Subreport: Logs for com.simiacryptus.ref.lang.ReferenceCountingBase
In this apply, we use a network to learn this target input, given it's pre-evaluated output:
TrainingTester.java:332 executed in 0.03 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(input_target)).flatMap(RefArrays::stream).map(x -> {
try {
return x.prettyPrint();
} finally {
x.freeRef();
}
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ 0.13885307140711833 ], [ -0.9605131948757784 ], [ -0.4862244553458821 ], [ -0.2628320168754166 ], [ 0.2880959368880065 ], [ -0.5786731720086329 ], [ 0.07213722384549404 ], [ -0.7831422581463763 ], ... ],
[ [ 0.132100368353119 ], [ 0.44433138884184875 ], [ 0.6653352295898849 ], [ -0.728548855528443 ], [ 0.6073089871848227 ], [ -0.25554252619033635 ], [ -0.02041818185275912 ], [ 0.061239004024502774 ], ... ],
[ [ -0.16207225298894157 ], [ 0.7627261339704554 ], [ -0.41388809613866573 ], [ -0.7180515116662314 ], [ -0.7948784317241036 ], [ -0.2889544536728814 ], [ -0.7193196049768309 ], [ 0.14477185950991256 ], ... ],
[ [ -0.19332195842908906 ], [ 0.28745720132889385 ], [ 0.2835686020500652 ], [ -0.30682796319246064 ], [ -0.5556978093206963 ], [ -0.14552537320366143 ], [ 0.17532153587619925 ], [ 0.5684122642430773 ], ... ],
[ [ 0.7129146134840232 ], [ -0.8368166655358056 ], [ -0.2988891867536638 ], [ 0.33303230734273725 ], [ 0.25625025660557155 ], [ 0.5836213506043142 ], [ -0.8269504737626425 ], [ 0.5643878230080333 ], ... ],
[ [ -0.7431421942943675 ], [ -0.335031140650786 ], [ 0.7924048436589672 ], [ 0.565024195369352 ], [ -0.8707869037755998 ], [ -0.7486973892162765 ], [ 0.29169452449171085 ], [ -0.5772974273770299 ], ... ],
[ [ 0.7540395281405252 ], [ 0.30802488255994054 ], [ -0.16741682753741416 ], [ -0.3745130303135731 ], [ 0.45289336744314035 ], [ 0.37060419946117507 ], [ 0.14464739900119983 ], [ -0.8269038470635532 ], ... ],
[ [ 0.7202121948389317 ], [ -0.8835851435281408 ], [ -0.8839299727458072 ], [ 0.15924352250356844 ], [ -0.08846359633688117 ], [ 0.2970781782481584 ], [ 0.722958902349695 ], [ -0.8974171603090784 ], ... ],
...
]
[
[ [ -0.8503135057212028 ], [ 0.6982341786010395 ], [ 0.41336019020680403 ], [ 0.7722359890905004 ], [ 0.07111980795099071 ], [ 0.32029866048772204 ], [ 0.12400208179643735 ], [ 0.9286498960478287 ], ... ],
[ [ 0.3953045521856724 ], [ 0.056908653368406226 ], [ -0.22275670312114437 ], [ 0.17071132405996692 ], [ -0.8638960877819624 ], [ -0.748325360509658 ], [ 0.12059374814690349 ], [ -0.6739765674395322 ], ... ],
[ [ -0.7386944490052816 ], [ -0.20004952290251787 ], [ 0.5987330177407684 ], [ -0.5073866499565822 ], [ 0.09842259223057259 ], [ 0.06194027469587926 ], [ 0.06853886462075898 ], [ -0.5060788904142908 ], ... ],
[ [ 0.11591234181723054 ], [ -0.8155439438012022 ], [ -0.9174987859924093 ], [ -0.6720861150555335 ], [ -0.7699735841205193 ], [ -0.27375964573292855 ], [ 0.12460724941579437 ], [ 0.6938534278601087 ], ... ],
[ [ 0.4671922369176331 ], [ 0.6676110861856142 ], [ 0.15162652688649758 ], [ -0.8851547494547696 ], [ 0.0843787782457952 ], [ 0.8414358489873517 ], [ -0.2267156596973099 ], [ 0.6648967307470095 ], ... ],
[ [ 0.9301560359246155 ], [ -0.5351488249270635 ], [ -0.17555696938716392 ], [ -0.10990084223923446 ], [ 0.7959535626513539 ], [ -0.9863492298009648 ], [ 0.7052026588597684 ], [ 0.8334762905004489 ], ... ],
[ [ -0.0837008483397097 ], [ 0.4779591748628409 ], [ -0.1201306509783524 ], [ -0.25925240794451954 ], [ -0.903656792259953 ], [ 0.08484034162743948 ], [ 0.6849519229833034 ], [ 0.5414329272100302 ], ... ],
[ [ -0.09939523962167618 ], [ 0.4654949883866575 ], [ 0.7781288390570116 ], [ 0.8949104588474552 ], [ 0.7414579675264359 ], [ -0.9123179168052029 ], [ -0.0569365798937822 ], [ 0.9249231966317939 ], ... ],
...
]
[
[ [ 0.20236339104861578 ], [ 0.08048544879103847 ], [ -0.7331816726349831 ], [ -0.5420867821142423 ], [ 0.32016121674768816 ], [ -0.40676071306771355 ], [ 0.7139279655424293 ], [ -0.8985237822429553 ], ... ],
[ [ -0.8445876218070683 ], [ 0.7504386088922077 ], [ 0.5516283689415267 ], [ 0.8670823782266939 ], [ 0.5467268791084214 ], [ 0.039809562908508456 ], [ 0.2448172939469513 ], [ 0.38136778261702364 ], ... ],
[ [ -0.5209382742327626 ], [ -0.1843773052262021 ], [ -0.7672815829085757 ], [ 0.19234454005570734 ], [ -0.4920520215013049 ], [ 0.9466145780165116 ], [ 0.6341304524429021 ], [ 0.022255174932743538 ], ... ],
[ [ 0.7507820421034774 ], [ -0.24481802561306587 ], [ 0.41757391722469284 ], [ 0.10232262700729922 ], [ -0.603197415445685 ], [ 0.3166003226671257 ], [ 0.16889075520339447 ], [ 0.7107685147655531 ], ... ],
[ [ 0.026261762750010798 ], [ -0.07173872411426974 ], [ 0.16371172241876208 ], [ -0.4809346491086235 ], [ -0.3240570298733041 ], [ 0.4498961439567677 ], [ 0.0642515465433171 ], [ 0.47716476054767787 ], ... ],
[ [ 0.42618934551004317 ], [ -0.20346539519941853 ], [ 0.47215138546008917 ], [ 0.4845858186838219 ], [ 0.7821671035712003 ], [ -0.0930944498426789 ], [ -0.8354434841886671 ], [ 0.5974819826582436 ], ... ],
[ [ 0.39133074939045676 ], [ 0.0024268454526197303 ], [ -0.6387987711561369 ], [ -0.7329634448161209 ], [ -0.4921732514031463 ], [ -0.8316867780571489 ], [ -0.7742699774302626 ], [ 0.6003007203702226 ], ... ],
[ [ -0.4121764343980039 ], [ 0.6056256804974232 ], [ 0.8093488654926768 ], [ -0.9763929067366792 ], [ -0.5634762991158031 ], [ 0.6897469031972678 ], [ 0.6486735019533323 ], [ 0.350988490591406 ], ... ],
...
]
[
[ [ -0.9813873401619488 ], [ -0.8750065119647523 ], [ 0.04658106187807576 ], [ -0.5684617159994341 ], [ 0.6621772422495855 ], [ 0.8788228005439223 ], [ 0.34069842180170395 ], [ 0.022822296006693277 ], ... ],
[ [ -0.15655432640380473 ], [ -0.9251803483310412 ], [ 0.04072241245336339 ], [ 0.14148274908600378 ], [ 0.7031872841388458 ], [ -0.05142489879310874 ], [ -0.8663546752682627 ], [ -0.35015784701882113 ], ... ],
[ [ -0.3749720686626128 ], [ 0.4996507087205455 ], [ 0.6474470531886107 ], [ 0.23991525683189052 ], [ -0.5202768858110107 ], [ 0.41054475717206107 ], [ -0.6496720340109092 ], [ 0.5901423557212195 ], ... ],
[ [ 0.7711612464931212 ], [ -0.24750045214332705 ], [ 0.9321247697951804 ], [ 0.29566637466921386 ], [ -0.9990842533636863 ], [ -0.03177106088858128 ], [ -0.08744892661193382 ], [ 0.1491548045847806 ], ... ],
[ [ 0.790672759494969 ], [ -0.08484112863879956 ], [ 0.5692288780528505 ], [ 0.881486217644269 ], [ -0.13360098133557896 ], [ -0.777603806428026 ], [ -0.947991490253751 ], [ -0.4700056862694775 ], ... ],
[ [ -0.016777086252472984 ], [ 0.29994055903429007 ], [ 0.922405658139003 ], [ 0.26191394618367436 ], [ 0.3518953128166542 ], [ 0.14939230859739938 ], [ -0.914192047060048 ], [ -0.0031329174594538767 ], ... ],
[ [ -0.6331960124415115 ], [ 0.2330570735342623 ], [ 0.011348717961448207 ], [ -0.0443700020574862 ], [ -0.43091705011122583 ], [ -0.5808219372676231 ], [ 0.25591013686773834 ], [ -0.2664325547218358 ], ... ],
[ [ -0.9302660275500758 ], [ 0.5270660216418084 ], [ 0.019909748569099106 ], [ 0.0948405996122903 ], [ -0.020488562484626494 ], [ -0.9145435843167804 ], [ 0.48236286040394494 ], [ -0.2127685193485802 ], ... ],
...
