cnt 1.78986603621
sample round 1, target #samples 237002
334119 samples processed, 290910 succeeded with avg try cnt 1.41478120381
epoch 25: 99% completed, cur loss: 0.151 training completed, total loss 19.7009086609, validation score 0.853
sample round 0, target #samples 654055
506726 samples processed, 416668 succeeded with avg try cnt 1.79250866397
sample round 1, target #samples 237387
334467 samples processed, 287648 succeeded with avg try cnt 1.4998192235
epoch 26: 99% completed, cur loss: 0.148 training completed, total loss 19.2985699177, validation score 0.855
sample round 0, target #samples 654055
506726 samples processed, 416617 succeeded with avg try cnt 1.79335456786
sample round 1, target #samples 237438
334413 samples processed, 269350 succeeded with avg try cnt 1.96580657138
epoch 27: 99% completed, cur loss: 0.154 training completed, total loss 18.8195259869, validation score 0.857
sample round 0, target #samples 654055
506726 samples processed, 416693 succeeded with avg try cnt 1.79180595786
sample round 1, target #samples 237362
334450 samples processed, 264117 succeeded with avg try cnt 2.10460894225
epoch 28: 99% completed, cur loss: 0.147 training completed, total loss 18.4891936034, validation score 0.859
sample round 0, target #samples 654055
506726 samples processed, 416591 succeeded with avg try cnt 1.79407860467
sample round 1, target #samples 237464
334803 samples processed, 282250 succeeded with avg try cnt 1.64369530558
epoch 29: 99% completed, cur loss: 0.127 training completed, total loss 18.1669463739, validation score 0.860
sample round 0, target #samples 654055
506726 samples processed, 416716 succeeded with avg try cnt 1.79091995508
sample round 1, target #samples 237339
334581 samples processed, 291198 succeeded with avg try cnt 1.41800081045
epoch 30: 99% completed, cur loss: 0.135 training completed, total loss 17.8696987331, validation score 0.862
sample round 0, target #samples 654055
506726 samples processed, 416990 succeeded with avg try cnt 1.78558238807
sample round 1, target #samples 237065
334029 samples processed, 265345 succeeded with avg try cnt 2.07050443762
epoch 31: 99% completed, cur loss: 0.132 training completed, total loss 17.5691298619, validation score 0.863
sample round 0, target #samples 654055
506726 samples processed, 416535 succeeded with avg try cnt 1.7922335458
sample round 1, target #samples 237520
334841 samples processed, 284746 succeeded with avg try cnt 1.57970963596
epoch 32: 99% completed, cur loss: 0.128 training completed, total loss 17.2103584185, validation score 0.865
sample round 0, target #samples 654055
506726 samples processed, 416729 succeeded with avg try cnt 1.78984903858
sample round 1, target #samples 237326
334496 samples processed, 278894 succeeded with avg try cnt 1.72248237682
epoch 33: 99% completed, cur loss: 0.143 training completed, total loss 17.0755880624, validation score 0.866
sample round 0, target #samples 654055
506726 samples processed, 416463 succeeded with avg try cnt 1.79453156703
sample round 1, target #samples 237592
334873 samples processed, 274645 succeeded with avg try cnt 1.84035755248
epoch 34: 99% completed, cur loss: 0.132 training completed, total loss 16.637338113, validation score 0.868
sample round 0, target #samples 654055
506726 samples processed, 416918 succeeded with avg try cnt 1.79021774066
sample round 1, target #samples 237137
334282 samples processed, 267210 succeeded with avg try cnt 2.01746940609
epoch 35: 99% completed, cur loss: 0.128 training completed, total loss 16.5302084088, validation score 0.869
sample round 0, target #samples 654055
506726 samples processed, 416679 succeeded with avg try cnt 1.79048380168
sample round 1, target #samples 237376
334747 samples processed, 287801 succeeded with avg try cnt 1.50208998579
epoch 36: 99% completed, cur loss: 0.134 training completed, total loss 16.6554230452, validation score 0.870
sample round 0, target #samples 654055
506726 samples processed, 416281 succeeded with avg try cnt 1.79610887838
sample round 1, target #samples 237774
335211 samples processed, 292923 succeeded with avg try cnt 1.38680813729
epoch 37: 99% completed, cur loss: 0.120 training completed, total loss 15.8766069524, validation score 0.872
sample round 0, target #samples 654055
506726 samples processed, 416759 succeeded with avg try cnt 1.7904616337
sample round 1, target #samples 237296
334391 samples processed, 289641 succeeded with avg try cnt 1.44998463615
epoch 38: 99% completed, cur loss: 0.116 training completed, total loss 15.5280020833, validation score 0.873
sample round 0, target #samples 654055
506726 samples processed, 416475 succeeded with avg try cnt 1.7946743502
sample round 1, target #samples 237580
334681 samples processed, 260513 succeeded with avg try cnt 2.2057555669
epoch 39: 99% completed, cur loss: 0.117 training completed, total loss 14.9740056545, validation score 0.874
sample round 0, target #samples 654055
506726 samples processed, 416954 succeeded with avg try cnt 1.7868565837
sample round 1, target #samples 237101
334196 samples processed, 280653 succeeded with avg try cnt 1.67011932885
epoch 40: 99% completed, cur loss: 0.119 training completed, total loss 14.9587996379, validation score 0.875
sample round 0, target #samples 654055
506726 samples processed, 416746 succeeded with avg try cnt 1.79071184846
sample round 1, target #samples 237309
334468 samples processed, 287906 succeeded with avg try cnt 1.49486290664
epoch 41: 99% completed, cur loss: 0.113 training completed, total loss 14.8312215358, validation score 0.876
sample round 0, target #samples 654055
506726 samples processed, 416399 succeeded with avg try cnt 1.79237462146
sample round 1, target #samples 237656
334872 samples processed, 289623 succeeded with avg try cnt 1.4607161724
epoch 42: 99% completed, cur loss: 0.108 training completed, total loss 14.8314667195, validation score 0.877
sample round 0, target #samples 654055
506726 samples processed, 416578 succeeded with avg try cnt 1.79480673487
sample round 1, target #samples 237477
334524 samples processed, 261921 succeeded with avg try cnt 2.17108593813
epoch 43: 99% completed, cur loss: 0.125 training completed, total loss 14.4348778687, validation score 0.879
sample round 0, target #samples 654055
506726 samples processed, 416700 succeeded with avg try cnt 1.7906887449
sample round 1, target #samples 237355
334513 samples processed, 289742 succeeded with avg try cnt 1.44902361411
epoch 44: 99% completed, cur loss: 0.112 training completed, total loss 14.3072180673, validation score 0.880
sample round 0, target #samples 654055
506726 samples processed, 416202 succeeded with avg try cnt 1.79995290748
sample round 1, target #samples 237853
335121 samples processed, 277093 succeeded with avg try cnt 1.78252066996
epoch 45: 99% completed, cur loss: 0.119 training completed, total loss 14.8462937586, validation score 0.881
sample round 0, target #samples 654055
506726 samples processed, 417088 succeeded with avg try cnt 1.7873254565
sample round 1, target #samples 236967
333892 samples processed, 273113 succeeded with avg try cnt 1.86066939325
epoch 46: 99% completed, cur loss: 0.117 training completed, total loss 13.7263465263, validation score 0.882
sample round 0, target #samples 654055
506726 samples processed, 416927 succeeded with avg try cnt 1.78688115665
sample round 1, target #samples 237128
334164 samples processed, 273144 succeeded with avg try cnt 1.86489910084
epoch 47: 99% completed, cur loss: 0.124 training completed, total loss 13.9071078561, validation score 0.883
sample round 0, target #samples 654055
506726 samples processed, 416326 succeeded with avg try cnt 1.79988278416
sample round 1, target #samples 237729
335062 samples processed, 266939 succeeded with avg try cnt 2.04870026485
epoch 48: 99% completed, cur loss: 0.112 training completed, total loss 12.8918096684, validation score 0.884
sample round 0, target #samples 654055
506726 samples processed, 416597 succeeded with avg try cnt 1.79150593979
sample round 1, target #samples 237458
334784 samples processed, 262916 succeeded with avg try cnt 2.14638515724
epoch 49: 99% completed, cur loss: 0.109 training completed, total loss 12.8444551788, validation score 0.885
sample round 0, target #samples 654055
506726 samples processed, 416483 succeeded with avg try cnt 1.79325926869
sample round 1, target #samples 237572
335076 samples processed, 275979 succeeded with avg try cnt 1.81135158835
epoch 50: 99% completed, cur loss: 0.120 training completed, total loss 13.5028176084, validation score 0.886
sample round 0, target #samples 654055
506726 samples processed, 416524 succeeded with avg try cnt 1.79183912572
sample round 1, target #samples 237531
335042 samples processed, 274084 succeeded with avg try cnt 1.86010857985
epoch 51: 99% completed, cur loss: 0.118 training completed, total loss 12.8768489771, validation score 0.887
sample round 0, target #samples 654055
506726 samples processed, 416708 succeeded with avg try cnt 1.78952887874
sample round 1, target #samples 237347
334819 samples processed, 291230 succeeded with avg try cnt 1.42088727123
epoch 52: 99% completed, cur loss: 0.113 training completed, total loss 13.4837617204, validation score 0.888
sample round 0, target #samples 654055
506726 samples processed, 416915 succeeded with avg try cnt 1.79023781826
sample round 1, target #samples 237140
334426 samples processed, 275463 succeeded with avg try cnt 1.80587955551
epoch 53: 99% completed, cur loss: 0.114 training completed, total loss 13.2640287131, validation score 0.889
sample round 0, target #samples 654055
506726 samples processed, 416842 succeeded with avg try cnt 1.78907115886
sample round 1, target #samples 237213
334550 samples processed, 278799 succeeded with avg try cnt 1.72809802044
epoch 54: 99% completed, cur loss: 0.124 training completed, total loss 12.2647068389, validation score 0.890
sample round 0, target #samples 654055
506726 samples processed, 416842 succeeded with avg try cnt 1.79207469497
sample round 1, target #samples 237213
334545 samples processed, 273637 succeeded with avg try cnt 1.859035876
epoch 55: 99% completed, cur loss: 0.125 training completed, total loss 12.1182507463, validation score 0.891
sample round 0, target #samples 654055
506726 samples processed, 416421 succeeded with avg try cnt 1.79411220856
sample round 1, target #samples 237634
335176 samples processed, 268340 succeeded with avg try cnt 2.01064321383
epoch 56: 99% completed, cur loss: 0.100 training completed, total loss 11.2669392936, validation score 0.892
