trial_index,submit_time,queue_time,start_time,end_time,run_time,program_string,VAL_ACC,exit_code,signal,hostname,OO_Info_SLURM_JOB_ID,arm_name,trial_status,generation_node,epochs,lr,batch_size,hidden_size,dropout,num_dense_layers,weight_decay,activation,init
0,1753190693,31,1753190724,1753190742,18,python3 .tests/mnist/train --epochs 119 --learning_rate 0.04547517540752887832 --batch_size 4096 --hidden_size 4774 --dropout 0.32788604497909545898 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.62162548303604125977,,1,,n1719,18578891,0_0,FAILED,SOBOL,119,0.04547517540752887832411488489,4096,4774,0.327886044979095458984375,4,0.621625483036041259765625,leaky_relu,normal
1,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 37 --learning_rate 0.08187936280146242141 --batch_size 263 --hidden_size 279 --dropout 0.01473537832498550415 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.16510647721588611603,,1,,n1720,18578887,1_0,FAILED,SOBOL,37,0.081879362801462421406206715346,263,279,0.014735378324985504150390625,1,0.16510647721588611602783203125,leaky_relu,normal
2,1753190693,31,1753190724,1753190730,6,python3 .tests/mnist/train --epochs 103 --learning_rate 0.01556215909915044902 --batch_size 3014 --hidden_size 6726 --dropout 0.21049671946093440056 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.81585886608809232712,,1,,n1719,18578892,2_0,FAILED,SOBOL,103,0.015562159099150449023674092075,3014,6726,0.210496719460934400558471679688,2,0.815858866088092327117919921875,leaky_relu,normal
3,1753190695,29,1753190724,1753190755,31,python3 .tests/mnist/train --epochs 162 --learning_rate 0.05094199270252138673 --batch_size 1225 --hidden_size 2543 --dropout 0.39781150175258517265 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39737818669527769089,,1,,n1719,18578893,3_0,FAILED,SOBOL,162,0.05094199270252138672665509489,1225,2543,0.397811501752585172653198242188,3,0.397378186695277690887451171875,leaky_relu,normal
4,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 200 --learning_rate 0.01155153194935992257 --batch_size 785 --hidden_size 3509 --dropout 0.48275432456284761429 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.94342354964464902878,,1,,n1720,18578888,4_0,FAILED,SOBOL,200,0.011551531949359922571418657355,785,3509,0.482754324562847614288330078125,4,0.943423549644649028778076171875,leaky_relu,normal
5,1753190694,50,1753190744,1753190751,7,python3 .tests/mnist/train --epochs 64 --learning_rate 0.07211981368083507371 --batch_size 3084 --hidden_size 7710 --dropout 0.1704127797856926918 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.26908155810087919235,,1,,n1720,18578895,5_0,FAILED,SOBOL,64,0.072119813680835073710362337351,3084,7710,0.170412779785692691802978515625,1,0.269081558100879192352294921875,leaky_relu,normal
6,1753190693,30,1753190723,1753190754,31,python3 .tests/mnist/train --epochs 22 --learning_rate 0.03073621091721579282 --batch_size 1850 --hidden_size 1372 --dropout 0.11533369356766343117 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.74406123347580432892,,1,,n1720,18578884,6_0,FAILED,SOBOL,22,0.030736210917215792820522679563,1850,1372,0.115333693567663431167602539062,2,0.74406123347580432891845703125,leaky_relu,normal
7,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 134 --learning_rate 0.09193863467276096324 --batch_size 2106 --hidden_size 5886 --dropout 0.30351876327767968178 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.04340361244976520538,,1,,n1720,18578889,7_0,FAILED,SOBOL,134,0.091938634672760963240101261817,2106,5886,0.303518763277679681777954101562,3,0.04340361244976520538330078125,leaky_relu,normal
8,1753190695,54,1753190749,1753190756,7,python3 .tests/mnist/train --epochs 146 --learning_rate 0.01951632173424586517 --batch_size 1674 --hidden_size 7387 --dropout 0.0547425542026758194 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.91777744051069021225,,1,,n1720,18578900,8_0,FAILED,SOBOL,146,0.019516321734245865165968680799,1674,7387,0.05474255420267581939697265625,3,0.917777440510690212249755859375,leaky_relu,normal
9,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 10 --learning_rate 0.057890026364848024 --batch_size 2440 --hidden_size 3960 --dropout 0.36801899783313274384 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.37337908800691366196,,1,,n1720,18578890,9_0,FAILED,SOBOL,10,0.05789002636484802399863269784,2440,3960,0.36801899783313274383544921875,2,0.373379088006913661956787109375,leaky_relu,normal