]
[
[ [ -0.5698852409754616 ], [ -0.04127493278074956 ], [ -0.46498732202496806 ], [ 0.9461844676463909 ], [ -0.5296319992388068 ], [ 0.6578066299988743 ], [ 0.5469778453983305 ], [ -0.027565737262877255 ], ... ],
[ [ -0.08883679209212292 ], [ 0.16979419164675758 ], [ 0.7686971011593191 ], [ 0.7074792150226594 ], [ -0.7929104193487 ], [ -0.029910826019827308 ], [ 0.5111743520087737 ], [ -0.07186782980671835 ], ... ],
[ [ -0.9024029576270141 ], [ 0.47680682903878324 ], [ -0.2787647141689251 ], [ 0.0015037217672515535 ], [ -0.24933477569474638 ], [ 0.659230235837194 ], [ -0.10457169238651787 ], [ 0.07567072227086058 ], ... ],
[ [ -0.7075410220512053 ], [ -0.6567781583150594 ], [ -0.7623451367166127 ], [ 0.4210167084898002 ], [ 0.3251451607513016 ], [ 0.4856618799118615 ], [ 0.9154959611217055 ], [ 0.7621318030283917 ], ... ],
[ [ -0.8386774428156296 ], [ -0.22882289741654227 ], [ 0.35447133969084543 ], [ 0.623621983422612 ], [ -0.9014547674296236 ], [ -0.16774906178248927 ], [ 0.2266942485477479 ], [ 0.9726375592218679 ], ... ],
[ [ 0.7659140328529874 ], [ 0.2555091721596565 ], [ -0.07965992027273439 ], [ 0.5807499381743273 ], [ -0.663742120912094 ], [ 0.6488443906535892 ], [ 0.9628595677494829 ], [ -0.18818887158639952 ], ... ],
[ [ -0.13472270182019197 ], [ -0.4962778721465073 ], [ 0.3240733593008205 ], [ 0.11356402700832136 ], [ -0.5749765921033849 ], [ 0.907445035651778 ], [ -0.26314772999635627 ], [ -0.41937103118376595 ], ... ],
[ [ 0.6132133302294192 ], [ -0.10216725429692519 ], [ 0.9329204589512494 ], [ -0.24173017209447023 ], [ 0.7082486123433174 ], [ -0.24975715997669612 ], [ 0.11707845424715368 ], [ 0.6221534587765027 ], ... ],
...
]
First, we train using basic gradient descent method apply weak line search conditions.
TrainingTester.java:480 executed in 30.08 seconds (0.206 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 3026202949087
BACKPROP_AGG_SIZE = 3
THREADS = 64
SINGLE_THREADED = false
Initialized CoreSettings = {
"backpropAggregationSize" : 3,
"jvmThreads" : 64,
"singleThreaded" : false
}
Reset training subject: 3026286353929
Constructing line search parameters: GD
th(0)=0.17702033001308956;dx=-2.409388570500114E-5
New Minimum: 0.17702033001308956 > 0.17696843025630724
WOLFE (weak): th(2.154434690031884)=0.17696843025630724; dx=-2.4085580951293525E-5 evalInputDelta=5.189975678232539E-5
New Minimum: 0.17696843025630724 > 0.17691654838933274
WOLFE (weak): th(4.308869380063768)=0.17691654838933274; dx=-2.4077278278707823E-5 evalInputDelta=1.037816237568212E-4
New Minimum: 0.17691654838933274 > 0.17670919972985316
WOLFE (weak): th(12.926608140191302)=0.17670919972985316; dx=-2.4044088393826366E-5 evalInputDelta=3.1113028323639935E-4
New Minimum: 0.17670919972985316 > 0.17577966436954678
WOLFE (weak): th(51.70643256076521)=0.17577966436954678; dx=-2.38951454229837E-5 evalInputDelta=0.0012406656435427765
New Minimum: 0.17577966436954678 > 0.1709188384217794
WOLFE (weak): th(258.53216280382605)=0.1709188384217794; dx=-2.311209362059013E-5 evalInputDelta=0.006101491591310154
New Minimum: 0.1709188384217794 > 0.14401225215204555
END: th(1551.1929768229563)=0.14401225215204555; dx=-1.8635306365038082E-5 evalInputDelta=0.03300807786104401
Fitness changed from 0.17702033001308956 to 0.14401225215204555
Iteration 1 complete. Error: 0.14401225215204555 Total: 0.3085; Orientation: 0.0073; Line Search: 0.1746
th(0)=0.14401225215204555;dx=-1.4645835095002616E-5
New Minimum: 0.14401225215204555 > 0.10379815933010347
END: th(3341.943960201201)=0.10379815933010347; dx=-9.666567502951021E-6 evalInputDelta=0.04021409282194208
Fitness changed from 0.14401225215204555 to 0.10379815933010347
Iteration 2 complete. Error: 0.10379815933010347 Total: 0.0502; Orientation: 0.0036; Line Search: 0.0355
th(0)=0.10379815933010347;dx=-6.843787587101358E-6
New Minimum: 0.10379815933010347 > 0.06495895187618883
END: th(7200.000000000001)=0.06495895187618883; dx=-4.00088726558199E-6 evalInputDelta=0.03883920745391464
Fitness changed from 0.10379815933010347 to 0.06495895187618883
Iteration 3 complete. Error: 0.06495895187618883 Total: 0.0485; Orientation: 0.0048; Line Search: 0.0280
th(0)=0.06495895187618883;dx=-2.9489899604965604E-6
New Minimum: 0.06495895187618883 > 0.03349295369454822
END: th(15511.929768229566)=0.03349295369454822; dx=-6.335927960385645E-7 evalInputDelta=0.03146599818164061
Fitness changed from 0.06495895187618883 to 0.03349295369454822
Iteration 4 complete. Error: 0.03349295369454822 Total: 0.2632; Orientation: 0.0043; Line Search: 0.2496
th(0)=0.03349295369454822;dx=-1.6894691016076768E-6
Armijo: th(33419.43960201202)=0.051171982777970845; dx=3.5607011123235304E-6 evalInputDelta=-0.017679029083422622
New Minimum: 0.03349295369454822 > 0.021283944776942867
WOLF (strong): th(16709.71980100601)=0.021283944776942867; dx=3.256985294753713E-7 evalInputDelta=0.012209008917605357
END: th(5569.906600335336)=0.025785854206508047; dx=-1.0749355109621624E-6 evalInputDelta=0.007707099488040176
Fitness changed from 0.03349295369454822 to 0.021283944776942867
Iteration 5 complete. Error: 0.021283944776942867 Total: 0.4619; Orientation: 0.0510; Line Search: 0.3662
th(0)=0.021283944776942867;dx=-1.5151763805085948E-6
New Minimum: 0.021283944776942867 > 0.012063940932903715
WOLF (strong): th(12000.000000000004)=0.012063940932903715; dx=9.524458399528981E-8 evalInputDelta=0.009220003844039152
END: th(6000.000000000002)=0.014274154479084308; dx=-7.975175313765728E-7 evalInputDelta=0.007009790297858559
Fitness changed from 0.021283944776942867 to 0.012063940932903715
Iteration 6 complete. Error: 0.012063940932903715 Total: 0.2404; Orientation: 0.0146; Line Search: 0.2172
th(0)=0.012063940932903715;dx=-6.290119206216911E-7
New Minimum: 0.012063940932903715 > 0.007637931407993908
WOLF (strong): th(12926.608140191307)=0.007637931407993908; dx=7.685039123010633E-9 evalInputDelta=0.0044260095249098064
END: th(6463.3040700956535)=0.008827639454700359; dx=-3.582611893324567E-7 evalInputDelta=0.003236301478203356
Fitness changed from 0.012063940932903715 to 0.007637931407993908
Iteration 7 complete. Error: 0.007637931407993908 Total: 0.4115; Orientation: 0.0034; Line Search: 0.3117
th(0)=0.007637931407993908;dx=-3.891245361141623E-7
New Minimum: 0.007637931407993908 > 0.0052317377664687255
WOLF (strong): th(13924.766500838343)=0.0052317377664687255; dx=7.000102846392809E-8 evalInputDelta=0.002406193641525183
END: th(6962.383250419171)=0.0056389903890803885; dx=-1.794184756992407E-7 evalInputDelta=0.00199894101891352
Fitness changed from 0.007637931407993908 to 0.0052317377664687255
Iteration 8 complete. Error: 0.0052317377664687255 Total: 0.2486; Orientation: 0.0031; Line Search: 0.2372
th(0)=0.0052317377664687255;dx=-3.3197578528483674E-7
New Minimum: 0.0052317377664687255 > 0.0039303686469284015
WOLF (strong): th(15000.000000000007)=0.0039303686469284015; dx=1.7297974644657812E-7 evalInputDelta=0.001301369119540324
New Minimum: 0.0039303686469284015 > 0.003637873863886123
END: th(7500.000000000004)=0.003637873863886123; dx=-9.038790224446716E-8 evalInputDelta=0.0015938639025826025
Fitness changed from 0.0052317377664687255 to 0.003637873863886123
Iteration 9 complete. Error: 0.003637873863886123 Total: 0.3473; Orientation: 0.0033; Line Search: 0.3351
th(0)=0.003637873863886123;dx=-1.1219829690585705E-7
New Minimum: 0.003637873863886123 > 0.00234631052209241
END: th(16158.260175239137)=0.00234631052209241; dx=-2.990413817035653E-8 evalInputDelta=0.001291563341793713
Fitness changed from 0.003637873863886123 to 0.00234631052209241
Iteration 10 complete. Error: 0.00234631052209241 Total: 0.4911; Orientation: 0.0048; Line Search: 0.4775
th(0)=0.00234631052209241;dx=-8.669892917423582E-8
Armijo: th(34811.91625209586)=0.0030355700414817317; dx=1.490190514008148E-7 evalInputDelta=-6.892595193893217E-4
New Minimum: 0.00234631052209241 > 0.0016955460936196784