sample round 0, target #samples 654055
506726 samples processed, 416742 succeeded with avg try cnt 1.79191202231
sample round 1, target #samples 237313
334798 samples processed, 280733 succeeded with avg try cnt 1.67942493401
epoch 57: 99% completed, cur loss: 0.106 training completed, total loss 12.5022094958, validation score 0.893
sample round 0, target #samples 654055
506726 samples processed, 416732 succeeded with avg try cnt 1.78850436252
sample round 1, target #samples 237323
334795 samples processed, 259908 succeeded with avg try cnt 2.22157455715
epoch 58: 99% completed, cur loss: 0.116 training completed, total loss 11.3876278624, validation score 0.893
sample round 0, target #samples 654055
506726 samples processed, 416577 succeeded with avg try cnt 1.7918824131
sample round 1, target #samples 237478
335143 samples processed, 294147 succeeded with avg try cnt 1.35975889606
epoch 59: 99% completed, cur loss: 0.103 training completed, total loss 12.065322645, validation score 0.894
sample round 0, target #samples 654055
506726 samples processed, 417091 succeeded with avg try cnt 1.78722628875
sample round 1, target #samples 236964
334307 samples processed, 274017 succeeded with avg try cnt 1.84383450662
epoch 60: 99% completed, cur loss: 0.108 training completed, total loss 11.6309280992, validation score 0.895
sample round 0, target #samples 654055
506726 samples processed, 416817 succeeded with avg try cnt 1.78782055434
sample round 1, target #samples 237238
334719 samples processed, 292527 succeeded with avg try cnt 1.38615922633
epoch 61: 99% completed, cur loss: 0.100 training completed, total loss 11.9475244619, validation score 0.896
sample round 0, target #samples 654055
506726 samples processed, 416638 succeeded with avg try cnt 1.79423384329
sample round 1, target #samples 237417
334877 samples processed, 290227 succeeded with avg try cnt 1.44840418018
epoch 62: 99% completed, cur loss: 0.100 training completed, total loss 11.8039218858, validation score 0.897
sample round 0, target #samples 654055
506726 samples processed, 416692 succeeded with avg try cnt 1.79170946406
sample round 1, target #samples 237363
334725 samples processed, 264586 succeeded with avg try cnt 2.10355423189
epoch 63: 99% completed, cur loss: 0.094 training completed, total loss 9.71375119686, validation score 0.898
sample round 0, target #samples 654055
506726 samples processed, 416450 succeeded with avg try cnt 1.79688317925
sample round 1, target #samples 237605
335158 samples processed, 294398 succeeded with avg try cnt 1.35138485995
epoch 64: 99% completed, cur loss: 0.107 training completed, total loss 11.2512186691, validation score 0.898
sample round 0, target #samples 654055
506726 samples processed, 416656 succeeded with avg try cnt 1.78985062018
sample round 1, target #samples 237399
334769 samples processed, 279430 succeeded with avg try cnt 1.71426833196
epoch 65: 99% completed, cur loss: 0.100 training completed, total loss 10.3301414251, validation score 0.899
sample round 0, target #samples 654055
506726 samples processed, 416940 succeeded with avg try cnt 1.78657840457
sample round 1, target #samples 237115
334362 samples processed, 269328 succeeded with avg try cnt 1.96981747163
epoch 66: 99% completed, cur loss: 0.095 training completed, total loss 10.2199792825, validation score 0.900
sample round 0, target #samples 654055
506726 samples processed, 416713 succeeded with avg try cnt 1.79228629776
sample round 1, target #samples 237342
334737 samples processed, 273752 succeeded with avg try cnt 1.8604320699
epoch 67: 99% completed, cur loss: 0.105 training completed, total loss 11.1948451623, validation score 0.901
sample round 0, target #samples 654055
506726 samples processed, 416585 succeeded with avg try cnt 1.79127669023
sample round 1, target #samples 237470
334947 samples processed, 292261 succeeded with avg try cnt 1.40124409346
epoch 68: 99% completed, cur loss: 0.096 training completed, total loss 10.026660867, validation score 0.901
sample round 0, target #samples 654055
506726 samples processed, 416746 succeeded with avg try cnt 1.79346412443
sample round 1, target #samples 237309
334639 samples processed, 292701 succeeded with avg try cnt 1.37833830428
epoch 69: 99% completed, cur loss: 0.097 training completed, total loss 10.3559941538, validation score 0.902
sample round 0, target #samples 654055
506726 samples processed, 416959 succeeded with avg try cnt 1.78659532472
sample round 1, target #samples 237096
334254 samples processed, 281754 succeeded with avg try cnt 1.64527211681
epoch 70: 99% completed, cur loss: 0.107 training completed, total loss 10.3405425474, validation score 0.902
sample round 0, target #samples 654055
506726 samples processed, 416369 succeeded with avg try cnt 1.79690370801
sample round 1, target #samples 237686
335069 samples processed, 260463 succeeded with avg try cnt 2.21892936809
epoch 71: 99% completed, cur loss: 0.100 training completed, total loss 9.74809188209, validation score 0.903
sample round 0, target #samples 654055
506726 samples processed, 416682 succeeded with avg try cnt 1.79216764823
sample round 1, target #samples 237373
334734 samples processed, 281362 succeeded with avg try cnt 1.66388495959
epoch 72: 99% completed, cur loss: 0.101 training completed, total loss 9.79165949114, validation score 0.904
sample round 0, target #samples 654055
506726 samples processed, 416660 succeeded with avg try cnt 1.79148226372
sample round 1, target #samples 237395
334750 samples processed, 290472 succeeded with avg try cnt 1.43919895894
epoch 73: 99% completed, cur loss: 0.094 training completed, total loss 10.2519208863, validation score 0.905
sample round 0, target #samples 654055
506726 samples processed, 416780 succeeded with avg try cnt 1.79124718077
sample round 1, target #samples 237275
334515 samples processed, 273524 succeeded with avg try cnt 1.85971249324
epoch 74: 99% completed, cur loss: 0.098 training completed, total loss 9.73943430558, validation score 0.905
sample round 0, target #samples 654055
506726 samples processed, 416608 succeeded with avg try cnt 1.79252918811
sample round 1, target #samples 237447
334786 samples processed, 287275 succeeded with avg try cnt 1.51823165956
epoch 75: 99% completed, cur loss: 0.097 training completed, total loss 8.33185894787, validation score 0.906
sample round 0, target #samples 654055
506726 samples processed, 416562 succeeded with avg try cnt 1.79103710852
sample round 1, target #samples 237493
334806 samples processed, 293442 succeeded with avg try cnt 1.36693111416
epoch 76: 99% completed, cur loss: 0.096 training completed, total loss 8.54704891331, validation score 0.907
sample round 0, target #samples 654055
506726 samples processed, 416606 succeeded with avg try cnt 1.79357954518
sample round 1, target #samples 237449
334667 samples processed, 289221 succeeded with avg try cnt 1.47092361896
epoch 77: 99% completed, cur loss: 0.112 training completed, total loss 8.33841670677, validation score 0.907
sample round 0, target #samples 654055
506726 samples processed, 416883 succeeded with avg try cnt 1.7882883207
sample round 1, target #samples 237172
334222 samples processed, 289843 succeeded with avg try cnt 1.44475802417
epoch 78: 99% completed, cur loss: 0.090 training completed, total loss 7.49463367462, validation score 0.908
sample round 0, target #samples 654055
506726 samples processed, 416802 succeeded with avg try cnt 1.78499863244
sample round 1, target #samples 237253
334278 samples processed, 274863 succeeded with avg try cnt 1.81931725987
epoch 79: 99% completed, cur loss: 0.100 training completed, total loss 7.83054200001, validation score 0.908
sample round 0, target #samples 654055
506726 samples processed, 416721 succeeded with avg try cnt 1.79231428222
sample round 1, target #samples 237334
334413 samples processed, 262584 succeeded with avg try cnt 2.14725573531
epoch 80: 99% completed, cur loss: 0.092 training completed, total loss 7.1392772533, validation score 0.909
sample round 0, target #samples 654055
506726 samples processed, 416487 succeeded with avg try cnt 1.79404399177
sample round 1, target #samples 237568
334827 samples processed, 274583 succeeded with avg try cnt 1.84111179498
epoch 81: 99% completed, cur loss: 0.107 training completed, total loss 7.13350416534, validation score 0.909
sample round 0, target #samples 654055
506726 samples processed, 416668 succeeded with avg try cnt 1.79236946442
sample round 1, target #samples 237387
334595 samples processed, 261227 succeeded with avg try cnt 2.19117089734
epoch 82: 99% completed, cur loss: 0.106 training completed, total loss 4.96390280128, validation score 0.910
sample round 0, target #samples 654055
506726 samples processed, 416738 succeeded with avg try cnt 1.79088300083
sample round 1, target #samples 237317
334583 samples processed, 275331 succeeded with avg try cnt 1.8108567506
epoch 83: 99% completed, cur loss: 0.098 training completed, total loss 7.80147685483, validation score 0.911
sample round 0, target #samples 654055
506726 samples processed, 416844 succeeded with avg try cnt 1.79304248112
sample round 1, target #samples 237211
334449 samples processed, 272717 succeeded with avg try cnt 1.88242023783
epoch 84: 99% completed, cur loss: 0.123 training completed, total loss 5.51270996593, validation score 0.911
sample round 0, target #samples 654055
506726 samples processed, 416718 succeeded with avg try cnt 1.79289831493
sample round 1, target #samples 237337
334655 samples processed, 287701 succeeded with avg try cnt 1.50527457325
epoch 85: 99% completed, cur loss: 0.135 training completed, total loss 6.53473762795, validation score 0.912
sample round 0, target #samples 654055
506726 samples processed, 416885 succeeded with avg try cnt 1.78944553054
sample round 1, target #samples 237170
334375 samples processed, 275995 succeeded with avg try cnt 1.79395641225
epoch 86: 99% completed, cur loss: 0.108 training completed, total loss 5.27842818946, validation score 0.912
sample round 0, target #samples 654055
506726 samples processed, 416524 succeeded with avg try cnt 1.79320519346
sample round 1, target #samples 237531
334897 samples processed, 286094 succeeded with avg try cnt 1.5508958594
epoch 87: 99% completed, cur loss: 0.114 training completed, total loss 2.25209164433, validation score 0.913
sample round 0, target #samples 654055
506726 samples processed, 416687 succeeded with avg try cnt 1.78916548872
sample round 1, target #samples 237368