10,1753190695,56,1753190751,1753190758,7,python3 .tests/mnist/train --epochs 76 --learning_rate 0.03838079315507784972 --batch_size 703 --hidden_size 5186 --dropout 0.40650656586512923241 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.64473813585937023163,,1,,n1720,18578897,10_0,FAILED,SOBOL,76,0.038380793155077849720946403522,703,5186,0.406506565865129232406616210938,1,0.64473813585937023162841796875,leaky_relu,normal
11,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 188 --learning_rate 0.07807154996600002006 --batch_size 3515 --hidden_size 1944 --dropout 0.21931778779253363609 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.06413633935153484344,,1,,n1720,18578885,11_0,FAILED,SOBOL,188,0.078071549966000020059908592884,3515,1944,0.219317787792533636093139648438,4,0.06413633935153484344482421875,leaky_relu,normal
12,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 174 --learning_rate 0.03478188869664446126 --batch_size 2676 --hidden_size 979 --dropout 0.1499941973015666008 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.51693118922412395477,,1,,n1720,18578886,12_0,FAILED,SOBOL,174,0.034781888696644461256290981055,2676,979,0.149994197301566600799560546875,3,0.51693118922412395477294921875,leaky_relu,normal
13,1753190695,49,1753190744,1753190751,7,python3 .tests/mnist/train --epochs 91 --learning_rate 0.09884393323194236303 --batch_size 1398 --hidden_size 4203 --dropout 0.4622173672541975975 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.19218694977462291718,,1,,n1720,18578898,13_0,FAILED,SOBOL,91,0.098843933231942363026867326425,1398,4203,0.462217367254197597503662109375,2,0.19218694977462291717529296875,leaky_relu,normal
14,1753190695,49,1753190744,1753190757,13,python3 .tests/mnist/train --epochs 49 --learning_rate 0.00440232499679550551 --batch_size 3662 --hidden_size 2867 --dropout 0.25178997637704014778 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.79558388050645589828,,1,,n1720,18578896,14_0,FAILED,SOBOL,49,0.004402324996795505505919887668,3662,2867,0.251789976377040147781372070312,1,0.795583880506455898284912109375,leaky_relu,normal
15,1753190695,49,1753190744,1753190751,7,python3 .tests/mnist/train --epochs 107 --learning_rate 0.0683180442947894373 --batch_size 340 --hidden_size 6275 --dropout 0.06348677026107907295 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.4953280305489897728,,1,,n1720,18578894,15_0,FAILED,SOBOL,107,0.068318044294789437298476286742,340,6275,0.063486770261079072952270507812,4,0.495328030548989772796630859375,leaky_relu,normal
16,1753190812,24,1753190836,1753190842,6,python3 .tests/mnist/train --epochs 113 --learning_rate 0.00124535889513790608 --batch_size 2386 --hidden_size 1095 --dropout 0.38922261074185371399 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14561120886355638504,,1,,n1720,18578913,16_0,FAILED,SOBOL,113,0.001245358895137906084585321942,2386,1095,0.3892226107418537139892578125,2,0.145611208863556385040283203125,leaky_relu,normal
17,1753190835,31,1753190866,1753190872,6,python3 .tests/mnist/train --epochs 55 --learning_rate 0.06535618589064107198 --batch_size 1620 --hidden_size 6128 --dropout 0.20144571363925933838 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.56299528200179338455,,1,,n1720,18578949,17_0,FAILED,SOBOL,55,0.065356185890641071978279796895,1620,6128,0.20144571363925933837890625,3,0.562995282001793384552001953125,leaky_relu,normal
18,1753190864,32,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 85 --learning_rate 0.03179266022872179881 --batch_size 3444 --hidden_size 3243 --dropout 0.02232909528538584709 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.41687381640076637268,,1,,n1719,18579001,18_0,FAILED,SOBOL,85,0.031792660228721798809647935968,3444,3243,0.022329095285385847091674804688,4,0.4168738164007663726806640625,leaky_relu,normal
19,1753190877,19,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.09565960339317099159 --batch_size 633 --hidden_size 7948 --dropout 0.33402595622465014458 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.87448965385556221008,,1,,n1719,18579049,19_0,FAILED,SOBOL,168,0.095659603393170991592064922315,633,7948,0.334025956224650144577026367188,1,0.8744896538555622100830078125,leaky_relu,normal
20,1753190890,6,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 182 --learning_rate 0.04222384893205017448 --batch_size 1472 --hidden_size 6996 --dropout 0.29592188913375139236 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29638927057385444641,,1,,n1719,18579056,20_0,FAILED,SOBOL,182,0.042223848932050174476149351221,1472,6996,0.295921889133751392364501953125,2,0.2963892705738544464111328125,leaky_relu,normal