WOLF (strong): th(17405.95812604793)=0.0016955460936196784; dx=1.4119261823496474E-8 evalInputDelta=6.507644284727315E-4
END: th(5801.986042015978)=0.0019373201109697767; dx=-5.42982066385154E-8 evalInputDelta=4.0899041112263325E-4
Fitness changed from 0.00234631052209241 to 0.0016955460936196784
Iteration 11 complete. Error: 0.0016955460936196784 Total: 0.4265; Orientation: 0.0042; Line Search: 0.4138
th(0)=0.0016955460936196784;dx=-9.579597397540275E-8
New Minimum: 0.0016955460936196784 > 0.001183076708064727
WOLF (strong): th(12500.00000000001)=0.001183076708064727; dx=2.2203321482686725E-8 evalInputDelta=5.124693855549515E-4
END: th(6250.000000000005)=0.001255549481602434; dx=-4.309816314341578E-8 evalInputDelta=4.399966120172444E-4
Fitness changed from 0.0016955460936196784 to 0.001183076708064727
Iteration 12 complete. Error: 0.001183076708064727 Total: 0.1826; Orientation: 0.0033; Line Search: 0.0910
th(0)=0.001183076708064727;dx=-5.925869394521184E-8
New Minimum: 0.001183076708064727 > 9.46029757067168E-4
WOLF (strong): th(13465.216812699284)=9.46029757067168E-4; dx=2.269157643177086E-8 evalInputDelta=2.37046950997559E-4
New Minimum: 9.46029757067168E-4 > 9.268622519450648E-4
END: th(6732.608406349642)=9.268622519450648E-4; dx=-1.7264808160652975E-8 evalInputDelta=2.5621445611966216E-4
Fitness changed from 0.001183076708064727 to 9.268622519450648E-4
Iteration 13 complete. Error: 9.268622519450648E-4 Total: 0.2536; Orientation: 0.0036; Line Search: 0.2372
th(0)=9.268622519450648E-4;dx=-1.932459379606429E-8
New Minimum: 9.268622519450648E-4 > 7.00249608655017E-4
END: th(14504.965105039946)=7.00249608655017E-4; dx=-1.0391543170354469E-8 evalInputDelta=2.266126432900478E-4
Fitness changed from 9.268622519450648E-4 to 7.00249608655017E-4
Iteration 14 complete. Error: 7.00249608655017E-4 Total: 0.0387; Orientation: 0.0030; Line Search: 0.0285
th(0)=7.00249608655017E-4;dx=-1.2426459445943736E-8
New Minimum: 7.00249608655017E-4 > 5.246123834590779E-4
WOLF (strong): th(31250.00000000003)=5.246123834590779E-4; dx=3.115395856025646E-9 evalInputDelta=1.7563722519593913E-4
END: th(15625.000000000015)=5.5251508956520
...skipping 60038 bytes...
WOLFE (weak): th(25276.32139852468)=1.6774113870853027E-7; dx=-1.307072969119486E-13 evalInputDelta=3.395838914801149E-9
New Minimum: 1.6774113870853027E-7 > 1.6150386715803277E-7
END: th(75828.96419557404)=1.6150386715803277E-7; dx=-1.1602701049338096E-13 evalInputDelta=9.633110465298643E-9
Fitness changed from 1.7113697762333142E-7 to 1.6150386715803277E-7
Iteration 114 complete. Error: 1.6150386715803277E-7 Total: 0.3643; Orientation: 0.0034; Line Search: 0.3538
Low gradient: 5.360912419132501E-7
th(0)=1.6150386715803277E-7;dx=-2.873938196560908E-13
Armijo: th(163368.55097213035)=4.648815589809334E-7; dx=4.031548819590707E-12 evalInputDelta=-3.0337769182290066E-7
Armijo: th(81684.27548606518)=2.249966106937678E-7; dx=1.849482300588576E-12 evalInputDelta=-6.349274353573502E-8
Armijo: th(27228.091828688393)=1.632965153476586E-7; dx=4.199010546194459E-13 evalInputDelta=-1.7926481896258369E-9
New Minimum: 1.6150386715803277E-7 > 1.6014762555494714E-7
END: th(6807.022957172098)=1.6014762555494714E-7; dx=-1.1103734841717967E-13 evalInputDelta=1.356241603085635E-9
Fitness changed from 1.6150386715803277E-7 to 1.6014762555494714E-7
Iteration 115 complete. Error: 1.6014762555494714E-7 Total: 0.3688; Orientation: 0.1136; Line Search: 0.1989
Low gradient: 3.549071022963482E-7
th(0)=1.6014762555494714E-7;dx=-1.2595905126039054E-13
New Minimum: 1.6014762555494714E-7 > 1.5832796146439977E-7
WOLFE (weak): th(14665.286394774987)=1.5832796146439977E-7; dx=-1.221983543928398E-13 evalInputDelta=1.81966409054737E-9
New Minimum: 1.5832796146439977E-7 > 1.5656353578210952E-7
WOLFE (weak): th(29330.572789549973)=1.5656353578210952E-7; dx=-1.1842580188674489E-13 evalInputDelta=3.5840897728376185E-9
New Minimum: 1.5656353578210952E-7 > 1.5006176091733977E-7
END: th(87991.71836864992)=1.5006176091733977E-7; dx=-1.0321341031043074E-13 evalInputDelta=1.0085864637607371E-8
Fitness changed from 1.6014762555494714E-7 to 1.5006176091733977E-7
Iteration 116 complete. Error: 1.5006176091733977E-7 Total: 0.2693; Orientation: 0.0032; Line Search: 0.1387
Low gradient: 5.689162389784028E-7
th(0)=1.5006176091733977E-7;dx=-3.2366568697333117E-13
Armijo: th(189572.4104889351)=7.009188182709554E-7; dx=6.195057589309462E-12 evalInputDelta=-5.508570573536156E-7
Armijo: th(94786.20524446755)=2.7102292478902577E-7; dx=2.8908326145889586E-12 evalInputDelta=-1.20961163871686E-7
Armijo: th(31595.40174815585)=1.5658009667594473E-7; dx=7.379250066886227E-13 evalInputDelta=-6.518335758604961E-9
New Minimum: 1.5006176091733977E-7 > 1.4854928010414318E-7
END: th(7898.850437038963)=1.4854928010414318E-7; dx=-5.919381830203718E-14 evalInputDelta=1.5124808131965897E-9
Fitness changed from 1.5006176091733977E-7 to 1.4854928010414318E-7
Iteration 117 complete. Error: 1.4854928010414318E-7 Total: 0.2157; Orientation: 0.0034; Line Search: 0.2048
Low gradient: 3.575553408743615E-7
th(0)=1.4854928010414318E-7;dx=-1.2784582178778083E-13
New Minimum: 1.4854928010414318E-7 > 1.4671287578195424E-7
END: th(17017.557392930248)=1.4671287578195424E-7; dx=-8.798450654175835E-14 evalInputDelta=1.8364043221889401E-9
Fitness changed from 1.4854928010414318E-7 to 1.4671287578195424E-7
Iteration 118 complete. Error: 1.4671287578195424E-7 Total: 0.0702; Orientation: 0.0031; Line Search: 0.0364
Low gradient: 3.9249386404539676E-7
th(0)=1.4671287578195424E-7;dx=-1.540514333132864E-13
New Minimum: 1.4671287578195424E-7 > 1.4565271247080789E-7
WOLF (strong): th(36663.215986937474)=1.4565271247080789E-7; dx=9.643296926082342E-14 evalInputDelta=1.0601633111463497E-9
New Minimum: 1.4565271247080789E-7 > 1.4503484912471378E-7
END: th(18331.607993468737)=1.4503484912471378E-7; dx=-2.8969783201781806E-14 evalInputDelta=1.678026657240457E-9
Fitness changed from 1.4671287578195424E-7 to 1.4503484912471378E-7
Iteration 119 complete. Error: 1.4503484912471378E-7 Total: 0.0794; Orientation: 0.0047; Line Search: 0.0647
Low gradient: 5.173571272507361E-7
th(0)=1.4503484912471378E-7;dx=-2.676583971171343E-13
Armijo: th(39494.25218519482)=1.541511586025905E-7; dx=7.276496849127904E-13 evalInputDelta=-9.116309477876715E-9
New Minimum: 1.4503484912471378E-7 > 1.4467938965113885E-7
WOLF (strong): th(19747.12609259741)=1.4467938965113885E-7; dx=2.312415283416892E-13 evalInputDelta=3.554594735749326E-10
New Minimum: 1.4467938965113885E-7 > 1.4382140993066774E-7
END: th(6582.375364199136)=1.4382140993066774E-7; dx=-1.0108123340427986E-13 evalInputDelta=1.21343919404604E-9
Fitness changed from 1.4503484912471378E-7 to 1.4382140993066774E-7
Iteration 120 complete. Error: 1.4382140993066774E-7 Total: 0.2461; Orientation: 0.0099; Line Search: 0.2286
Low gradient: 3.3094133495216164E-7
th(0)=1.4382140993066774E-7;dx=-1.0952216717991886E-13
New Minimum: 1.4382140993066774E-7 > 1.4228060684835615E-7
WOLFE (weak): th(14181.297827441875)=1.4228060684835615E-7; dx=-1.077765686058028E-13 evalInputDelta=1.5408030823115918E-9
New Minimum: 1.4228060684835615E-7 > 1.4076464319736482E-7
WOLFE (weak): th(28362.59565488375)=1.4076464319736482E-7; dx=-1.0601901700702387E-13 evalInputDelta=3.0567667333029157E-9
New Minimum: 1.4076464319736482E-7 > 1.34952626088957E-7
WOLFE (weak): th(85087.78696465126)=1.34952626088957E-7; dx=-9.886629083353862E-14 evalInputDelta=8.868783841710727E-9
New Minimum: 1.34952626088957E-7 > 1.1406557593712678E-7
END: th(340351.147858605)=1.1406557593712678E-7; dx=-6.402622598253313E-14 evalInputDelta=2.9755833993540962E-8
Fitness changed from 1.4382140993066774E-7 to 1.1406557593712678E-7
Iteration 121 complete. Error: 1.1406557593712678E-7 Total: 0.3162; Orientation: 0.0035; Line Search: 0.3054
Low gradient: 1.1559110032974702E-6