334634 samples processed, 278229 succeeded with avg try cnt 1.73971440792
epoch 88: 99% completed, cur loss: 0.135 training completed, total loss 4.5459356457, validation score 0.913
sample round 0, target #samples 654055
506726 samples processed, 416383 succeeded with avg try cnt 1.79674242224
sample round 1, target #samples 237672
335066 samples processed, 293385 succeeded with avg try cnt 1.3706767558
epoch 89: 99% completed, cur loss: 0.108 training completed, total loss 3.7976297047, validation score 0.914
sample round 0, target #samples 654055
506726 samples processed, 416977 succeeded with avg try cnt 1.78705060471
sample round 1, target #samples 237078
334163 samples processed, 270438 succeeded with avg try cnt 1.93281269644
epoch 90: 99% completed, cur loss: -0.496 training completed, total loss 0.310678474605, validation score 0.914
sample round 0, target #samples 654055
506726 samples processed, 416940 succeeded with avg try cnt 1.7838705809
sample round 1, target #samples 237115
334250 samples processed, 272010 succeeded with avg try cnt 1.89518400059
epoch 91: 99% completed, cur loss: 0.030 training completed, total loss -0.856807949021, validation score 0.915
sample round 0, target #samples 654055
506726 samples processed, 416969 succeeded with avg try cnt 1.78733191196
sample round 1, target #samples 237086
334237 samples processed, 277703 succeeded with avg try cnt 1.75246576378
epoch 92: 99% completed, cur loss: 0.140 training completed, total loss -2.99048859626, validation score 0.915
sample round 0, target #samples 654055
506726 samples processed, 416684 succeeded with avg try cnt 1.79275182152
sample round 1, target #samples 237371
334642 samples processed, 293365 succeeded with avg try cnt 1.36408569529
epoch 93: 99% completed, cur loss: 0.087 training completed, total loss -2.02309531532, validation score 0.916
sample round 0, target #samples 654055
506726 samples processed, 416881 succeeded with avg try cnt 1.78516171281
sample round 1, target #samples 237174
334300 samples processed, 289391 succeeded with avg try cnt 1.45523184895
epoch 94: 99% completed, cur loss: -0.035 training completed, total loss -3.12116039544, validation score 0.916
sample round 0, target #samples 654055
506726 samples processed, 417008 succeeded with avg try cnt 1.7841792004
sample round 1, target #samples 237047
334073 samples processed, 263194 succeeded with avg try cnt 2.1216669073
epoch 95: 99% completed, cur loss: 0.199 training completed, total loss -11.0086820442, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416851 succeeded with avg try cnt 1.78893177658
sample round 1, target #samples 237204
334360 samples processed, 269717 succeeded with avg try cnt 1.96170430488
epoch 96: 99% completed, cur loss: 0.114 training completed, total loss -17.7445939854, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416687 succeeded with avg try cnt 1.79090540382
sample round 1, target #samples 237368
334629 samples processed, 288059 succeeded with avg try cnt 1.49559291673
epoch 97: 99% completed, cur loss: 0.254 training completed, total loss -16.4399162978, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416175 succeeded with avg try cnt 1.79982459302
sample round 1, target #samples 237880
335314 samples processed, 286425 succeeded with avg try cnt 1.54632451776
epoch 98: 99% completed, cur loss: -0.230 training completed, total loss -29.9994706623, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416869 succeeded with avg try cnt 1.78837956288
sample round 1, target #samples 237186
334306 samples processed, 271874 succeeded with avg try cnt 1.89690077021
epoch 99: 99% completed, cur loss: -1.010 training completed, total loss -51.8447214328, validation score 0.916
best validation score at itr 97: 0.916730638792
5581.72320485 seconds elapsed for pretraining
saving output to output
***python stdtests.py:
running with options:  {'datafn': 'data/academic.pickle', 'repeat': 10, 'embdir': 'output', 'debug': False, 'cachefn': '/tmp/academic_raw', 'classifier': 'lr', 'stepsize': 4, 'scale': 1, 'starttime': 1980, 'test': 'all', 'nsteps': 15, 'datasetmod': 'core.dataset.citation', 'stepstride': 2}
updating cache for prefix /tmp/academic_raw
generating samples for years from 1980 to 1983, i.e. featidx from 0 to 3
label distribution: Counter({-1: 50641, 4: 148, 3: 137, 0: 68, 5: 38, 1: 28})
28/51060 positive samples at step 0
generating samples for years from 1982 to 1985, i.e. featidx from 2 to 5
label distribution: Counter({-1: 50546, 3: 186, 4: 150, 0: 106, 5: 42, 1: 30})
30/51060 positive samples at step 1
generating samples for years from 1984 to 1987, i.e. featidx from 4 to 7
label distribution: Counter({-1: 50525, 3: 238, 0: 135, 4: 97, 5: 50, 1: 15})
15/51060 positive samples at step 2
generating samples for years from 1986 to 1989, i.e. featidx from 6 to 9
label distribution: Counter({-1: 50511, 3: 252, 0: 139, 4: 91, 5: 53, 1: 14})
14/51060 positive samples at step 3
generating samples for years from 1988 to 1991, i.e. featidx from 8 to 11
label distribution: Counter({-1: 50085, 3: 338, 0: 278, 4: 245, 1: 61, 5: 53})
61/51060 positive samples at step 4
generating samples for years from 1990 to 1993, i.e. featidx from 10 to 13
label distribution: Counter({-1: 49619, 3: 440, 4: 405, 0: 361, 1: 130, 5: 76, 2: 29})
130/51060 positive samples at step 5
generating samples for years from 1992 to 1995, i.e. featidx from 12 to 15
label distribution: Counter({-1: 49309, 3: 521, 4: 520, 0: 294, 1: 235, 5: 135, 2: 46})
235/51060 positive samples at step 6
generating samples for years from 1994 to 1997, i.e. featidx from 14 to 17
label distribution: Counter({-1: 48803, 4: 649, 3: 645, 1: 485, 0: 248, 5: 199, 2: 31})
485/51060 positive samples at step 7
generating samples for years from 1996 to 1999, i.e. featidx from 16 to 19
label distribution: Counter({-1: 48647, 4: 756, 3: 664, 1: 461, 0: 335, 5: 160, 2: 37})
461/51060 positive samples at step 8
generating samples for years from 1998 to 2001, i.e. featidx from 18 to 21
label distribution: Counter({-1: 48897, 4: 785, 3: 643, 0: 301, 1: 212, 5: 159, 2: 63})
212/51060 positive samples at step 9
generating samples for years from 2000 to 2003, i.e. featidx from 20 to 23
label distribution: Counter({-1: 48602, 4: 785, 3: 678, 0: 394, 1: 336, 5: 223, 2: 42})
336/51060 positive samples at step 10
generating samples for years from 2002 to 2005, i.e. featidx from 22 to 25
label distribution: Counter({-1: 47334, 3: 1010, 0: 768, 4: 719, 5: 678, 1: 551})
551/51060 positive samples at step 11
generating samples for years from 2004 to 2007, i.e. featidx from 24 to 27
label distribution: Counter({-1: 46281, 3: 1652, 0: 954, 1: 860, 5: 659, 4: 654})
860/51060 positive samples at step 12
generating samples for years from 2006 to 2009, i.e. featidx from 26 to 29
label distribution: Counter({-1: 46129, 3: 1508, 1: 1206, 0: 1190, 4: 720, 5: 307})
1206/51060 positive samples at step 13
generating samples for years from 2008 to 2011, i.e. featidx from 28 to 31
label distribution: Counter({-1: 46161, 1: 1568, 0: 1445, 3: 746, 4: 719, 5: 372, 2: 49})
1568/51060 positive samples at step 14
merging graph from year 1980 to 1983
converting into graph nsize: 51060, esize: 1198, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1982 to 1985
converting into graph nsize: 51060, esize: 1965, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1984 to 1987
converting into graph nsize: 51060, esize: 3183, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1986 to 1989
converting into graph nsize: 51060, esize: 4883, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1988 to 1991
converting into graph nsize: 51060, esize: 8218, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1990 to 1993
converting into graph nsize: 51060, esize: 12946, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1992 to 1995
converting into graph nsize: 51060, esize: 18316, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1994 to 1997
converting into graph nsize: 51060, esize: 24695, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1996 to 1999
converting into graph nsize: 51060, esize: 31720, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1998 to 2001
converting into graph nsize: 51060, esize: 40351, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2000 to 2003
converting into graph nsize: 51060, esize: 50699, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2002 to 2005
converting into graph nsize: 51060, esize: 72125, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2004 to 2007
converting into graph nsize: 51060, esize: 101686, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2006 to 2009
converting into graph nsize: 51060, esize: 134741, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2008 to 2011
converting into graph nsize: 51060, esize: 147329, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
cache file /tmp/academic_raw updated
embedding shape is (51060, 48)
task 1: node label predict from current time step
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
precision mean: 0.719982971116 std: 0.00880015810048
recall mean: 0.710668035125 std: 0.0106282649371
f1 mean: 0.71522810503 std: 0.00691074757067
task 2: node label predict from previous time step
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
precision mean: 0.716660834889 std: 0.00936783930261
recall mean: 0.710322138451 std: 0.0150967305942
f1 mean: 0.713411401558 std: 0.0105378780357
task 3: link prediction from current time step
feature shape (1308110, 48)
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
precision mean: 0.907072710206 std: 0.000827686192746
recall mean: 0.926881072693 std: 0.000791835559012
f1 mean: 0.916869490292 std: 0.00051552318958
task 4: link prediction from previous time step
feature shape (1305714, 48)
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
precision mean: 0.885841924131 std: 0.00083767424281
recall mean: 0.886221485342 std: 0.00097032375374
f1 mean: 0.886031076364 std: 0.000548262180668
task 5 : changed link prediction from current time step
feature shape (446437, 48)
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
precision mean: 0.755020511735 std: 0.00150650586612
recall mean: 0.572703555995 std: 0.00190957884046
f1 mean: 0.651343229543 std: 0.00159266463889
task 6: changed link prediction from previous time step-
feature shape (445022, 48)
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
precision mean: 0.736502727446 std: 0.00132235936714
recall mean: 0.587783246509 std: 0.00194419537211
f1 mean: 0.653790866073 std: 0.00151509998723
Process finished with exit code 0