21,1753190889,7,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 70 --learning_rate 0.0805487714746035699 --batch_size 2750 --hidden_size 2309 --dropout 0.10919838491827249527 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99424130097031593323,,1,,n1719,18579054,21_0,FAILED,SOBOL,70,0.08054877147460356989761010027,2750,2309,0.109198384918272495269775390625,3,0.9942413009703159332275390625,leaky_relu,normal
22,1753190888,8,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 16 --learning_rate 0.02201457734219729873 --batch_size 398 --hidden_size 5047 --dropout 0.17899719858542084694 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.01609530765563249588,,1,,n1719,18579050,22_0,FAILED,SOBOL,16,0.022014577342197298726045318062,398,5047,0.178997198585420846939086914062,4,0.016095307655632495880126953125,leaky_relu,normal
23,1753190889,7,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 152 --learning_rate 0.06175411065882072115 --batch_size 3721 --hidden_size 33 --dropout 0.49180836835876107216 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.69324312824755907059,,1,,n1719,18579055,23_0,FAILED,SOBOL,152,0.061754110658820721146966548076,3721,33,0.491808368358761072158813476562,1,0.693243128247559070587158203125,leaky_relu,normal
24,1753190889,7,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.02796652501225471363 --batch_size 60 --hidden_size 2625 --dropout 0.24352808482944965363 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31481028348207473755,,1,,n1719,18579053,24_0,FAILED,SOBOL,140,0.027966525012254713628001567827,60,2625,0.24352808482944965362548828125,1,0.314810283482074737548828125,leaky_relu,normal
25,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 28 --learning_rate 0.08858358920393512304 --batch_size 3893 --hidden_size 6552 --dropout 0.43118660710752010345 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89822172373533248901,,1,,n1720,18579057,25_0,FAILED,SOBOL,28,0.088583589203935123035371645983,3893,6552,0.43118660710752010345458984375,4,0.898221723735332489013671875,leaky_relu,normal
26,1753190892,33,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 58 --learning_rate 0.00817502328474074488 --batch_size 1038 --hidden_size 740 --dropout 0.34479621564969420433 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.12270453665405511856,,1,,n1720,18579061,26_0,FAILED,SOBOL,58,0.008175023284740744883292151712,1038,740,0.344796215649694204330444335938,3,0.122704536654055118560791015625,leaky_relu,normal
27,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 194 --learning_rate 0.06932867090674117716 --batch_size 2827 --hidden_size 4468 --dropout 0.03298121830448508263 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.66429348383098840714,,1,,n1720,18579060,27_0,FAILED,SOBOL,194,0.069328670906741177160093059229,2827,4468,0.032981218304485082626342773438,2,0.664293483830988407135009765625,leaky_relu,normal
28,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 156 --learning_rate 0.01823117797318845809 --batch_size 3268 --hidden_size 5421 --dropout 0.08670460712164640427 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24294306430965662003,,1,,n1720,18579059,28_0,FAILED,SOBOL,156,0.018231177973188458091291508367,3268,5421,0.086704607121646404266357421875,1,0.242943064309656620025634765625,leaky_relu,normal
29,1753190892,33,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 97 --learning_rate 0.05458658206956461256 --batch_size 968 --hidden_size 1675 --dropout 0.27355387713760137558 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.5442995736375451088,,1,,n1720,18579062,29_0,FAILED,SOBOL,97,0.054586582069564612562651007011,968,1675,0.273553877137601375579833984375,4,0.544299573637545108795166015625,leaky_relu,normal
30,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 43 --learning_rate 0.04914746912792325451 --batch_size 2305 --hidden_size 7633 --dropout 0.43800438614562153816 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.4445722624659538269,,1,,n1720,18579058,30_0,FAILED,SOBOL,43,0.049147469127923254506029593358,2305,7633,0.438004386145621538162231445312,3,0.444572262465953826904296875,leaky_relu,normal
31,1753190892,33,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 125 --learning_rate 0.08457607923699543562 --batch_size 2050 --hidden_size 3687 --dropout 0.12531922059133648872 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.76821608096361160278,,1,,n1720,18579063,31_0,FAILED,SOBOL,125,0.084576079236995435617352256941,2050,3687,0.125319220591336488723754882812,2,0.768216080963611602783203125,leaky_relu,normal