th(0)=1.1406557593712678E-7;dx=-1.3361302475441642E-12
Armijo: th(733264.3197387495)=4.439098257807562E-5; dx=1.1011327049158243E-10 evalInputDelta=-4.427691700213849E-5
Armijo: th(366632.15986937477)=1.2069035432137985E-5; dx=6.338066003773832E-11 evalInputDelta=-1.1954969856200858E-5
Armijo: th(122210.71995645826)=1.42120875354325E-6; dx=2.2362650011442647E-11 evalInputDelta=-1.3071431776061232E-6
Armijo: th(30552.679989114564)=1.6725060642866516E-7; dx=4.794539930525566E-12 evalInputDelta=-5.318503049153838E-8
New Minimum: 1.1406557593712678E-7 > 1.0968404282117177E-7
END: th(6110.535997822913)=1.0968404282117177E-7; dx=-9.888901165727974E-14 evalInputDelta=4.381533115955005E-9
Fitness changed from 1.1406557593712678E-7 to 1.0968404282117177E-7
Iteration 122 complete. Error: 1.0968404282117177E-7 Total: 0.6430; Orientation: 0.0035; Line Search: 0.4607
Low gradient: 2.6949260684715004E-7
th(0)=1.0968404282117177E-7;dx=-7.262626514527257E-14
New Minimum: 1.0968404282117177E-7 > 1.0873912130564623E-7
WOLFE (weak): th(13164.750728398274)=1.0873912130564623E-7; dx=-7.092641102276196E-14 evalInputDelta=9.449215155255375E-10
New Minimum: 1.0873912130564623E-7 > 1.0781660150501625E-7
WOLFE (weak): th(26329.501456796548)=1.0781660150501625E-7; dx=-6.922297319540536E-14 evalInputDelta=1.8674413161555218E-9
New Minimum: 1.0781660150501625E-7 > 1.0435149208080629E-7
END: th(78988.50437038965)=1.0435149208080629E-7; dx=-6.237283441403266E-14 evalInputDelta=5.332550740365487E-9
Fitness changed from 1.0968404282117177E-7 to 1.0435149208080629E-7
Iteration 123 complete. Error: 1.0435149208080629E-7 Total: 0.2280; Orientation: 0.0034; Line Search: 0.1187
Low gradient: 3.76641476415098E-7
th(0)=1.0435149208080629E-7;dx=-1.418588017561448E-13
Armijo: th(170175.57392930254)=2.5772889202401817E-7; dx=1.954417992007855E-12 evalInputDelta=-1.533773999432119E-7
Armijo: th(85087.78696465127)=1.364486045491919E-7; dx=8.98793941237904E-13 evalInputDelta=-3.2097112468385604E-8
Armijo: th(28362.595654883757)=1.0521984791601957E-7; dx=2.0336720470663115E-13 evalInputDelta=-8.683558352132863E-10
New Minimum: 1.0435149208080629E-7 > 1.0365099437470608E-7
END: th(7090.648913720939)=1.0365099437470608E-7; dx=-5.570749019763892E-14 evalInputDelta=7.004977061002067E-10
Fitness changed from 1.0435149208080629E-7 to 1.0365099437470608E-7
Iteration 124 complete. Error: 1.0365099437470608E-7 Total: 0.5549; Orientation: 0.0042; Line Search: 0.4491
Final threshold in iteration 124: 1.0365099437470608E-7 (> 0.0) after 30.070s (< 30.000s)
Returns
1.0365099437470608E-7
First, we use a conjugate gradient descent method, which converges the fastest for purely linear functions.
TrainingTester.java:452 executed in 30.30 seconds (0.153 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new QuadraticSearch());
iterativeTrainer.setOrientation(new GradientDescent());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 3056281312548
Reset training subject: 3056304491525
Constructing line search parameters: GD
F(0.0) = LineSearchPoint{point=PointSample{avg=0.17702033001308956}, derivative=-2.409388570500114E-5}
New Minimum: 0.17702033001308956 > 0.1770203300130871
F(1.0E-10) = LineSearchPoint{point=PointSample{avg=0.1770203300130871}, derivative=-2.4093885705000757E-5}, evalInputDelta = -2.4702462297909733E-15
New Minimum: 0.1770203300130871 > 0.1770203300130726
F(7.000000000000001E-10) = LineSearchPoint{point=PointSample{avg=0.1770203300130726}, derivative=-2.409388570499844E-5}, evalInputDelta = -1.6958656701149266E-14
New Minimum: 0.1770203300130726 > 0.17702033001297132
F(4.900000000000001E-9) = LineSearchPoint{point=PointSample{avg=0.17702033001297132}, derivative=-2.409388570498225E-5}, evalInputDelta = -1.1823875212257917E-13
New Minimum: 0.17702033001297132 > 0.1770203300122628
F(3.430000000000001E-8) = LineSearchPoint{point=PointSample{avg=0.1770203300122628}, derivative=-2.4093885704868905E-5}, evalInputDelta = -8.267553308627384E-13
New Minimum: 0.1770203300122628 > 0.17702033000730402
F(2.4010000000000004E-7) = LineSearchPoint{point=PointSample{avg=0.17702033000730402}, derivative=-2.4093885704075506E-5}, evalInputDelta = -5.7855387147753845E-12
New Minimum: 0.17702033000730402 > 0.17702032997259498
F(1.6807000000000003E-6) = LineSearchPoint{point=PointSample{avg=0.17702032997259498}, derivative=-2.4093885698521694E-5}, evalInputDelta = -4.049457991150973E-11
New Minimum: 0.17702032997259498 > 0.1770203297296274
F(1.1764900000000001E-5) = LineSearchPoint{point=PointSample{avg=0.1770203297296274}, derivative=-2.4093885659645002E-5}, evalInputDelta = -2.834621704028706E-10
New Minimum: 0.1770203297296274 > 0.17702032802885453
F(8.235430000000001E-5) = LineSearchPoint{point=PointSample{avg=0.17702032802885453}, derivative=-2.4093885387508163E-5}, evalInputDelta = -1.9842350262866404E-9
New Minimum: 0.17702032802885453 > 0.1770203161234442
F(5.764801000000001E-4) = LineSearchPoint{point=PointSample{avg=0.1770203161234442}, derivative=-2.4093883482550384E-5}, evalInputDelta = -1.3889645350539936E-8
New Minimum: 0.1770203161234442 > 0.17702023278560125
F(0.004035360700000001) = LineSearchPoint{point=PointSample{avg=0.17702023278560125}, derivative=-2.409387014784898E-5}, evalInputDelta = -9.722748831042516E-8
New Minimum: 0.17702023278560125 > 0.1770196494219912
F(0.028247524900000005) = LineSearchPoint{point=PointSample{avg=0.1770196494219912}, derivative=-2.4093776805089357E-5}, evalInputDelta = -6.805910983676E-7
New Minimum: 0.1770196494219912 > 0.17701556593999984
F(0.19773267430000002) = LineSearchPoint{point=PointSample{avg=0.17701556593999984}, derivative=-2.4093123413132616E-5}, evalInputDelta = -4.764073089719156E-6
New Minimum: 0.17701556593999984 > 0.17698698466663565
F(1.3841287201) = LineSearchPoint{point=PointSample{avg=0.17698698466663565}, derivative=-2.4088550030094862E-5}, evalInputDelta = -3.3345346453911295E-5
New Minimum: 0.17698698466663565 > 0.17678706762429877
F(9.688901040700001) = LineSearchPoint{point=PointSample{avg=0.17678706762429877}, derivative=-2.4056554017489167E-5}, evalInputDelta = -2.332623887907892E-4
New Minimum: 0.17678706762429877 > 0.17539507052174502
F(67.8223072849) = LineSearchPoint{point=PointSample{avg=0.17539507052174502}, derivative=-2.383344644032854E-5}, evalInputDelta = -0.0016252594913445384
New Minimum: 0.17539507052174502 > 0.1660081423146269
F(474.7561509943) = LineSearchPoint{point=PointSample{avg=0.1660081423146269}, derivative=-2.2313624598419323E-5}, evalInputDelta = -0.011012187698462655
New Minimum: 0.1660081423146269 > 0.11564146862885431
F(3323.2930569601003) = LineSearchPoint{point=PointSample{avg=0.11564146862885431}, derivative=-1.3582063696621363E-5}, evalInputDelta = -0.06137886138423525
New Minimum: 0.11564146862885431 > 0.07009018569725554
F(23263.0513987207) = LineSearchPoint{point=PointSample{avg=0.07009018569725554}, derivative=4.657250324450216E-6}, evalInputDelta = -0.10693014431583402
0.07009018569725554 <= 0.17702033001308956
New Minimum: 0.07009018569725554 > 0.059422515691472964
F(19494.78799641849) = LineSearchPoint{point=PointSample{avg=0.059422515691472964}, derivative=1.399929259202534E-6}, evalInputDelta = -0.11759781432161659
Right bracket at 19494.78799641849
New Minimum: 0.059422515691472964 > 0.05823687339663726
F(18424.28033970031) = LineSearchPoint{point=PointSample{avg=0.05823687339663726}, derivative=8.337753520967002E-7}, evalInputDelta = -0.1187834566164523
Right bracket at 18424.28033970031
New Minimum: 0.05823687339663726 > 0.057811079193183554
F(17808.028747054886) = LineSearchPoint{point=PointSample{avg=0.057811079193183554}, derivative=5.527365774095389E-7}, evalInputDelta = -0.119209250819906
Right bracket at 17808.028747054886
New Minimum: 0.057811079193183554 > 0.057624325763226125
F(17408.657638621808) = LineSearchPoint{point=PointSample{avg=0.057624325763226125}, derivative=3.8405590594483617E-7}, evalInputDelta = -0.11939600424986344