I was wondering why my results are quite different from the reported table (F1-scores) under this parameter setting?
Is there any parameter setting I didn't use it correctly?
Thanks.
Baiyang Chen

Dear Zhou,
I ran the experiments on the full academic dataset, and your offered academic_full.pickle. Here are the results I got from running the stdtest.py (based on 100 iterations pretraining and 10 times repeated testting).

sudo+ssh://yons@<IP_ADDRESS>:22/home/yons/anaconda3/envs/ympy27/bin/python -u /home/yons/ym/DT/main.py
Warning: passing language='c++' to cythonize() is deprecated. Instead, put "# distutils: language=c++" in your .pyx or .pxd file(s)
running build_ext
Using TensorFlow backend.
updating cache file for prefix /tmp/academic.cache
merging graph from year 0 to 3
converting into graph nsize: 51060, esize: 1198, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 2 to 5
converting into graph nsize: 51060, esize: 1965, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 4 to 7
converting into graph nsize: 51060, esize: 3183, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 6 to 9
converting into graph nsize: 51060, esize: 4883, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 8 to 11
converting into graph nsize: 51060, esize: 8218, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 10 to 13
converting into graph nsize: 51060, esize: 12946, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 12 to 15
converting into graph nsize: 51060, esize: 18316, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 14 to 17
converting into graph nsize: 51060, esize: 24695, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 16 to 19
converting into graph nsize: 51060, esize: 31720, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 18 to 21
converting into graph nsize: 51060, esize: 40351, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 20 to 23
converting into graph nsize: 51060, esize: 50699, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 22 to 25
converting into graph nsize: 51060, esize: 72125, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 24 to 27
converting into graph nsize: 51060, esize: 101686, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 26 to 29
converting into graph nsize: 51060, esize: 134741, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
merging graph from year 28 to 31
converting into graph nsize: 51060, esize: 147329, weight_type: <type 'float'>, name_type: <type 'str'>, directed: False
cache file /tmp/academic.cache updated
654055 edges in pretraining graphs
generating validation set
1308110 validation samples generated
sample round 0, target #samples 654055
506726 samples processed, 416839 succeeded with avg try cnt 1.79014199727
sample round 1, target #samples 237216
335812 samples processed, 288353 succeeded with avg try cnt 1.51324244936
epoch 0: 99% completed, cur loss: 2.069 training completed, total loss<PHONE_NUMBER>12, validation score 0.675
sample round 0, target #samples 654055
506726 samples processed, 416911 succeeded with avg try cnt 1.78721117936
sample round 1, target #samples 237144
332580 samples processed, 283606 succeeded with avg try cnt 1.56556631383
epoch 1: 99% completed, cur loss: 0.947 training completed, total loss<PHONE_NUMBER>93, validation score 0.728
sample round 0, target #samples 654055
506726 samples processed, 417133 succeeded with avg try cnt 1.78445723546
sample round 1, target #samples 236922
331841 samples processed, 261569 succeeded with avg try cnt 2.11877554297
epoch 2: 99% completed, cur loss: 0.646 training completed, total loss 92.755889833, validation score 0.756
sample round 0, target #samples 654055
506726 samples processed, 416726 succeeded with avg try cnt 1.79194722671
sample round 1, target #samples 237329
334706 samples processed, 291644 succeeded with avg try cnt 1.4043594245
epoch 3: 99% completed, cur loss: 0.515 training completed, total loss 71.1527889967, validation score 0.772
sample round 0, target #samples 654055
506726 samples processed, 416707 succeeded with avg try cnt 1.79144578805
sample round 1, target #samples 237348
333557 samples processed, 263819 succeeded with avg try cnt 2.09569439654
epoch 4: 99% completed, cur loss: 0.439 training completed, total loss 59.0625114739, validation score 0.784
sample round 0, target #samples 654055
506726 samples processed, 416502 succeeded with avg try cnt 1.79160244128
sample round 1, target #samples 237553
335083 samples processed, 270561 succeeded with avg try cnt 1.95904805201
epoch 5: 99% completed, cur loss: 0.391 training completed, total loss 51.3192759156, validation score 0.792
sample round 0, target #samples 654055
506726 samples processed, 416596 succeeded with avg try cnt 1.79267203718
sample round 1, target #samples 237459
335467 samples processed, 277054 succeeded with avg try cnt 1.78802327344
epoch 6: 99% completed, cur loss: 0.346 training completed, total loss 45.8155831695, validation score 0.799
sample round 0, target #samples 654055
506726 samples processed, 416600 succeeded with avg try cnt 1.7942318771
sample round 1, target #samples 237455
335505 samples processed, 286478 succeeded with avg try cnt 1.55429736315
epoch 7: 99% completed, cur loss: 0.305 training completed, total loss 41.4113515019, validation score 0.804
sample round 0, target #samples 654055
506726 samples processed, 416888 succeeded with avg try cnt 1.78908004068
sample round 1, target #samples 237167
334665 samples processed, 291558 succeeded with avg try cnt 1.41134525549
epoch 8: 99% completed, cur loss: 0.294 training completed, total loss 38.0732320845, validation score 0.809
sample round 0, target #samples 654055
506726 samples processed, 416851 succeeded with avg try cnt 1.78709658847
sample round 1, target #samples 237204
334130 samples processed, 271931 succeeded with avg try cnt 1.89884934046
epoch 9: 99% completed, cur loss: 0.277 training completed, total loss 35.6262742281, validation score 0.813
sample round 0, target #samples 654055
506726 samples processed, 416500 succeeded with avg try cnt 1.79443697479
sample round 1, target #samples 237555
334908 samples processed, 293863 succeeded with avg try cnt 1.36109003175
epoch 10: 99% completed, cur loss: 0.250 training completed, total loss 33.4194956273, validation score 0.817
sample round 0, target #samples 654055
506726 samples processed, 416776 succeeded with avg try cnt 1.78976956447
sample round 1, target #samples 237279
333987 samples processed, 268857 succeeded with avg try cnt 1.97401220723
epoch 11: 99% completed, cur loss: 0.259 training completed, total loss 31.6063426435, validation score 0.821
sample round 0, target #samples 654055
506726 samples processed, 416899 succeeded with avg try cnt 1.79004027354
sample round 1, target #samples 237156
334155 samples processed, 283057 succeeded with avg try cnt 1.6085311439
epoch 12: 99% completed, cur loss: 0.226 training completed, total loss 30.0368994772, validation score 0.824
sample round 0, target #samples 654055
506726 samples processed, 416681 succeeded with avg try cnt 1.79124558115
sample round 1, target #samples 237374
334334 samples processed, 274327 succeeded with avg try cnt 1.83506545109
epoch 13: 99% completed, cur loss: 0.226 training completed, total loss 28.5690755844, validation score 0.827
sample round 0, target #samples 654055
506726 samples processed, 416946 succeeded with avg try cnt 1.79165167672
sample round 1, target #samples 237109
334093 samples processed, 279062 succeeded with avg try cnt 1.70276139353
epoch 14: 99% completed, cur loss: 0.206 training completed, total loss 27.524065733, validation score 0.830
sample round 0, target #samples 654055
506726 samples processed, 416708 succeeded with avg try cnt 1.79219501425
sample round 1, target #samples 237347
334420 samples processed, 287614 succeeded with avg try cnt 1.50247554013
epoch 15: 99% completed, cur loss: 0.197 training completed, total loss 26.4079041034, validation score 0.833
sample round 0, target #samples 654055
506726 samples processed, 416875 succeeded with avg try cnt 1.78821229385
sample round 1, target #samples 237180
333968 samples processed, 273749 succeeded with avg try cnt 1.84388618771
epoch 16: 99% completed, cur loss: 0.205 training completed, total loss 25.4404604137, validation score 0.836
sample round 0, target #samples 654055
506726 samples processed, 416566 succeeded with avg try cnt 1.79613554635
sample round 1, target #samples 237489
334534 samples processed, 285327 succeeded with avg try cnt 1.5583102896
epoch 17: 99% completed, cur loss: 0.191 training completed, total loss 24.519077301, validation score 0.838
sample round 0, target #samples 654055
506726 samples processed, 416726 succeeded with avg try cnt 1.78990751717
sample round 1, target #samples 237329
334175 samples processed, 282974 succeeded with avg try cnt 1.60962844643
epoch 18: 99% completed, cur loss: 0.179 training completed, total loss 23.7582446486, validation score 0.840
sample round 0, target #samples 654055
506726 samples processed, 416558 succeeded with avg try cnt 1.79326768421
sample round 1, target #samples 237497
334339 samples processed, 280192 succeeded with avg try cnt 1.68844934902
epoch 19: 99% completed, cur loss: 0.230 training completed, total loss 23.1597882062, validation score 0.842
sample round 0, target #samples 654055
506726 samples processed, 416633 succeeded with avg try cnt 1.79723401651
sample round 1, target #samples 237422
334225 samples processed, 272918 succeeded with avg try cnt 1.87224734169
epoch 20: 99% completed, cur loss: 0.176 training completed, total loss 22.4027647525, validation score 0.844
sample round 0, target #samples 654055
506726 samples processed, 416582 succeeded with avg try cnt 1.79163045931
sample round 1, target #samples 237473
334426 samples processed, 269870 succeeded with avg try cnt 1.95845036499
epoch 21: 99% completed, cur loss: 0.163 training completed, total loss 21.770785071, validation score 0.846
sample round 0, target #samples 654055
506726 samples processed, 416623 succeeded with avg try cnt 1.79075567119
sample round 1, target #samples 237432
334545 samples processed, 272768 succeeded with avg try cnt 1.88370336696
epoch 22: 99% completed, cur loss: 0.166 training completed, total loss 21.2501583546, validation score 0.848
sample round 0, target #samples 654055
506726 samples processed, 416264 succeeded with avg try cnt 1.80109257587
sample round 1, target #samples 237791
335170 samples processed, 291418 succeeded with avg try cnt 1.42596545169
epoch 23: 99% completed, cur loss: 0.158 training completed, total loss 20.6235400289, validation score 0.850
sample round 0, target #samples 654055
506726 samples processed, 416653 succeeded with avg try cnt 1.79132515547
sample round 1, target #samples 237402