32,1753191005,16,1753191021,1753191027,6,python3 .tests/mnist/train --epochs 129 --learning_rate 0.01326881769858300614 --batch_size 743 --hidden_size 209 --dropout 0.30879422789439558983 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43125533033162355423,,1,,n1720,18579075,32_0,FAILED,SOBOL,129,0.013268817698583006137180717587,743,209,0.308794227894395589828491210938,2,0.431255330331623554229736328125,leaky_relu,normal
33,1753191005,11,1753191016,1753191022,6,python3 .tests/mnist/train --epochs 41 --learning_rate 0.05177052574371919513 --batch_size 3554 --hidden_size 4968 --dropout 0.12196009745821356773 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.85546946991235017776,,1,,n1720,18579074,33_0,FAILED,SOBOL,41,0.051770525743719195133074606474,3554,4968,0.121960097458213567733764648438,3,0.855469469912350177764892578125,leaky_relu,normal
34,1753191005,16,1753191021,1753191027,6,python3 .tests/mnist/train --epochs 93 --learning_rate 0.04474420142527670008 --batch_size 1761 --hidden_size 2102 --dropout 0.16062025167047977448 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.13122984394431114197,,1,,n1720,18579073,34_0,FAILED,SOBOL,93,0.044744201425276700079258773712,1761,2102,0.16062025167047977447509765625,4,0.1312298439443111419677734375,leaky_relu,normal
35,1753191052,24,1753191076,1753191082,6,python3 .tests/mnist/train --epochs 157 --learning_rate 0.08427026354009285736 --batch_size 2528 --hidden_size 7044 --dropout 0.47332079522311687469 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.58201531693339347839,,1,,n1720,18579079,35_0,FAILED,SOBOL,157,0.084270263540092857357244326977,2528,7044,0.47332079522311687469482421875,1,0.5820153169333934783935546875,leaky_relu,normal
36,1753191072,33,1753191105,1753191112,7,python3 .tests/mnist/train --epochs 190 --learning_rate 0.02844115424733608885 --batch_size 3607 --hidden_size 8156 --dropout 0.40394197823479771614 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.0029346756637096405,,1,,n1720,18579080,36_0,FAILED,SOBOL,190,0.028441154247336088850550694929,3607,8156,0.403941978234797716140747070312,2,0.0029346756637096405029296875,leaky_relu,normal
37,1753191080,25,1753191105,1753191112,7,python3 .tests/mnist/train --epochs 61 --learning_rate 0.09276545393327251254 --batch_size 285 --hidden_size 3195 --dropout 0.21626807795837521553 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.70957758650183677673,,1,,n1720,18579081,37_0,FAILED,SOBOL,61,0.092765453933272512543339871627,285,3195,0.216268077958375215530395507812,3,0.7095775865018367767333984375,leaky_relu,normal
38,1753191118,17,1753191135,1753191141,6,python3 .tests/mnist/train --epochs 31 --learning_rate 0.01082227202691137674 --batch_size 2605 --hidden_size 5952 --dropout 0.00579774659126996994 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.30954999197274446487,,1,,n1720,18579091,38_0,FAILED,SOBOL,31,0.01082227202691137674106514055,2605,5952,0.005797746591269969940185546875,4,0.309549991972744464874267578125,leaky_relu,normal
39,1753191117,18,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 137 --learning_rate 0.0745124282001517757 --batch_size 1327 --hidden_size 1175 --dropout 0.31759760435670614243 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.977906753309071064,,1,,n1720,18579087,39_0,FAILED,SOBOL,137,0.074512428200151775703474754664,1327,1175,0.317597604356706142425537109375,1,0.977906753309071063995361328125,leaky_relu,normal
40,1753191118,17,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 149 --learning_rate 0.03921075509116053737 --batch_size 2973 --hidden_size 3766 --dropout 0.07420253334566950798 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10826213657855987549,,1,,n1720,18579090,40_0,FAILED,SOBOL,149,0.039210755091160537366690164163,2973,3766,0.074202533345669507980346679688,1,0.10826213657855987548828125,leaky_relu,normal
41,1753191118,17,1753191135,1753191141,6,python3 .tests/mnist/train --epochs 19 --learning_rate 0.07577963783247396168 --batch_size 1184 --hidden_size 7456 --dropout 0.26091065956279635429 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68288627266883850098,,1,,n1720,18579089,41_0,FAILED,SOBOL,19,0.075779637832473961678303453482,1184,7456,0.260910659562796354293823242188,4,0.6828862726688385009765625,leaky_relu,normal