Right bracket at 17408.657638621808
New Minimum: 0.057624325763226125 > 0.05753458631428175
F(17135.517932393625) = LineSearchPoint{point=PointSample{avg=0.05753458631428175}, derivative=2.7364664318772195E-7}, evalInputDelta = -0.11948574369880781
Right bracket at 17135.517932393625
New Minimum: 0.05753458631428175 > 0.057489240498752106
F(16943.086589963044) = LineSearchPoint{point=PointSample{avg=0.057489240498752106}, derivative=1.9790670336740198E-7}, evalInputDelta = -0.11953108951433745
Right bracket at 16943.086589963044
Converged to right
Fitness changed from 0.17702033001308956 to 0.057489240498752106
Iteration 1 complete. Error: 0.057489240498752106 Total: 2.0058; Orientation: 0.0032; Line Search: 1.8853
F(0.0) = LineSearchPoint{point=PointSample{avg=0.057489240498752106}, derivative=-3.002999067242444E-6}
New Minimum: 0.057489240498752106 > 0.037188721018577335
F(16943.086589963044) = LineSearchPoint{point=PointSample{avg=0.037188721018577335}, derivative=6.535941748020198E-7}, evalInputDelta = -0.02030051948017477
0.037188721018577335 <= 0.057489240498752106
New Minimum: 0.037188721018577335 > 0.03628013294657341
F(13914.611185306207) = LineSearchPoint{point=PointSample{avg=0.03628013294657341}, derivative=-4.523005143180302E-8}, evalInputDelta = -0.021209107552178696
Left bracket at 13914.611185306207
New Minimum: 0.03628013294657341 > 0.03627555662655295
F(14110.623420100634) = LineSearchPoint{point=PointSample{avg=0.03627555662655295}, derivative=-1.435093259782927E-9}, evalInputDelta = -0.021213683872199157
Left bracket at 14110.623420100634
Converged to left
Fitness changed from 0.057489240498752106 to 0.03627555662655295
Iteration 2 complete. Error: 0.03627555662655295 Total: 0.2378; Orientation: 0.0028; Line Search: 0.2285
F(0.0) = LineSearchPoint{point=PointSample{avg=0.03627555662655295}, derivative=-2.008374529685284E-6}
New Minimum: 0.03627555662655295 > 0.02064961022603027
F(14110.623420100634) = LineSearchPoint{point=PointSample{avg=0.02064961022603027}, derivative=1.6007248325999717E-7}, evalInputDelta = -0.01562594640052268
0.02064961022603027 <= 0.03627555662655295
New Minimum: 0.02064961022603027 > 0.02060914719178408
F(13068.992004752243) = LineSearchPoint{point=PointSample{avg=0.02060914719178408}, derivative=-7.996806149086849E-8}, evalInputDelta = -0.01566640943476887
Left bracket at 13068.992004752243
New Minimum: 0.02060914719178408 > 0.020594947586096167
F(13416.005236037206) = LineSearchPoint{point=PointSample{avg=0.020594947586096167}, derivative=-1.6055974285100606E-9}, evalInputDelta = -0.015680609040456782
Left bracket at 13416.005236037206
Converged to left
Fitness changed from 0.03627555662655295 to 0.020594947586096167
Iteration 3 complete. Error: 0.020594947586096167 Total: 0.4835; Orientation: 0.0030; Line Search: 0.4736
F(0.0) = LineSearchPoint{point=PointSample{avg=0.020594947586096167}, derivative=-1.11030220783918E-6}
New Minimum: 0.020594947586096167 > 0.013309248233512585
F(13416.005236037206) = LineSearchPoint{point=PointSample{avg=0.013309248233512585}, derivative=9.124715364159494E-8}, evalInputDelta = -0.007285699352583582
0.0133092
...skipping 65319 bytes...
317260582474E-13}, evalInputDelta = -4.740829114011817E-7
9.552672685385987E-6 <= 1.0026755596787169E-5
New Minimum: 9.552672685385987E-6 > 9.55262423867057E-6
F(12341.036292659812) = LineSearchPoint{point=PointSample{avg=9.55262423867057E-6}, derivative=-1.8640073183720646E-15}, evalInputDelta = -4.741313581165982E-7
Left bracket at 12341.036292659812
Converged to left
Fitness changed from 1.0026755596787169E-5 to 9.55262423867057E-6
Iteration 63 complete. Error: 9.55262423867057E-6 Total: 0.3342; Orientation: 0.0033; Line Search: 0.3242
Low gradient: 8.514687641399556E-6
F(0.0) = LineSearchPoint{point=PointSample{avg=9.55262423867057E-6}, derivative=-7.249990563060233E-11}
New Minimum: 9.55262423867057E-6 > 9.100013847871327E-6
F(12341.036292659812) = LineSearchPoint{point=PointSample{avg=9.100013847871327E-6}, derivative=-8.225082155676034E-13}, evalInputDelta = -4.526103907992437E-7
F(86387.25404861868) = LineSearchPoint{point=PointSample{avg=2.5079665198926522E-5}, derivative=4.340185115655459E-10}, evalInputDelta = 1.552704096025595E-5
F(6645.173388355282) = LineSearchPoint{point=PointSample{avg=9.198991108767165E-6}, derivative=-3.3925343174836855E-11}, evalInputDelta = -3.536331299034052E-7
F(46516.21371848698) = LineSearchPoint{point=PointSample{avg=1.2476505157840279E-5}, derivative=1.987024363759393E-10}, evalInputDelta = 2.923880919169708E-6
F(3578.17028603746) = LineSearchPoint{point=PointSample{avg=9.330353739699009E-6}, derivative=-5.173483157594644E-11}, evalInputDelta = -2.2227049897156193E-7
F(25047.192002262218) = LineSearchPoint{point=PointSample{avg=9.559397205884799E-6}, derivative=7.316592761470365E-11}, evalInputDelta = 6.772967214228572E-9
F(1926.7070770970936) = LineSearchPoint{point=PointSample{avg=9.42370738891734E-6}, derivative=-6.132037004167869E-11}, evalInputDelta = -1.28916849753231E-7
F(13486.949539679656) = LineSearchPoint{point=PointSample{avg=9.102889551269702E-6}, derivative=5.841831045673544E-12}, evalInputDelta = -4.4973468740086877E-7
9.102889551269702E-6 <= 9.55262423867057E-6
New Minimum: 9.100013847871327E-6 > 9.099955683190402E-6
F(12481.247038369233) = LineSearchPoint{point=PointSample{avg=9.099955683190402E-6}, derivative=-7.162947514230401E-15}, evalInputDelta = -4.526685554801689E-7
Left bracket at 12481.247038369233
Converged to left
Fitness changed from 9.55262423867057E-6 to 9.099955683190402E-6
Iteration 64 complete. Error: 9.099955683190402E-6 Total: 0.7321; Orientation: 0.0030; Line Search: 0.6072
Low gradient: 8.373956513264803E-6
F(0.0) = LineSearchPoint{point=PointSample{avg=9.099955683190402E-6}, derivative=-7.012314768605002E-11}
New Minimum: 9.099955683190402E-6 > 8.666634581572063E-6
F(12481.247038369233) = LineSearchPoint{point=PointSample{avg=8.666634581572063E-6}, derivative=7.494357839026413E-13}, evalInputDelta = -4.333211016183382E-7
8.666634581572063E-6 <= 9.099955683190402E-6
New Minimum: 8.666634581572063E-6 > 8.666585255868047E-6
F(12349.265209849485) = LineSearchPoint{point=PointSample{avg=8.666585255868047E-6}, derivative=-1.966542811714415E-15}, evalInputDelta = -4.3337042732235484E-7
Left bracket at 12349.265209849485
Converged to left
Fitness changed from 9.099955683190402E-6 to 8.666585255868047E-6
Iteration 65 complete. Error: 8.666585255868047E-6 Total: 0.2885; Orientation: 0.0031; Line Search: 0.1829
Low gradient: 8.148561536837038E-6
F(0.0) = LineSearchPoint{point=PointSample{avg=8.666585255868047E-6}, derivative=-6.639905511961997E-11}
New Minimum: 8.666585255868047E-6 > 8.252570095497582E-6
F(12349.265209849485) = LineSearchPoint{point=PointSample{avg=8.252570095497582E-6}, derivative=-6.180381534853344E-13}, evalInputDelta = -4.140151603704648E-7
F(86444.8564689464) = LineSearchPoint{point=PointSample{avg=2.2969111755992254E-5}, derivative=3.9969616172007393E-10}, evalInputDelta = 1.4302526500124207E-5
F(6649.604343765108) = LineSearchPoint{point=PointSample{avg=8.342708410174635E-6}, derivative=-3.10038189113045E-11}, evalInputDelta = -3.238768456934118E-7
F(46547.23040635575) = LineSearchPoint{point=PointSample{avg=1.1361607198130704E-5}, derivative=1.8277566669109594E-10}, evalInputDelta = 2.695021942262657E-6
F(3580.5561851042885) = LineSearchPoint{point=PointSample{avg=8.462943054204902E-6}, derivative=-4.734716597650866E-11}, evalInputDelta = -2.0364220166314477E-7
F(25063.89329573002) = LineSearchPoint{point=PointSample{avg=8.676464238231874E-6}, derivative=6.733749355072636E-11}, evalInputDelta = 9.878982363827643E-9
F(1927.9917919792324) = LineSearchPoint{point=PointSample{avg=8.548455087909045E-6}, derivative=-5.614235983031617E-11}, evalInputDelta = -1.1813016795900185E-7