334420 samples processed, 262577 succeeded with avg try cnt 2.14292569418
epoch 24: 99% completed, cur loss: 0.148 training completed, total loss 20.0883183628, validation score 0.852
sample round 0, target #samples 654055
506726 samples processed, 417053 succeeded with avg try cnt 1.78986603621
sample round 1, target #samples 237002
334119 samples processed, 290910 succeeded with avg try cnt 1.41478120381
epoch 25: 99% completed, cur loss: 0.151 training completed, total loss 19.7009086609, validation score 0.853
sample round 0, target #samples 654055
506726 samples processed, 416668 succeeded with avg try cnt 1.79250866397
sample round 1, target #samples 237387
334467 samples processed, 287648 succeeded with avg try cnt 1.4998192235
epoch 26: 99% completed, cur loss: 0.148 training completed, total loss 19.2985699177, validation score 0.855
sample round 0, target #samples 654055
506726 samples processed, 416617 succeeded with avg try cnt 1.79335456786
sample round 1, target #samples 237438
334413 samples processed, 269350 succeeded with avg try cnt 1.96580657138
epoch 27: 99% completed, cur loss: 0.154 training completed, total loss 18.8195259869, validation score 0.857
sample round 0, target #samples 654055
506726 samples processed, 416693 succeeded with avg try cnt 1.79180595786
sample round 1, target #samples 237362
334450 samples processed, 264117 succeeded with avg try cnt 2.10460894225
epoch 28: 99% completed, cur loss: 0.147 training completed, total loss 18.4891936034, validation score 0.859
sample round 0, target #samples 654055
506726 samples processed, 416591 succeeded with avg try cnt 1.79407860467
sample round 1, target #samples 237464
334803 samples processed, 282250 succeeded with avg try cnt 1.64369530558
epoch 29: 99% completed, cur loss: 0.127 training completed, total loss 18.1669463739, validation score 0.860
sample round 0, target #samples 654055
506726 samples processed, 416716 succeeded with avg try cnt 1.79091995508
sample round 1, target #samples 237339
334581 samples processed, 291198 succeeded with avg try cnt 1.41800081045
epoch 30: 99% completed, cur loss: 0.135 training completed, total loss 17.8696987331, validation score 0.862
sample round 0, target #samples 654055
506726 samples processed, 416990 succeeded with avg try cnt 1.78558238807
sample round 1, target #samples 237065
334029 samples processed, 265345 succeeded with avg try cnt 2.07050443762
epoch 31: 99% completed, cur loss: 0.132 training completed, total loss 17.5691298619, validation score 0.863
sample round 0, target #samples 654055
506726 samples processed, 416535 succeeded with avg try cnt 1.7922335458
sample round 1, target #samples 237520
334841 samples processed, 284746 succeeded with avg try cnt 1.57970963596
epoch 32: 99% completed, cur loss: 0.128 training completed, total loss 17.2103584185, validation score 0.865
sample round 0, target #samples 654055
506726 samples processed, 416729 succeeded with avg try cnt 1.78984903858
sample round 1, target #samples 237326
334496 samples processed, 278894 succeeded with avg try cnt 1.72248237682
epoch 33: 99% completed, cur loss: 0.143 training completed, total loss 17.0755880624, validation score 0.866
sample round 0, target #samples 654055
506726 samples processed, 416463 succeeded with avg try cnt 1.79453156703
sample round 1, target #samples 237592
334873 samples processed, 274645 succeeded with avg try cnt 1.84035755248
epoch 34: 99% completed, cur loss: 0.132 training completed, total loss 16.637338113, validation score 0.868
sample round 0, target #samples 654055
506726 samples processed, 416918 succeeded with avg try cnt 1.79021774066
sample round 1, target #samples 237137
334282 samples processed, 267210 succeeded with avg try cnt 2.01746940609
epoch 35: 99% completed, cur loss: 0.128 training completed, total loss 16.5302084088, validation score 0.869
sample round 0, target #samples 654055
506726 samples processed, 416679 succeeded with avg try cnt 1.79048380168
sample round 1, target #samples 237376
334747 samples processed, 287801 succeeded with avg try cnt 1.50208998579
epoch 36: 99% completed, cur loss: 0.134 training completed, total loss 16.6554230452, validation score 0.870
sample round 0, target #samples 654055
506726 samples processed, 416281 succeeded with avg try cnt 1.79610887838
sample round 1, target #samples 237774
335211 samples processed, 292923 succeeded with avg try cnt 1.38680813729
epoch 37: 99% completed, cur loss: 0.120 training completed, total loss 15.8766069524, validation score 0.872
sample round 0, target #samples 654055
506726 samples processed, 416759 succeeded with avg try cnt 1.7904616337
sample round 1, target #samples 237296
334391 samples processed, 289641 succeeded with avg try cnt 1.44998463615
epoch 38: 99% completed, cur loss: 0.116 training completed, total loss 15.5280020833, validation score 0.873
sample round 0, target #samples 654055
506726 samples processed, 416475 succeeded with avg try cnt 1.7946743502
sample round 1, target #samples 237580
334681 samples processed, 260513 succeeded with avg try cnt 2.2057555669
epoch 39: 99% completed, cur loss: 0.117 training completed, total loss 14.9740056545, validation score 0.874
sample round 0, target #samples 654055
506726 samples processed, 416954 succeeded with avg try cnt 1.7868565837
sample round 1, target #samples 237101
334196 samples processed, 280653 succeeded with avg try cnt 1.67011932885
epoch 40: 99% completed, cur loss: 0.119 training completed, total loss 14.9587996379, validation score 0.875
sample round 0, target #samples 654055
506726 samples processed, 416746 succeeded with avg try cnt 1.79071184846
sample round 1, target #samples 237309
334468 samples processed, 287906 succeeded with avg try cnt 1.49486290664
epoch 41: 99% completed, cur loss: 0.113 training completed, total loss 14.8312215358, validation score 0.876
sample round 0, target #samples 654055
506726 samples processed, 416399 succeeded with avg try cnt 1.79237462146
sample round 1, target #samples 237656
334872 samples processed, 289623 succeeded with avg try cnt 1.4607161724
epoch 42: 99% completed, cur loss: 0.108 training completed, total loss 14.8314667195, validation score 0.877
sample round 0, target #samples 654055
506726 samples processed, 416578 succeeded with avg try cnt 1.79480673487
sample round 1, target #samples 237477
334524 samples processed, 261921 succeeded with avg try cnt 2.17108593813
epoch 43: 99% completed, cur loss: 0.125 training completed, total loss 14.4348778687, validation score 0.879
sample round 0, target #samples 654055
506726 samples processed, 416700 succeeded with avg try cnt 1.7906887449
sample round 1, target #samples 237355
334513 samples processed, 289742 succeeded with avg try cnt 1.44902361411
epoch 44: 99% completed, cur loss: 0.112 training completed, total loss 14.3072180673, validation score 0.880
sample round 0, target #samples 654055
506726 samples processed, 416202 succeeded with avg try cnt 1.79995290748
sample round 1, target #samples 237853
335121 samples processed, 277093 succeeded with avg try cnt 1.78252066996
epoch 45: 99% completed, cur loss: 0.119 training completed, total loss 14.8462937586, validation score 0.881
sample round 0, target #samples 654055
506726 samples processed, 417088 succeeded with avg try cnt 1.7873254565
sample round 1, target #samples 236967
333892 samples processed, 273113 succeeded with avg try cnt 1.86066939325
epoch 46: 99% completed, cur loss: 0.117 training completed, total loss 13.7263465263, validation score 0.882
sample round 0, target #samples 654055
506726 samples processed, 416927 succeeded with avg try cnt 1.78688115665
sample round 1, target #samples 237128
334164 samples processed, 273144 succeeded with avg try cnt 1.86489910084
epoch 47: 99% completed, cur loss: 0.124 training completed, total loss 13.9071078561, validation score 0.883
sample round 0, target #samples 654055
506726 samples processed, 416326 succeeded with avg try cnt 1.79988278416
sample round 1, target #samples 237729
335062 samples processed, 266939 succeeded with avg try cnt 2.04870026485
epoch 48: 99% completed, cur loss: 0.112 training completed, total loss 12.8918096684, validation score 0.884
sample round 0, target #samples 654055
506726 samples processed, 416597 succeeded with avg try cnt 1.79150593979
sample round 1, target #samples 237458
334784 samples processed, 262916 succeeded with avg try cnt 2.14638515724
epoch 49: 99% completed, cur loss: 0.109 training completed, total loss 12.8444551788, validation score 0.885
sample round 0, target #samples 654055
506726 samples processed, 416483 succeeded with avg try cnt 1.79325926869
sample round 1, target #samples 237572
335076 samples processed, 275979 succeeded with avg try cnt 1.81135158835
epoch 50: 99% completed, cur loss: 0.120 training completed, total loss 13.5028176084, validation score 0.886
sample round 0, target #samples 654055
506726 samples processed, 416524 succeeded with avg try cnt 1.79183912572
sample round 1, target #samples 237531
335042 samples processed, 274084 succeeded with avg try cnt 1.86010857985
epoch 51: 99% completed, cur loss: 0.118 training completed, total loss 12.8768489771, validation score 0.887
sample round 0, target #samples 654055
506726 samples processed, 416708 succeeded with avg try cnt 1.78952887874
sample round 1, target #samples 237347
334819 samples processed, 291230 succeeded with avg try cnt 1.42088727123
epoch 52: 99% completed, cur loss: 0.113 training completed, total loss 13.4837617204, validation score 0.888
sample round 0, target #samples 654055
506726 samples processed, 416915 succeeded with avg try cnt 1.79023781826
sample round 1, target #samples 237140
334426 samples processed, 275463 succeeded with avg try cnt 1.80587955551
epoch 53: 99% completed, cur loss: 0.114 training completed, total loss 13.2640287131, validation score 0.889
sample round 0, target #samples 654055
506726 samples processed, 416842 succeeded with avg try cnt 1.78907115886
sample round 1, target #samples 237213
334550 samples processed, 278799 succeeded with avg try cnt 1.72809802044
epoch 54: 99% completed, cur loss: 0.124 training completed, total loss 12.2647068389, validation score 0.890
sample round 0, target #samples 654055
506726 samples processed, 416842 succeeded with avg try cnt 1.79207469497
sample round 1, target #samples 237213
334545 samples processed, 273637 succeeded with avg try cnt 1.859035876
epoch 55: 99% completed, cur loss: 0.125 training completed, total loss 12.1182507463, validation score 0.891
sample round 0, target #samples 654055
506726 samples processed, 416421 succeeded with avg try cnt 1.79411220856
sample round 1, target #samples 237634
335176 samples processed, 268340 succeeded with avg try cnt 2.01064321383