42,1753191118,17,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 73 --learning_rate 0.02190579320583492529 --batch_size 4008 --hidden_size 1626 --dropout 0.45675111934542655945 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.3292528325691819191,,1,,n1720,18579088,42_0,FAILED,SOBOL,73,0.021905793205834925285735437228,4008,1626,0.4567511193454265594482421875,3,0.329252832569181919097900390625,leaky_relu,normal
43,1753191117,18,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 179 --learning_rate 0.05715762227820232744 --batch_size 174 --hidden_size 5628 --dropout 0.14392480999231338501 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.8796287858858704567,,1,,n1720,18579086,43_0,FAILED,SOBOL,179,0.057157622278202327437135465971,174,5628,0.143924809992313385009765625,2,0.879628785885870456695556640625,leaky_relu,normal
44,1753191118,17,1753191135,1753191141,6,python3 .tests/mnist/train --epochs 169 --learning_rate 0.00523400294650346043 --batch_size 1908 --hidden_size 4516 --dropout 0.22893436485901474953 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45730573777109384537,,1,,n1720,18579092,44_0,FAILED,SOBOL,169,0.005234002946503460429461540571,1908,4516,0.228934364859014749526977539062,1,0.457305737771093845367431640625,leaky_relu,normal
45,1753191135,33,1753191168,1753191174,6,python3 .tests/mnist/train --epochs 81 --learning_rate 0.06602784668626264508 --batch_size 2163 --hidden_size 533 --dropout 0.41672640154138207436 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75182049814611673355,,1,,n1720,18579095,45_0,FAILED,SOBOL,81,0.066027846686262645081733069219,2163,533,0.416726401541382074356079101562,4,0.751820498146116733551025390625,leaky_relu,normal
46,1753191135,31,1753191166,1753191172,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.0371696441546082515 --batch_size 857 --hidden_size 6473 --dropout 0.36145368684083223343 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.23020967841148376465,,1,,n1720,18579094,46_0,FAILED,SOBOL,52,0.037169644154608251496174631257,857,6473,0.361453686840832233428955078125,3,0.2302096784114837646484375,leaky_relu,normal
47,1753191135,31,1753191166,1753191172,6,python3 .tests/mnist/train --epochs 117 --learning_rate 0.09810981462029741418 --batch_size 3157 --hidden_size 2801 --dropout 0.04977220389991998672 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.56069506704807281494,,1,,n1720,18579096,47_0,FAILED,SOBOL,117,0.098109814620297414178295980491,3157,2801,0.049772203899919986724853515625,2,0.56069506704807281494140625,leaky_relu,normal
48,1753191253,33,1753191286,1753191299,13,python3 .tests/mnist/train --epochs 111 --learning_rate 0.0340861925455741635 --batch_size 1111 --hidden_size 5678 --dropout 0.49745771801099181175 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.82816515304148197174,,1,,n1720,18579101,48_0,FAILED,SOBOL,111,0.034086192545574163503818709842,1111,5678,0.497457718010991811752319335938,4,0.82816515304148197174072265625,leaky_relu,normal
49,1753191258,28,1753191286,1753191293,7,python3 .tests/mnist/train --epochs 47 --learning_rate 0.09483125977963209607 --batch_size 2900 --hidden_size 1421 --dropout 0.18524968763813376427 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.38043322600424289703,,1,,n1720,18579102,49_0,FAILED,SOBOL,47,0.094831259779632096074131197838,2900,1421,0.185249687638133764266967773438,1,0.38043322600424289703369140625,leaky_relu,normal
50,1753193953,37,1753193990,1753193996,6,python3 .tests/mnist/train --epochs 87 --learning_rate 0.00197614317061379531 --batch_size 116 --hidden_size 7887 --dropout 0.0987878013402223587 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60931927245110273361,,1,,n1720,18579857,50_0,FAILED,SOBOL,87,0.001976143170613795310708304953,116,7887,0.09878780134022235870361328125,2,0.609319272451102733612060546875,leaky_relu,normal
51,1753193953,36,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 175 --learning_rate 0.06296509572435170232 --batch_size 3950 --hidden_size 3429 --dropout 0.28710638545453548431 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.1820513484999537468,,1,,n1720,18579856,51_0,FAILED,SOBOL,175,0.062965095724351702322074686435,3950,3429,0.28710638545453548431396484375,3,0.182051348499953746795654296875,leaky_relu,normal
52,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 185 --learning_rate 0.02430944309579208609 --batch_size 2216 --hidden_size 2367 --dropout 0.34077436896041035652 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.72906957846134901047,,1,,n1720,18579853,52_0,FAILED,SOBOL,185,0.024309443095792086092510331241,2216,2367,0.340774368960410356521606445312,4,0.729069578461349010467529296875,leaky_relu,normal