F(13495.942543854628) = LineSearchPoint{point=PointSample{avg=8.255369276248111E-6}, derivative=5.50060034161348E-12}, evalInputDelta = -4.112159796199358E-7
8.255369276248111E-6 <= 8.666585255868047E-6
New Minimum: 8.252570095497582E-6 > 8.252534305562783E-6
F(12463.451001427851) = LineSearchPoint{point=PointSample{avg=8.252534305562783E-6}, derivative=-8.83068278153244E-15}, evalInputDelta = -4.1405095030526404E-7
Left bracket at 12463.451001427851
Converged to left
Fitness changed from 8.666585255868047E-6 to 8.252534305562783E-6
Iteration 66 complete. Error: 8.252534305562783E-6 Total: 0.5902; Orientation: 0.0033; Line Search: 0.5791
Low gradient: 7.994653130146356E-6
F(0.0) = LineSearchPoint{point=PointSample{avg=8.252534305562783E-6}, derivative=-6.391447867135893E-11}
New Minimum: 8.252534305562783E-6 > 7.858664392459895E-6
F(12463.451001427851) = LineSearchPoint{point=PointSample{avg=7.858664392459895E-6}, derivative=7.743383207625366E-13}, evalInputDelta = -3.938699131028876E-7
7.858664392459895E-6 <= 8.252534305562783E-6
New Minimum: 7.858664392459895E-6 > 7.858606802553671E-6
F(12314.260953316025) = LineSearchPoint{point=PointSample{avg=7.858606802553671E-6}, derivative=-2.2946602392704007E-15}, evalInputDelta = -3.939275030091116E-7
Left bracket at 12314.260953316025
Converged to left
Fitness changed from 8.252534305562783E-6 to 7.858606802553671E-6
Iteration 67 complete. Error: 7.858606802553671E-6 Total: 0.5268; Orientation: 0.0400; Line Search: 0.4794
Low gradient: 7.735146691834987E-6
F(0.0) = LineSearchPoint{point=PointSample{avg=7.858606802553671E-6}, derivative=-5.983249434420574E-11}
New Minimum: 7.858606802553671E-6 > 7.4872493013722075E-6
F(12314.260953316025) = LineSearchPoint{point=PointSample{avg=7.4872493013722075E-6}, derivative=-4.4530393727974376E-13}, evalInputDelta = -3.713575011814635E-7
F(86199.82667321217) = LineSearchPoint{point=PointSample{avg=2.076022282721072E-5}, derivative=3.6156675982866677E-10}, evalInputDelta = 1.290161602465705E-5
F(6630.755897939398) = LineSearchPoint{point=PointSample{avg=7.567768956929686E-6}, derivative=-2.78813652071881E-11}, evalInputDelta = -2.9083784562398524E-7
F(46415.29128557579) = LineSearchPoint{point=PointSample{avg=1.0291970143799513E-5}, derivative=1.6527680268173512E-10}, evalInputDelta = 2.433363341245842E-6
F(3570.4070219673686) = LineSearchPoint{point=PointSample{avg=7.67567542756743E-6}, derivative=-4.2635523992119556E-11}, evalInputDelta = -1.8293137498624034E-7
F(24992.84915377158) = LineSearchPoint{point=PointSample{avg=7.87044954016223E-6}, derivative=6.093619509940633E-11}, evalInputDelta = 1.1842737608559246E-8
F(1922.5268579824294) = LineSearchPoint{point=PointSample{avg=7.752475592572504E-6}, derivative=-5.057472190468702E-11}, evalInputDelta = -1.0613120998116713E-7
F(13457.688005877006) = LineSearchPoint{point=PointSample{avg=7.48989890807352E-6}, derivative=5.080132317468289E-12}, evalInputDelta = -3.687078944801512E-7
7.48989890807352E-6 <= 7.858606802553671E-6
New Minimum: 7.4872493013722075E-6 > 7.487228789601366E-6
F(12404.47479801545) = LineSearchPoint{point=PointSample{avg=7.487228789601366E-6}, derivative=-9.430684437917812E-15}, evalInputDelta = -3.713780129523054E-7
Left bracket at 12404.47479801545
Converged to left
Fitness changed from 7.858606802553671E-6 to 7.487228789601366E-6
Iteration 68 complete. Error: 7.487228789601366E-6 Total: 0.7196; Orientation: 0.0035; Line Search: 0.7089
Final threshold in iteration 68: 7.487228789601366E-6 (> 0.0) after 30.302s (< 30.000s)
Returns
7.487228789601366E-6
Next, we apply the same optimization using L-BFGS, which is nearly ideal for purely second-order or quadratic functions.
TrainingTester.java:509 executed in 30.37 seconds (0.059 gc):
IterativeTrainer iterativeTrainer = new IterativeTrainer(trainable.addRef());
try {
iterativeTrainer.setLineSearchFactory(label -> new ArmijoWolfeSearch());
iterativeTrainer.setOrientation(new LBFGS());
iterativeTrainer.setMonitor(TrainingTester.getMonitor(history));
iterativeTrainer.setTimeout(30, TimeUnit.SECONDS);
iterativeTrainer.setIterationsPerSample(100);
iterativeTrainer.setMaxIterations(250);
iterativeTrainer.setTerminateThreshold(0);
return iterativeTrainer.run();
} finally {
iterativeTrainer.freeRef();
}
Reset training subject: 3086590946951
Reset training subject: 3086598823073
Adding measurement 541fc1a8 to history. Total: 0
LBFGS Accumulation History: 1 points
Constructing line search parameters: GD
Non-optimal measurement 0.17702033001308956 < 0.17702033001308956. Total: 1
th(0)=0.17702033001308956;dx=-2.409388570500114E-5
Adding measurement 423ffdc8 to history. Total: 1
New Minimum: 0.17702033001308956 > 0.17696843025630724
WOLFE (weak): th(2.154434690031884)=0.17696843025630724; dx=-2.4085580951293525E-5 evalInputDelta=5.189975678232539E-5
Adding measurement 46efc89a to history. Total: 2
New Minimum: 0.17696843025630724 > 0.17691654838933274
WOLFE (weak): th(4.308869380063768)=0.17691654838933274; dx=-2.4077278278707823E-5 evalInputDelta=1.037816237568212E-4
Adding measurement 69bc9ab4 to history. Total: 3
New Minimum: 0.17691654838933274 > 0.17670919972985316
WOLFE (weak): th(12.926608140191302)=0.17670919972985316; dx=-2.4044088393826366E-5 evalInputDelta=3.1113028323639935E-4
Adding measurement 6cd35b33 to history. Total: 4
New Minimum: 0.17670919972985316 > 0.17577966436954678
WOLFE (weak): th(51.70643256076521)=0.17577966436954678; dx=-2.38951454229837E-5 evalInputDelta=0.0012406656435427765
Adding measurement 75463a3d to history. Total: 5
New Minimum: 0.17577966436954678 > 0.1709188384217794
WOLFE (weak): th(258.53216280382605)=0.1709188384217794; dx=-2.311209362059013E-5 evalInputDelta=0.006101491591310154
Adding measurement 1cebd5cb to history. Total: 6
New Minimum: 0.1709188384217794 > 0.14401225215204555
END: th(1551.1929768229563)=0.14401225215204555; dx=-1.8635306365038082E-5 evalInputDelta=0.03300807786104401
Fitness changed from 0.17702033001308956 to 0.14401225215204555
Iteration 1 complete. Error: 0.14401225215204555 Total: 0.5342; Orientation: 0.0179; Line Search: 0.4124
Non-optimal measurement 0.14401225215204555 < 0.14401225215204555. Total: 7
Rejected: LBFGS Orientation magnitude: 3.099e+01, gradient 3.827e-03, dot -0.969; [fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.14401225215204555, 0.1709188384217794, 0.17577966436954678, 0.17670919972985316, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 3.100e+01, gradient 3.827e-03, dot -0.969; [50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.14401225215204555, 0.1709188384217794, 0.17577966436954678, 0.17670919972985316, 0.17691654838933274, 0.17696843025630724
Rejected: LBFGS Orientation magnitude: 3.102e+01, gradient 3.827e-03, dot -0.969; [fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.14401225215204555, 0.1709188384217794, 0.17577966436954678, 0.17670919972985316, 0.17691654838933274
Rejected: LBFGS Orientation magnitude: 3.110e+01, gradient 3.827e-03, dot -0.969; [17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.14401225215204555, 0.1709188384217794, 0.17577966436954678, 0.17670919972985316
LBFGS Accumulation History: 3 points
Removed measurement 1cebd5cb to history. Total: 6
Removed measurement 75463a3d to history. Total: 5
Removed measurement 6cd35b33 to history. Total: 4
Removed measurement 69bc9ab4 to history. Total: 3
Adding measurement 74fdbba4 to history. Total: 3
th(0)=0.14401225215204555;dx=-1.4645835095002616E-5
Adding measurement 15a705a0 to history. Total: 4
New Minimum: 0.14401225215204555 > 0.10379815933010347
END: th(3341.943960201201)=0.10379815933010347; dx=-9.666567502951021E-6 evalInputDelta=0.04021409282194208
Fitness changed from 0.14401225215204555 to 0.10379815933010347
Iteration 2 complete. Error: 0.10379815933010347 Total: 4.7733; Orientation: 4.5919; Line Search: 0.1736