epoch 56: 99% completed, cur loss: 0.100 training completed, total loss 11.2669392936, validation score 0.892
sample round 0, target #samples 654055
506726 samples processed, 416742 succeeded with avg try cnt 1.79191202231
sample round 1, target #samples 237313
334798 samples processed, 280733 succeeded with avg try cnt 1.67942493401
epoch 57: 99% completed, cur loss: 0.106 training completed, total loss 12.5022094958, validation score 0.893
sample round 0, target #samples 654055
506726 samples processed, 416732 succeeded with avg try cnt 1.78850436252
sample round 1, target #samples 237323
334795 samples processed, 259908 succeeded with avg try cnt 2.22157455715
epoch 58: 99% completed, cur loss: 0.116 training completed, total loss 11.3876278624, validation score 0.893
sample round 0, target #samples 654055
506726 samples processed, 416577 succeeded with avg try cnt 1.7918824131
sample round 1, target #samples 237478
335143 samples processed, 294147 succeeded with avg try cnt 1.35975889606
epoch 59: 99% completed, cur loss: 0.103 training completed, total loss 12.065322645, validation score 0.894
sample round 0, target #samples 654055
506726 samples processed, 417091 succeeded with avg try cnt 1.78722628875
sample round 1, target #samples 236964
334307 samples processed, 274017 succeeded with avg try cnt 1.84383450662
epoch 60: 99% completed, cur loss: 0.108 training completed, total loss 11.6309280992, validation score 0.895
sample round 0, target #samples 654055
506726 samples processed, 416817 succeeded with avg try cnt 1.78782055434
sample round 1, target #samples 237238
334719 samples processed, 292527 succeeded with avg try cnt 1.38615922633
epoch 61: 99% completed, cur loss: 0.100 training completed, total loss 11.9475244619, validation score 0.896
sample round 0, target #samples 654055
506726 samples processed, 416638 succeeded with avg try cnt 1.79423384329
sample round 1, target #samples 237417
334877 samples processed, 290227 succeeded with avg try cnt 1.44840418018
epoch 62: 99% completed, cur loss: 0.100 training completed, total loss 11.8039218858, validation score 0.897
sample round 0, target #samples 654055
506726 samples processed, 416692 succeeded with avg try cnt 1.79170946406
sample round 1, target #samples 237363
334725 samples processed, 264586 succeeded with avg try cnt 2.10355423189
epoch 63: 99% completed, cur loss: 0.094 training completed, total loss 9.71375119686, validation score 0.898
sample round 0, target #samples 654055
506726 samples processed, 416450 succeeded with avg try cnt 1.79688317925
sample round 1, target #samples 237605
335158 samples processed, 294398 succeeded with avg try cnt 1.35138485995
epoch 64: 99% completed, cur loss: 0.107 training completed, total loss 11.2512186691, validation score 0.898
sample round 0, target #samples 654055
506726 samples processed, 416656 succeeded with avg try cnt 1.78985062018
sample round 1, target #samples 237399
334769 samples processed, 279430 succeeded with avg try cnt 1.71426833196
epoch 65: 99% completed, cur loss: 0.100 training completed, total loss 10.3301414251, validation score 0.899
sample round 0, target #samples 654055
506726 samples processed, 416940 succeeded with avg try cnt 1.78657840457
sample round 1, target #samples 237115
334362 samples processed, 269328 succeeded with avg try cnt 1.96981747163
epoch 66: 99% completed, cur loss: 0.095 training completed, total loss 10.2199792825, validation score 0.900
sample round 0, target #samples 654055
506726 samples processed, 416713 succeeded with avg try cnt 1.79228629776
sample round 1, target #samples 237342
334737 samples processed, 273752 succeeded with avg try cnt 1.8604320699
epoch 67: 99% completed, cur loss: 0.105 training completed, total loss 11.1948451623, validation score 0.901
sample round 0, target #samples 654055
506726 samples processed, 416585 succeeded with avg try cnt 1.79127669023
sample round 1, target #samples 237470
334947 samples processed, 292261 succeeded with avg try cnt 1.40124409346
epoch 68: 99% completed, cur loss: 0.096 training completed, total loss 10.026660867, validation score 0.901
sample round 0, target #samples 654055
506726 samples processed, 416746 succeeded with avg try cnt 1.79346412443
sample round 1, target #samples 237309
334639 samples processed, 292701 succeeded with avg try cnt 1.37833830428
epoch 69: 99% completed, cur loss: 0.097 training completed, total loss 10.3559941538, validation score 0.902
sample round 0, target #samples 654055
506726 samples processed, 416959 succeeded with avg try cnt 1.78659532472
sample round 1, target #samples 237096
334254 samples processed, 281754 succeeded with avg try cnt 1.64527211681
epoch 70: 99% completed, cur loss: 0.107 training completed, total loss 10.3405425474, validation score 0.902
sample round 0, target #samples 654055
506726 samples processed, 416369 succeeded with avg try cnt 1.79690370801
sample round 1, target #samples 237686
335069 samples processed, 260463 succeeded with avg try cnt 2.21892936809
epoch 71: 99% completed, cur loss: 0.100 training completed, total loss 9.74809188209, validation score 0.903
sample round 0, target #samples 654055
506726 samples processed, 416682 succeeded with avg try cnt 1.79216764823
sample round 1, target #samples 237373
334734 samples processed, 281362 succeeded with avg try cnt 1.66388495959
epoch 72: 99% completed, cur loss: 0.101 training completed, total loss 9.79165949114, validation score 0.904
sample round 0, target #samples 654055
506726 samples processed, 416660 succeeded with avg try cnt 1.79148226372
sample round 1, target #samples 237395
334750 samples processed, 290472 succeeded with avg try cnt 1.43919895894
epoch 73: 99% completed, cur loss: 0.094 training completed, total loss 10.2519208863, validation score 0.905
sample round 0, target #samples 654055
506726 samples processed, 416780 succeeded with avg try cnt 1.79124718077
sample round 1, target #samples 237275
334515 samples processed, 273524 succeeded with avg try cnt 1.85971249324
epoch 74: 99% completed, cur loss: 0.098 training completed, total loss 9.73943430558, validation score 0.905
sample round 0, target #samples 654055
506726 samples processed, 416608 succeeded with avg try cnt 1.79252918811
sample round 1, target #samples 237447
334786 samples processed, 287275 succeeded with avg try cnt 1.51823165956
epoch 75: 99% completed, cur loss: 0.097 training completed, total loss 8.33185894787, validation score 0.906
sample round 0, target #samples 654055
506726 samples processed, 416562 succeeded with avg try cnt 1.79103710852
sample round 1, target #samples 237493
334806 samples processed, 293442 succeeded with avg try cnt 1.36693111416
epoch 76: 99% completed, cur loss: 0.096 training completed, total loss 8.54704891331, validation score 0.907
sample round 0, target #samples 654055
506726 samples processed, 416606 succeeded with avg try cnt 1.79357954518
sample round 1, target #samples 237449
334667 samples processed, 289221 succeeded with avg try cnt 1.47092361896
epoch 77: 99% completed, cur loss: 0.112 training completed, total loss 8.33841670677, validation score 0.907
sample round 0, target #samples 654055
506726 samples processed, 416883 succeeded with avg try cnt 1.7882883207
sample round 1, target #samples 237172
334222 samples processed, 289843 succeeded with avg try cnt 1.44475802417
epoch 78: 99% completed, cur loss: 0.090 training completed, total loss 7.49463367462, validation score 0.908
sample round 0, target #samples 654055
506726 samples processed, 416802 succeeded with avg try cnt 1.78499863244
sample round 1, target #samples 237253
334278 samples processed, 274863 succeeded with avg try cnt 1.81931725987
epoch 79: 99% completed, cur loss: 0.100 training completed, total loss 7.83054200001, validation score 0.908
sample round 0, target #samples 654055
506726 samples processed, 416721 succeeded with avg try cnt 1.79231428222
sample round 1, target #samples 237334
334413 samples processed, 262584 succeeded with avg try cnt 2.14725573531
epoch 80: 99% completed, cur loss: 0.092 training completed, total loss 7.1392772533, validation score 0.909
sample round 0, target #samples 654055
506726 samples processed, 416487 succeeded with avg try cnt 1.79404399177
sample round 1, target #samples 237568
334827 samples processed, 274583 succeeded with avg try cnt 1.84111179498
epoch 81: 99% completed, cur loss: 0.107 training completed, total loss 7.13350416534, validation score 0.909
sample round 0, target #samples 654055
506726 samples processed, 416668 succeeded with avg try cnt 1.79236946442
sample round 1, target #samples 237387
334595 samples processed, 261227 succeeded with avg try cnt 2.19117089734
epoch 82: 99% completed, cur loss: 0.106 training completed, total loss 4.96390280128, validation score 0.910
sample round 0, target #samples 654055
506726 samples processed, 416738 succeeded with avg try cnt 1.79088300083
sample round 1, target #samples 237317
334583 samples processed, 275331 succeeded with avg try cnt 1.8108567506
epoch 83: 99% completed, cur loss: 0.098 training completed, total loss 7.80147685483, validation score 0.911
sample round 0, target #samples 654055
506726 samples processed, 416844 succeeded with avg try cnt 1.79304248112
sample round 1, target #samples 237211
334449 samples processed, 272717 succeeded with avg try cnt 1.88242023783
epoch 84: 99% completed, cur loss: 0.123 training completed, total loss 5.51270996593, validation score 0.911
sample round 0, target #samples 654055
506726 samples processed, 416718 succeeded with avg try cnt 1.79289831493
sample round 1, target #samples 237337
334655 samples processed, 287701 succeeded with avg try cnt 1.50527457325
epoch 85: 99% completed, cur loss: 0.135 training completed, total loss 6.53473762795, validation score 0.912
sample round 0, target #samples 654055
506726 samples processed, 416885 succeeded with avg try cnt 1.78944553054
sample round 1, target #samples 237170
334375 samples processed, 275995 succeeded with avg try cnt 1.79395641225
epoch 86: 99% completed, cur loss: 0.108 training completed, total loss 5.27842818946, validation score 0.912
sample round 0, target #samples 654055
506726 samples processed, 416524 succeeded with avg try cnt 1.79320519346
sample round 1, target #samples 237531
334897 samples processed, 286094 succeeded with avg try cnt 1.5508958594
epoch 87: 99% completed, cur loss: 0.114 training completed, total loss 2.25209164433, validation score 0.913
sample round 0, target #samples 654055
506726 samples processed, 416687 succeeded with avg try cnt 1.78916548872
sample round 1, target #samples 237368
334634 samples processed, 278229 succeeded with avg try cnt 1.73971440792
epoch 88: 99% completed, cur loss: 0.135 training completed, total loss 4.5459356457, validation score 0.913