53,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 79 --learning_rate 0.06092710197065025896 --batch_size 1961 --hidden_size 6806 --dropout 0.0274825473316013813 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.06156909745186567307,,1,,n1720,18579845,53_0,FAILED,SOBOL,79,0.06092710197065025895524215116,1961,6806,0.027482547331601381301879882812,1,0.061569097451865673065185546875,leaky_relu,normal
54,1753193954,35,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 13 --learning_rate 0.04295329977078363864 --batch_size 3227 --hidden_size 486 --dropout 0.19213431607931852341 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.95841535367071628571,,1,,n1720,18579858,54_0,FAILED,SOBOL,13,0.042953299770783638644733315459,3227,486,0.192134316079318523406982421875,2,0.95841535367071628570556640625,leaky_relu,normal
55,1753193950,13,1753193963,1753193969,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.07815634638294578773 --batch_size 927 --hidden_size 4726 --dropout 0.3793079545721411705 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25091592408716678619,,1,,n1720,18579847,55_0,FAILED,SOBOL,143,0.078156346382945787731877373972,927,4726,0.379307954572141170501708984375,3,0.25091592408716678619384765625,leaky_relu,normal
56,1753193950,39,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 131 --learning_rate 0.00734486968806013531 --batch_size 3373 --hidden_size 6226 --dropout 0.13541692821308970451 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.63212676253169775009,,1,,n1720,18579855,56_0,FAILED,SOBOL,131,0.007344869688060135307083875489,3373,6226,0.135416928213089704513549804688,3,0.632126762531697750091552734375,leaky_relu,normal
57,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 25 --learning_rate 0.07162039286829531559 --batch_size 562 --hidden_size 3074 --dropout 0.44774309499189257622 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.08089810516685247421,,1,,n1720,18579846,57_0,FAILED,SOBOL,25,0.071620392868295315591531391419,562,3074,0.447743094991892576217651367188,2,0.080898105166852474212646484375,leaky_relu,normal
58,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 67 --learning_rate 0.02557724520126357717 --batch_size 2331 --hidden_size 4282 --dropout 0.26846151426434516907 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93038890324532985687,,1,,n1720,18579844,58_0,FAILED,SOBOL,67,0.025577245201263577173422802957,2331,4282,0.2684615142643451690673828125,1,0.93038890324532985687255859375,leaky_relu,normal
59,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 196 --learning_rate 0.08931618346255272567 --batch_size 1564 --hidden_size 802 --dropout 0.08026130497455596924 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.3566172327846288681,,1,,n1720,18579852,59_0,FAILED,SOBOL,196,0.089316183462552725669247877249,1564,802,0.08026130497455596923828125,4,0.35661723278462886810302734375,leaky_relu,normal
60,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 163 --learning_rate 0.04831598283881322065 --batch_size 485 --hidden_size 1864 --dropout 0.0422240295447409153 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.81039257906377315521,,1,,n1720,18579851,60_0,FAILED,SOBOL,163,0.04831598283881322064559071805,485,1864,0.042224029544740915298461914062,3,0.81039257906377315521240234375,leaky_relu,normal
61,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 99 --learning_rate 0.08686646701749414778 --batch_size 3807 --hidden_size 5363 --dropout 0.35538984695449471474 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.47685722075402736664,,1,,n1720,18579848,61_0,FAILED,SOBOL,99,0.086866467017494147784262281675,3807,5363,0.355389846954494714736938476562,2,0.47685722075402736663818359375,leaky_relu,normal
62,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 35 --learning_rate 0.01584323085462674419 --batch_size 1511 --hidden_size 4009 --dropout 0.42523923236876726151 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.50212263967841863632,,1,,n1720,18579849,62_0,FAILED,SOBOL,35,0.015843230854626744186219866606,1511,4009,0.425239232368767261505126953125,1,0.502122639678418636322021484375,leaky_relu,normal
63,1753193950,39,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 123 --learning_rate 0.0553205105092376484 --batch_size 2789 --hidden_size 7179 --dropout 0.23793982807546854019 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.21065761055797338486,,1,,n1720,18579854,63_0,FAILED,SOBOL,123,0.05532051050923764839994944964,2789,7179,0.237939828075468540191650390625,4,0.210657610557973384857177734375,leaky_relu,normal