Non-optimal measurement 0.10379815933010347 < 0.10379815933010347. Total: 5
Rejected: LBFGS Orientation magnitude: 2.400e+01, gradient 2.616e-03, dot -0.987; [fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.10379815933010347, 0.14401225215204555, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 2.401e+01, gradient 2.616e-03, dot -0.987; [fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.10379815933010347, 0.14401225215204555, 0.17691654838933274, 0.17696843025630724
LBFGS Accumulation History: 3 points
Removed measurement 15a705a0 to history. Total: 4
Removed measurement 74fdbba4 to history. Total: 3
Adding measurement 681179e2 to history. Total: 3
th(0)=0.10379815933010347;dx=-6.843787587101358E-6
Adding measurement 20a1c78 to history. Total: 4
New Minimum: 0.10379815933010347 > 0.06495895187618883
END: th(7200.000000000001)=0.06495895187618883; dx=-4.00088726558199E-6 evalInputDelta=0.03883920745391464
Fitness changed from 0.10379815933010347 to 0.06495895187618883
Iteration 3 complete. Error: 0.06495895187618883 Total: 2.2021; Orientation: 2.0806; Line Search: 0.0269
Non-optimal measurement 0.06495895187618883 < 0.06495895187618883. Total: 5
Rejected: LBFGS Orientation magnitude: 2.065e+01, gradient 1.717e-03, dot -0.990; [c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.06495895187618883, 0.10379815933010347, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 2.065e+01, gradient 1.717e-03, dot -0.990; [fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.06495895187618883, 0.10379815933010347, 0.17691654838933274, 0.17696843025630724
LBFGS Accumulation History: 3 points
Removed measurement 20a1c78 to history. Total: 4
Removed measurement 681179e2 to history. Total: 3
Adding measurement 100acbfc to history. Total: 3
th(0)=0.06495895187618883;dx=-2.9489899604965604E-6
Adding measurement 416cae3a to history. Total: 4
New Minimum: 0.06495895187618883 > 0.03349295369454822
END: th(15511.929768229566)=0.03349295369454822; dx=-6.335927960385645E-7 evalInputDelta=0.03146599818164061
Fitness changed from 0.06495895187618883 to 0.03349295369454822
Iteration 4 complete. Error: 0.03349295369454822 Total: 1.8894; Orientation: 1.7046; Line Search: 0.1761
Non-optimal measurement 0.03349295369454822 <
...skipping 9997 bytes...
1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.003637873863886123, 0.0039303686469284015, 0.0052317377664687255, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 4.176e+00, gradient 3.350e-04, dot -0.869; [c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.003637873863886123, 0.0039303686469284015, 0.0052317377664687255, 0.17691654838933274, 0.17696843025630724
Rejected: LBFGS Orientation magnitude: 8.188e+00, gradient 3.350e-04, dot -0.932; [fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.003637873863886123, 0.0039303686469284015, 0.0052317377664687255, 0.17691654838933274
LBFGS Accumulation History: 3 points
Removed measurement 39761409 to history. Total: 5
Removed measurement 310ef14d to history. Total: 4
Removed measurement 6d237ff9 to history. Total: 3
Adding measurement 1e710d11 to history. Total: 3
th(0)=0.003637873863886123;dx=-1.1219829690585705E-7
Adding measurement 3cf5eba4 to history. Total: 4
New Minimum: 0.003637873863886123 > 0.00234631052209241
END: th(16158.260175239137)=0.00234631052209241; dx=-2.990413817035653E-8 evalInputDelta=0.001291563341793713
Fitness changed from 0.003637873863886123 to 0.00234631052209241
Iteration 10 complete. Error: 0.00234631052209241 Total: 3.0389; Orientation: 2.9249; Line Search: 0.0239
Non-optimal measurement 0.00234631052209241 < 0.00234631052209241. Total: 5
Rejected: LBFGS Orientation magnitude: 4.472e+00, gradient 2.944e-04, dot -0.691; [50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.00234631052209241, 0.003637873863886123, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 4.473e+00, gradient 2.944e-04, dot -0.691; [50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.00234631052209241, 0.003637873863886123, 0.17691654838933274, 0.17696843025630724
LBFGS Accumulation History: 3 points
Removed measurement 3cf5eba4 to history. Total: 4
Removed measurement 1e710d11 to history. Total: 3
Adding measurement d1b723c to history. Total: 3
th(0)=0.00234631052209241;dx=-8.669892917423582E-8
Non-optimal measurement 0.0030355700414817317 < 0.00234631052209241. Total: 4
Armijo: th(34811.91625209586)=0.0030355700414817317; dx=1.490190514008148E-7 evalInputDelta=-6.892595193893217E-4
Adding measurement 749a783c to history. Total: 4
New Minimum: 0.00234631052209241 > 0.0016955460936196784
WOLF (strong): th(17405.95812604793)=0.0016955460936196784; dx=1.4119261823496474E-8 evalInputDelta=6.507644284727315E-4
Non-optimal measurement 0.0019373201109697767 < 0.0016955460936196784. Total: 5
END: th(5801.986042015978)=0.0019373201109697767; dx=-5.42982066385154E-8 evalInputDelta=4.0899041112263325E-4
Fitness changed from 0.00234631052209241 to 0.0016955460936196784
Iteration 11 complete. Error: 0.0016955460936196784 Total: 2.5626; Orientation: 2.2366; Line Search: 0.2854
Non-optimal measurement 0.0016955460936196784 < 0.0016955460936196784. Total: 5
Rejected: LBFGS Orientation magnitude: 2.246e+00, gradient 3.095e-04, dot -0.769; [17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.0016955460936196784, 0.00234631052209241, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 2.247e+00, gradient 3.095e-04, dot -0.769; [fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.0016955460936196784, 0.00234631052209241, 0.17691654838933274, 0.17696843025630724
LBFGS Accumulation History: 3 points
Removed measurement 749a783c to history. Total: 4
Removed measurement d1b723c to history. Total: 3
Adding measurement 4ffddb95 to history. Total: 3
th(0)=0.0016955460936196784;dx=-9.579597397540275E-8
Adding measurement 2de6588d to history. Total: 4
New Minimum: 0.0016955460936196784 > 0.001183076708064727
WOLF (strong): th(12500.00000000001)=0.001183076708064727; dx=2.2203321482686725E-8 evalInputDelta=5.124693855549515E-4
Non-optimal measurement 0.001255549481602434 < 0.001183076708064727. Total: 5
END: th(6250.000000000005)=0.001255549481602434; dx=-4.309816314341578E-8 evalInputDelta=4.399966120172444E-4
Fitness changed from 0.0016955460936196784 to 0.001183076708064727
Iteration 12 complete. Error: 0.001183076708064727 Total: 2.3629; Orientation: 2.2117; Line Search: 0.1444
Non-optimal measurement 0.001183076708064727 < 0.001183076708064727. Total: 5
Rejected: LBFGS Orientation magnitude: 1.001e+00, gradient 2.434e-04, dot -0.979; [fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.001183076708064727, 0.0016955460936196784, 0.17691654838933274, 0.17696843025630724, 0.17702033001308956
Rejected: LBFGS Orientation magnitude: 1.001e+00, gradient 2.434e-04, dot -0.979; [c92ed5a4-23cf-42fc-af2f-fa4adecbea40 = 1.000/1.000e+00, 50aab4e3-d099-4854-ba2d-5b6d50c02b43 = 1.000/1.000e+00, fd315c0a-9c80-4bfd-b1bc-1cd53ee8fb30 = 1.000/1.000e+00, 17470236-8a06-4b98-bb71-80e40b45cff2 = 1.000/1.000e+00, fcb5be2f-f487-4ea6-9234-1e51f8007e3f = 1.000/1.000e+00]
Orientation rejected. Popping history element from 0.001183076708064727, 0.0016955460936196784, 0.17691654838933274, 0.17696843025630724
LBFGS Accumulation History: 3 points
Removed measurement 2de6588d to history. Total: 4
Removed measurement 4ffddb95 to history. Total: 3
Adding measurement 675f1923 to history. Total: 3
th(0)=0.001183076708064727;dx=-5.925869394521184E-8
Adding measurement 38ed2da6 to history. Total: 4
New Minimum: 0.001183076708064727 > 9.46029757067168E-4
WOLF (strong): th(13465.216812699284)=9.46029757067168E-4; dx=2.269157643177086E-8 evalInputDelta=2.37046950997559E-4
Adding measurement 5c5b71a1 to history. Total: 5
New Minimum: 9.46029757067168E-4 > 9.268622519450648E-4
END: th(6732.608406349642)=9.268622519450648E-4; dx=-1.726480816065297E-8 evalInputDelta=2.5621445611966216E-4