sample round 0, target #samples 654055
506726 samples processed, 416383 succeeded with avg try cnt 1.79674242224
sample round 1, target #samples 237672
335066 samples processed, 293385 succeeded with avg try cnt 1.3706767558
epoch 89: 99% completed, cur loss: 0.108 training completed, total loss 3.7976297047, validation score 0.914
sample round 0, target #samples 654055
506726 samples processed, 416977 succeeded with avg try cnt 1.78705060471
sample round 1, target #samples 237078
334163 samples processed, 270438 succeeded with avg try cnt 1.93281269644
epoch 90: 99% completed, cur loss: -0.496 training completed, total loss 0.310678474605, validation score 0.914
sample round 0, target #samples 654055
506726 samples processed, 416940 succeeded with avg try cnt 1.7838705809
sample round 1, target #samples 237115
334250 samples processed, 272010 succeeded with avg try cnt 1.89518400059
epoch 91: 99% completed, cur loss: 0.030 training completed, total loss -0.856807949021, validation score 0.915
sample round 0, target #samples 654055
506726 samples processed, 416969 succeeded with avg try cnt 1.78733191196
sample round 1, target #samples 237086
334237 samples processed, 277703 succeeded with avg try cnt 1.75246576378
epoch 92: 99% completed, cur loss: 0.140 training completed, total loss -2.99048859626, validation score 0.915
sample round 0, target #samples 654055
506726 samples processed, 416684 succeeded with avg try cnt 1.79275182152
sample round 1, target #samples 237371
334642 samples processed, 293365 succeeded with avg try cnt 1.36408569529
epoch 93: 99% completed, cur loss: 0.087 training completed, total loss -2.02309531532, validation score 0.916
sample round 0, target #samples 654055
506726 samples processed, 416881 succeeded with avg try cnt 1.78516171281
sample round 1, target #samples 237174
334300 samples processed, 289391 succeeded with avg try cnt 1.45523184895
epoch 94: 99% completed, cur loss: -0.035 training completed, total loss -3.12116039544, validation score 0.916
sample round 0, target #samples 654055
506726 samples processed, 417008 succeeded with avg try cnt 1.7841792004
sample round 1, target #samples 237047
334073 samples processed, 263194 succeeded with avg try cnt 2.1216669073
epoch 95: 99% completed, cur loss: 0.199 training completed, total loss -11.0086820442, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416851 succeeded with avg try cnt 1.78893177658
sample round 1, target #samples 237204
334360 samples processed, 269717 succeeded with avg try cnt 1.96170430488
epoch 96: 99% completed, cur loss: 0.114 training completed, total loss -17.7445939854, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416687 succeeded with avg try cnt 1.79090540382
sample round 1, target #samples 237368
334629 samples processed, 288059 succeeded with avg try cnt 1.49559291673
epoch 97: 99% completed, cur loss: 0.254 training completed, total loss -16.4399162978, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416175 succeeded with avg try cnt 1.79982459302
sample round 1, target #samples 237880
335314 samples processed, 286425 succeeded with avg try cnt 1.54632451776
epoch 98: 99% completed, cur loss: -0.230 training completed, total loss -29.9994706623, validation score 0.917
sample round 0, target #samples 654055
506726 samples processed, 416869 succeeded with avg try cnt 1.78837956288
sample round 1, target #samples 237186
334306 samples processed, 271874 succeeded with avg try cnt 1.89690077021
epoch 99: 99% completed, cur loss: -1.010 training completed, total loss -51.8447214328, validation score 0.916
best validation score at itr 97: 0.916730638792
5581.72320485 seconds elapsed for pretraining
saving output to output
***python stdtests.py:
running with options:  {'datafn': 'data/academic.pickle', 'repeat': 10, 'embdir': 'output', 'debug': False, 'cachefn': '/tmp/academic_raw', 'classifier': 'lr', 'stepsize': 4, 'scale': 1, 'starttime': 1980, 'test': 'all', 'nsteps': 15, 'datasetmod': 'core.dataset.citation', 'stepstride': 2}
updating cache for prefix /tmp/academic_raw
generating samples for years from 1980 to 1983, i.e. featidx from 0 to 3
label distribution: Counter({-1: 50641, 4: 148, 3: 137, 0: 68, 5: 38, 1: 28})
28/51060 positive samples at step 0
generating samples for years from 1982 to 1985, i.e. featidx from 2 to 5
label distribution: Counter({-1: 50546, 3: 186, 4: 150, 0: 106, 5: 42, 1: 30})
30/51060 positive samples at step 1
generating samples for years from 1984 to 1987, i.e. featidx from 4 to 7
label distribution: Counter({-1: 50525, 3: 238, 0: 135, 4: 97, 5: 50, 1: 15})
15/51060 positive samples at step 2
generating samples for years from 1986 to 1989, i.e. featidx from 6 to 9
label distribution: Counter({-1: 50511, 3: 252, 0: 139, 4: 91, 5: 53, 1: 14})
14/51060 positive samples at step 3
generating samples for years from 1988 to 1991, i.e. featidx from 8 to 11
label distribution: Counter({-1: 50085, 3: 338, 0: 278, 4: 245, 1: 61, 5: 53})
61/51060 positive samples at step 4
generating samples for years from 1990 to 1993, i.e. featidx from 10 to 13
label distribution: Counter({-1: 49619, 3: 440, 4: 405, 0: 361, 1: 130, 5: 76, 2: 29})
130/51060 positive samples at step 5
generating samples for years from 1992 to 1995, i.e. featidx from 12 to 15
label distribution: Counter({-1: 49309, 3: 521, 4: 520, 0: 294, 1: 235, 5: 135, 2: 46})
235/51060 positive samples at step 6
generating samples for years from 1994 to 1997, i.e. featidx from 14 to 17
label distribution: Counter({-1: 48803, 4: 649, 3: 645, 1: 485, 0: 248, 5: 199, 2: 31})
485/51060 positive samples at step 7
generating samples for years from 1996 to 1999, i.e. featidx from 16 to 19
label distribution: Counter({-1: 48647, 4: 756, 3: 664, 1: 461, 0: 335, 5: 160, 2: 37})
461/51060 positive samples at step 8
generating samples for years from 1998 to 2001, i.e. featidx from 18 to 21
label distribution: Counter({-1: 48897, 4: 785, 3: 643, 0: 301, 1: 212, 5: 159, 2: 63})
212/51060 positive samples at step 9
generating samples for years from 2000 to 2003, i.e. featidx from 20 to 23
label distribution: Counter({-1: 48602, 4: 785, 3: 678, 0: 394, 1: 336, 5: 223, 2: 42})
336/51060 positive samples at step 10
generating samples for years from 2002 to 2005, i.e. featidx from 22 to 25
label distribution: Counter({-1: 47334, 3: 1010, 0: 768, 4: 719, 5: 678, 1: 551})
551/51060 positive samples at step 11
generating samples for years from 2004 to 2007, i.e. featidx from 24 to 27
label distribution: Counter({-1: 46281, 3: 1652, 0: 954, 1: 860, 5: 659, 4: 654})
860/51060 positive samples at step 12
generating samples for years from 2006 to 2009, i.e. featidx from 26 to 29
label distribution: Counter({-1: 46129, 3: 1508, 1: 1206, 0: 1190, 4: 720, 5: 307})
1206/51060 positive samples at step 13
generating samples for years from 2008 to 2011, i.e. featidx from 28 to 31
label distribution: Counter({-1: 46161, 1: 1568, 0: 1445, 3: 746, 4: 719, 5: 372, 2: 49})
1568/51060 positive samples at step 14
merging graph from year 1980 to 1983
converting into graph nsize: 51060, esize: 1198, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1982 to 1985
converting into graph nsize: 51060, esize: 1965, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1984 to 1987
converting into graph nsize: 51060, esize: 3183, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1986 to 1989
converting into graph nsize: 51060, esize: 4883, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1988 to 1991
converting into graph nsize: 51060, esize: 8218, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1990 to 1993
converting into graph nsize: 51060, esize: 12946, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1992 to 1995
converting into graph nsize: 51060, esize: 18316, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1994 to 1997
converting into graph nsize: 51060, esize: 24695, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1996 to 1999
converting into graph nsize: 51060, esize: 31720, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 1998 to 2001
converting into graph nsize: 51060, esize: 40351, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2000 to 2003
converting into graph nsize: 51060, esize: 50699, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2002 to 2005
converting into graph nsize: 51060, esize: 72125, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2004 to 2007
converting into graph nsize: 51060, esize: 101686, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2006 to 2009
converting into graph nsize: 51060, esize: 134741, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
merging graph from year 2008 to 2011
converting into graph nsize: 51060, esize: 147329, weight_type: <type 'float'>, name_type: <type 'int'>, directed: False
cache file /tmp/academic_raw updated
embedding shape is (51060, 48)
task 1: node label predict from current time step
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
classifying with pos:neg = 7443:7443
precision mean: 0.719982971116 std: 0.00880015810048
recall mean: 0.710668035125 std: 0.0106282649371
f1 mean: 0.71522810503 std: 0.00691074757067
task 2: node label predict from previous time step
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
classifying with pos:neg = 7295:7295
precision mean: 0.716660834889 std: 0.00936783930261
recall mean: 0.710322138451 std: 0.0150967305942
f1 mean: 0.713411401558 std: 0.0105378780357
task 3: link prediction from current time step
feature shape (1308110, 48)
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
classifying with pos:neg = 654055:654055
precision mean: 0.907072710206 std: 0.000827686192746
recall mean: 0.926881072693 std: 0.000791835559012
f1 mean: 0.916869490292 std: 0.00051552318958
task 4: link prediction from previous time step
feature shape (1305714, 48)
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
classifying with pos:neg = 652857:652857
precision mean: 0.885841924131 std: 0.00083767424281
recall mean: 0.886221485342 std: 0.00097032375374
f1 mean: 0.886031076364 std: 0.000548262180668
task 5 : changed link prediction from current time step
feature shape (446437, 48)
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
classifying with pos:neg = 296284:150153
precision mean: 0.755020511735 std: 0.00150650586612
recall mean: 0.572703555995 std: 0.00190957884046
f1 mean: 0.651343229543 std: 0.00159266463889
task 6: changed link prediction from previous time step-
feature shape (445022, 48)
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
classifying with pos:neg = 295193:149829
precision mean: 0.736502727446 std: 0.00132235936714
recall mean: 0.587783246509 std: 0.00194419537211
f1 mean: 0.653790866073 std: 0.00151509998723
Process finished with exit code 0