64,1753193954,35,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 121 --learning_rate 0.00982255834611132743 --batch_size 1352 --hidden_size 2955 --dropout 0.11837203986942768097 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02814712561666965485,,1,,n1720,18579859,64_0,FAILED,SOBOL,121,0.009822558346111327429173165626,1352,2955,0.11837203986942768096923828125,3,0.02814712561666965484619140625,leaky_relu,normal
65,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 36 --learning_rate 0.07394634587783366353 --batch_size 2630 --hidden_size 6187 --dropout 0.3065226580947637558 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.69656501151621341705,,1,,n1720,18579843,65_0,FAILED,SOBOL,36,0.073946345877833663529088426003,2630,6187,0.30652265809476375579833984375,2,0.69656501151621341705322265625,leaky_relu,normal
66,1753194165,33,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 101 --learning_rate 0.02944625098584219974 --batch_size 390 --hidden_size 875 --dropout 0.47019830858334898949 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.28433792572468519211,,1,,n1720,18579867,66_0,FAILED,SOBOL,101,0.029446250985842199743292013636,390,875,0.470198308583348989486694335938,1,0.284337925724685192108154296875,leaky_relu,normal
67,1753194169,29,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 162 --learning_rate 0.09332615319788456487 --batch_size 3712 --hidden_size 4307 --dropout 0.15788358589634299278 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.99091989081352949142,,1,,n1720,18579869,67_0,FAILED,SOBOL,162,0.093326153197884564871600332481,3712,4307,0.157883585896342992782592773438,4,0.990919890813529491424560546875,leaky_relu,normal
68,1753194164,6,1753194170,1753194176,6,python3 .tests/mnist/train --epochs 195 --learning_rate 0.04456930601252243052 --batch_size 2490 --hidden_size 5274 --dropout 0.21155166160315275192 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.41238844674080610275,,1,,n1720,18579866,68_0,FAILED,SOBOL,195,0.044569306012522430515687688057,2490,5274,0.211551661603152751922607421875,3,0.412388446740806102752685546875,leaky_relu,normal
69,1753194168,30,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 68 --learning_rate 0.08288279199972749256 --batch_size 1723 --hidden_size 1856 --dropout 0.39889302756637334824 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86311303358525037766,,1,,n1720,18579868,69_0,FAILED,SOBOL,68,0.082882791999727492560090524876,1723,1856,0.398893027566373348236083984375,2,0.863113033585250377655029296875,leaky_relu,normal
70,1753194169,29,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.01343680607276037317 --batch_size 3468 --hidden_size 7283 --dropout 0.31340719433501362801 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15009609796106815338,,1,,n1720,18579870,70_0,FAILED,SOBOL,27,0.01343680607276037317077133082,3468,7283,0.313407194335013628005981445312,1,0.15009609796106815338134765625,leaky_relu,normal
71,1753194175,23,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 130 --learning_rate 0.05316490432266146593 --batch_size 657 --hidden_size 4064 --dropout 0.00022230343893170357 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57437142170965671539,,1,,n1720,18579874,71_0,FAILED,SOBOL,130,0.053164904322661465929655832952,657,4064,0.000222303438931703567504882812,4,0.57437142170965671539306640625,leaky_relu,normal
72,1753194175,23,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 142 --learning_rate 0.03655887942025438236 --batch_size 3132 --hidden_size 1540 --dropout 0.26462446525692939758 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.4488072982057929039,,1,,n1720,18579875,72_0,FAILED,SOBOL,142,0.036558879420254382364152689888,3132,1540,0.2646244652569293975830078125,4,0.448807298205792903900146484375,leaky_relu,normal
73,1753194184,50,1753194234,1753194240,6,python3 .tests/mnist/train --epochs 15 --learning_rate 0.09716450110208244006 --batch_size 832 --hidden_size 5718 --dropout 0.07634784281253814697 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77935381140559911728,,1,,n1720,18579882,73_0,FAILED,SOBOL,15,0.097164501102082440064933166468,832,5718,0.07634784281253814697265625,1,0.779353811405599117279052734375,leaky_relu,normal