Fitness changed from 0.001183076708064727 to 9.268622519450648E-4
Iteration 13 complete. Error: 9.268622519450648E-4 Total: 2.3833; Orientation: 2.2644; Line Search: 0.1116
Final threshold in iteration 13: 9.268622519450648E-4 (> 0.0) after 30.370s (< 30.000s)
Returns
9.268622519450648E-4
This training apply resulted in the following configuration:
TrainingTester.java:610 executed in 0.00 seconds (0.000 gc):
RefList<double[]> state = network.state();
assert state != null;
String description = state.stream().map(RefArrays::toString).reduce((a, b) -> a + "\n" + b)
.orElse("");
state.freeRef();
return description;
Returns
TrainingTester.java:622 executed in 0.00 seconds (0.000 gc):
return RefArrays.stream(RefUtil.addRef(data)).flatMap(x -> {
return RefArrays.stream(x);
}).limit(1).map(x -> {
String temp_18_0015 = x.prettyPrint();
x.freeRef();
return temp_18_0015;
}).reduce((a, b) -> a + "\n" + b).orElse("");
Returns
[
[ [ 0.21080791878734512 ], [ -0.9604496535064276 ], [ 0.48625822136227637 ], [ -0.19969637409570273 ], [ -0.29864582603824735 ], [ -0.5786729596189761 ], [ -0.00576346608377808 ], [ -0.7831428741220743 ], ... ],
[ [ -0.20831314362205852 ], [ 0.4365424745182739 ], [ 0.6653352297812419 ], [ 0.7285488542156217 ], [ -0.6073089970828981 ], [ 0.2753144132023579 ], [ -0.1773760208802567 ], [ 0.18528471887927225 ], ... ],
[ [ 0.20545462127067357 ], [ 0.7633161963443861 ], [ -0.4045225354141657 ], [ 0.7180515618839955 ], [ 0.7948778047684645 ], [ -0.30066540216288573 ], [ 0.7193196049309042 ], [ -0.21295777590851528 ], ... ],
[ [ -0.22940929870611113 ], [ -0.2995926536186712 ], [ 0.29375745338323717 ], [ 0.31549073726883964 ], [ 0.5462865152649207 ], [ 0.2104496705990237 ], [ 0.22658698359746918 ], [ -0.5653776370042198 ], ... ],
[ [ 0.7129146133248081 ], [ -0.8367907818336372 ], [ -0.30759724551277284 ], [ 0.3188071758790852 ], [ -0.2720026818981318 ], [ -0.583621352537793 ], [ -0.8269423394014733 ], [ 0.5643878996624182 ], ... ],
[ [ 0.7431421533170883 ], [ 0.296020419036058 ], [ 0.7924345558640027 ], [ 0.5650242294082697 ], [ -0.8708343198102387 ], [ -0.7486974538040985 ], [ 0.2989942620659912 ], [ -0.5743493175986237 ], ... ],
[ [ -0.7540394861858188 ], [ 0.31474218149928834 ], [ -0.22058414157520137 ], [ -0.3765148419152263 ], [ 0.45305020291381787 ], [ 0.2379795596682527 ], [ 0.04950812862884863 ], [ 0.8269061231742487 ], ... ],
[ [ -0.7202121955890955 ], [ 0.8836595456810595 ], [ 0.8838763207466447 ], [ 0.21859501322381408 ], [ -0.11195213472873809 ], [ 0.3052166752425421 ], [ -0.7229582520791202 ], [ 0.897659538846299 ], ... ],
...
]
To produce the following output:
TrainingTester.java:633 executed in 0.00 seconds (0.000 gc):
Result[] array = ConstantResult.batchResultArray(pop(RefUtil.addRef(data)));
@Nullable
Result eval = layer.eval(array);
assert eval != null;
TensorList tensorList = Result.getData(eval);
String temp_18_0016 = tensorList.stream().limit(1).map(x -> {
String temp_18_0017 = x.prettyPrint();
x.freeRef();
return temp_18_0017;
}).reduce((a, b) -> a + "\n" + b).orElse("");
tensorList.freeRef();
return temp_18_0016;
Returns
[
[ [ 0.04443997862345189 ], [ 0.9224635369206169 ], [ 0.23644705784240455 ], [ 0.03987864182697085 ], [ 0.0891893294100671 ], [ 0.3348623941941852 ], [ 3.321754129886024E-5 ], [ 0.6133127612881831 ], ... ],
[ [ 0.04339436580570438 ], [ 0.1905693320585378 ], [ 0.442670967988058 ], [ 0.5307834329788952 ], [ 0.36882421793783554 ], [ 0.07579802611695866 ], [ 0.03146225278331326 ], [ 0.03433042705017095 ], ... ],
[ [ 0.04221160140147591 ], [ 0.5826516156016613 ], [ 0.16363848165790496 ], [ 0.5155980455240455 ], [ 0.6318307245135332 ], [ 0.09039968405776981 ], [ 0.5174206940379521 ], [ 0.04535101431990141 ], ... ],
[ [ 0.05262862633282972 ], [ 0.08975575810227711 ], [ 0.08629344141820476 ], [ 0.099534405302436 ], [ 0.2984289567602904 ], [ 0.04428906385523758 ], [ 0.051341661135799764 ], [ 0.31965187242447535 ], ... ],
[ [ 0.5082472458920606 ], [ 0.7002188125617498 ], [ 0.09461606544704505 ], [ 0.10163801539199796 ], [ 0.07398545895977629 ], [ 0.34061388313804286 ], [ 0.6838336326947815 ], [ 0.31853370128535585 ], ... ],
[ [ 0.5522602600367588 ], [ 0.08762808848628338 ], [ 0.6279525253273792 ], [ 0.319252379818409 ], [ 0.7583524125593611 ], [ 0.5605478773327401 ], [ 0.08939756874838664 ], [ 0.32987713862600476 ], ... ],
[ [ 0.5685755467273736 ], [ 0.09906264081493096 ], [ 0.048657363514468484 ], [ 0.14176342618244783 ], [ 0.20525448636025154 ], [ 0.05663427081989545 ], [ 0.0024510548003306215 ], [ 0.6837737365430658 ], ... ],
[ [ 0.5187056066752657 ], [ 0.7808541926732565 ], [ 0.7812373503766256 ], [ 0.047783779806319454 ], [ 0.012533280470321526 ], [ 0.0931572188461114 ], [ 0.5226686342492968 ], [ 0.8057926476817502 ], ... ],
...
]
TrainingTester.java:432 executed in 0.11 seconds (0.000 gc):
return TestUtil.compare(title + " vs Iteration", runs);
Plotting range=[1.0, -6.984426527150667], [124.0, -0.8416005577959389]; valueStats=DoubleSummaryStatistics{count=205, sum=0.969788, min=0.000000, average=0.004731, max=0.144012}
Plotting 124 points for GD
Plotting 68 points for CjGD
Plotting 13 points for LBFGS
Returns
TrainingTester.java:435 executed in 0.01 seconds (0.000 gc):
return TestUtil.compareTime(title + " vs Time", runs);
Plotting range=[0.0, -6.984426527150667], [29.836, -0.8416005577959389]; valueStats=DoubleSummaryStatistics{count=205, sum=0.969788, min=0.000000, average=0.004731, max=0.144012}
Plotting 124 points for GD
Plotting 68 points for CjGD
Plotting 13 points for LBFGS
Returns
TrainingTester.java:255 executed in 0.00 seconds (0.000 gc):
return grid(inputLearning, modelLearning, completeLearning);
Returns
TrainingTester.java:258 executed in 0.00 seconds (0.000 gc):
return new ComponentResult(null == inputLearning ? null : inputLearning.value,
null == modelLearning ? null : modelLearning.value, null == completeLearning ? null : completeLearning.value);
Returns
{"input":{ "LBFGS": { "type": "NonConverged", "value": 9.268622519450648E-4 }, "CjGD": { "type": "NonConverged", "value": 7.487228789601366E-6 }, "GD": { "type": "NonConverged", "value": 1.0365099437470608E-7 } }, "model":null, "complete":null}
LayerTests.java:425 executed in 0.00 seconds (0.000 gc):
throwException(exceptions.addRef());
| details | result |
|---|---|
| {"input":{ "LBFGS": { "type": "NonConverged", "value": 9.268622519450648E-4 }, "CjGD": { "type": "NonConverged", "value": 7.487228789601366E-6 }, "GD": { "type": "NonConverged", "value": 1.0365099437470608E-7 } }, "model":null, "complete":null} | OK |
{
"result": "OK",
"performance": {
"execution_time": "91.525",
"gc_time": "0.622"
},
"created_on": 1586737613969,
"file_name": "trainingTest",
"report": {
"simpleName": "SquarePowerTest",
"canonicalName": "com.simiacryptus.mindseye.layers.java.NthPowerActivationLayerTest.SquarePowerTest",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/test/java/com/simiacryptus/mindseye/layers/java/NthPowerActivationLayerTest.java",
"javaDoc": ""
},
"training_analysis": {
"input": {
"LBFGS": {
"type": "NonConverged",
"value": 9.268622519450648E-4
},
"CjGD": {
"type": "NonConverged",
"value": 7.487228789601366E-6
},
"GD": {
"type": "NonConverged",
"value": 1.0365099437470608E-7
}
}
},
"archive": "s3://code.simiacrypt.us/tests/com/simiacryptus/mindseye/layers/java/NthPowerActivationLayer/SquarePowerTest/trainingTest/202004132653",
"id": "9cf54cfe-cc92-4964-9035-26d823d4aed6",
"report_type": "Components",
"display_name": "Comparative Training",
"target": {
"simpleName": "NthPowerActivationLayer",
"canonicalName": "com.simiacryptus.mindseye.layers.java.NthPowerActivationLayer",
"link": "https://github.com/SimiaCryptus/mindseye-java/tree/93db34cedee48c0202777a2b25deddf1dfaf5731/src/main/java/com/simiacryptus/mindseye/layers/java/NthPowerActivationLayer.java",
"javaDoc": ""
}
}