I was wondering why my results are quite different from the reported table (F1-scores) under this parameter setting?
Is there any parameter setting I didn't use it correctly?
Thanks.
Baiyang Chen


Animate-out slide-out-from-top doesn't seem to work

Hey,
I just started using the package and animate-out slide-out-from-top doesn't seem to be working properly.
Is it just me, or is there anything I am missing?

I'm seeing the same problem

Try to use slide-out-to-top


Flipped image card, always show White POV

Steps

As White: make a move
Share the new URL with your opponent

Expected
The image card (as displayed by Whatsapp or Twitter or other) should show the board from the point of view of the Black
Observed
The image card shows the board from the point of view of the White
How to fix
I suspect that the image card generation currently only takes the state of the board into account, but doesn't take into account who was the last player. Ideally, the generated image should be tailored for the next player (the one who will have to read the board and make the next move).

I discovered this while testing #8. I have not thoroughly tested all possible combinations of {last player color} x {Copy or Share} x {target service that displays a card}.
If you can reproduce my observation and agree with the intent, then let's fix it!

Works on my machine LOL
The FEN (in URL) indicates whose's move it is and orients the board accordingly in the preview. Are you not seeing that?

The FEN (board position in the URL) shows who's move it is. I just never got around to changing the code to flip the board. One way to approach it is to rewrite the FEN to reverse the board.  Any ideas? Lots of string manipulation.

I implemented this - check it out :)
I'll highlight the last move soon (I noticed a pull request in chess-image-generator that implements this in the lib)

It works!
And yes, showing the last move in the card image would be awesome.

Done - check it out :)


Cleanup NU1301

Docs Build status updates of commit 162406d:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

docs/reference/errors-and-warnings/NU1301.md
:white_check_mark:Succeeded
View

docs/reference/errors-and-warnings/NU1801.md
:white_check_mark:Succeeded
View

For more details, please refer to the build report.
Note: Broken links written as relative paths are included in the above build report. For broken links written as absolute paths or external URLs, see the broken link report.
For any questions, please:Try searching the docs.microsoft.com contributor guidesPost your question in the Docs support channel

Docs Build status updates of commit 35fe3d5:
:white_check_mark: Validation status: passed

File
Status
Preview URL
Details

docs/reference/errors-and-warnings/NU1301.md
:white_check_mark:Succeeded
View

docs/reference/errors-and-warnings/NU1801.md
:white_check_mark:Succeeded
View

For more details, please refer to the build report.
Note: Broken links written as relative paths are included in the above build report. For broken links written as absolute paths or external URLs, see the broken link report.
For any questions, please:Try searching the docs.microsoft.com contributor guidesPost your question in the Docs support channel

@nkolev92  You might check this https://github.com/NuGet/docs.microsoft.com-nuget/issues/2900,  and add https://github.com/Microsoft/artifacts-credprovider#setup as a potential solution

Thanks @chucklu
I'll take a look and add that.


when sending hitting enter results in the send being "declined"

When you type in your password fully on send, and hit enter, it will decline the transaction. If your password is correct, and hit enter the transaction should be sent.
Steps to reproduce:
1.) Login to Qt wallet.
2.) Create any send transaction.
3.) Enter full password in confirmation box.
4.) Hit "enter" button on keyboard.
Current behavior: transaction dialog will close.
Expected behavior: transaction will be sent.

Yes, we should fix that, we have our custom default button management

Verified with the latest build - https://ftp.mwc.mw/nightly_builds/05-26-2020/
Hence closing this ticket.


feat: Introduce Automated UATs

The design is described in the following 2 internal docs:

KF053 - Automated UATs: Design
KF064 - Automated UATs: Scenarios

The UATs are not yet integrated with the repo's CI. In order to run you will need:

a Kubeflow installation integrated with MLFlow

make sure kubeflow-profiles includes this fix: https://github.com/canonical/kubeflow-profiles-operator/commit/142668739552b67545a73797c683e78fb0582804

(only part of latest/edge at the moment)

make sure kfp-api includes this fix: https://github.com/canonical/kfp-operators/commit/e4d73fa8ee1fb2ee3b67af157c9e803a4972c094

(not yet published)

To run:
# fetch code
git clone git@github.com:canonical/bundle-kubeflow.git
cd bundle-kubeflow

# setup tox
python3 -m venv venv
source venv/bin/activate
pip install tox

# run UATs
tox -e uats

Closing this PR in favour of https://github.com/canonical/charmed-kubeflow-uats/pull/1, since we've agreed to move the UAT code to a new repo.


consider switching to glob for file matching to get consistent behaviour on windows

At the moment patterns like: app/**/* fail to find anything on windows because of: https://github.com/jshint/jshint/blob/master/src/cli.js#L415.
Maybe it would be better to use glob for file matching so that you get consistent behaviour on windows and linux.
Also see: #1904 and https://github.com/STRML/JSXHint/issues/37#issuecomment-64379358

Following along with this article:
http://blog.keithcirkel.co.uk/how-to-use-npm-as-a-build-tool/#usingmultiplefiles
and this will be a show stopper on windows; seems a shame to keep the project on Grunt just for this reason.

I'm all for it. I'm even more all for it if it shrinks dependency sizes.