74,1753194183,45,1753194228,1753194235,7,python3 .tests/mnist/train --epochs 80 --learning_rate 0.00583786064228042963 --batch_size 2058 --hidden_size 3357 --dropout 0.147173288743942976 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.23870756290853023529,,1,,n1720,18579881,74_0,FAILED,SOBOL,80,0.005837860642280429633588223481,2058,3357,0.147173288743942975997924804688,2,0.23870756290853023529052734375,leaky_relu,normal
75,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 183 --learning_rate 0.06698006724305451132 --batch_size 1802 --hidden_size 7862 --dropout 0.45936224563047289848 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.53316137753427028656,,1,,n1720,18579877,75_0,FAILED,SOBOL,183,0.066980067243054511316735499804,1802,7862,0.459362245630472898483276367188,3,0.53316137753427028656005859375,leaky_relu,normal
76,1753194183,45,1753194228,1753194235,7,python3 .tests/mnist/train --epochs 174 --learning_rate 0.02056776805287226922 --batch_size 211 --hidden_size 6894 --dropout 0.42132493574172258377 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11041096411645412445,,1,,n1720,18579880,76_0,FAILED,SOBOL,174,0.02056776805287226922436261134,211,6894,0.421324935741722583770751953125,4,0.11041096411645412445068359375,leaky_relu,normal
77,1753194184,44,1753194228,1753194235,7,python3 .tests/mnist/train --epochs 89 --learning_rate 0.05693613863997162156 --batch_size 4045 --hidden_size 2375 --dropout 0.23410170618444681168 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.66072603128850460052,,1,,n1720,18579883,77_0,FAILED,SOBOL,89,0.056936138639971621555613268129,4045,2375,0.234101706184446811676025390625,1,0.66072603128850460052490234375,leaky_relu,normal
78,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 48 --learning_rate 0.04055416330182925327 --batch_size 1270 --hidden_size 4622 --dropout 0.05384401464834809303 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.32710434403270483017,,1,,n1720,18579876,78_0,FAILED,SOBOL,48,0.040554163301829253274188857858,1270,4622,0.053844014648348093032836914062,2,0.327104344032704830169677734375,leaky_relu,normal
79,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 109 --learning_rate 0.07599573841299862853 --batch_size 3058 --hidden_size 431 --dropout 0.36714728036895394325 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90178966429084539413,,1,,n1720,18579878,79_0,FAILED,SOBOL,109,0.075995738412998628530381495239,3058,431,0.367147280368953943252563476562,3,0.901789664290845394134521484375,leaky_relu,normal
80,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 115 --learning_rate 0.04312895736005157438 --batch_size 1016 --hidden_size 7529 --dropout 0.18008241988718509674 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.73951292503625154495,,1,,n1720,18579879,80_0,FAILED,SOBOL,115,0.043128957360051574376758054541,1016,7529,0.18008241988718509674072265625,1,0.739512925036251544952392578125,leaky_relu,normal
81,1753194280,9,1753194289,1753194295,6,python3 .tests/mnist/train --epochs 54 --learning_rate 0.07954610445285216491 --batch_size 3316 --hidden_size 3791 --dropout 0.49285913817584514618 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.03207467962056398392,,1,,n1720,18579893,81_0,FAILED,SOBOL,54,0.079546104452852164912179944167,3316,3791,0.49285913817584514617919921875,4,0.032074679620563983917236328125,leaky_relu,normal
82,1753194411,28,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 83 --learning_rate 0.02413916819207370321 --batch_size 2002 --hidden_size 5509 --dropout 0.28141274815425276756 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.94797138497233390808,,1,,n1720,18579901,82_0,FAILED,SOBOL,83,0.024139168192073703206323997961,2002,5509,0.281412748154252767562866210938,3,0.9479713849723339080810546875,leaky_relu,normal
83,1753194420,19,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.05953196121519432199 --batch_size 2258 --hidden_size 1587 --dropout 0.09471606602892279625 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.28041001781821250916,,1,,n1720,18579904,83_0,FAILED,SOBOL,168,0.059531961215194321990207271256,2258,1587,0.094716066028922796249389648438,2,0.2804100178182125091552734375,leaky_relu,normal
84,1753194420,19,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 177 --learning_rate 0.0029735703218728305 --batch_size 3849 --hidden_size 636 --dropout 0.02533716242760419846 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82797744497656822205,,1,,n1720,18579903,84_0,FAILED,SOBOL,177,0.002973570321872830504728035805,3849,636,0.025337162427604198455810546875,1,0.8279774449765682220458984375,leaky_relu,normal
85,1753194424,15,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 74 --learning_rate 0.06353041587015614833 --batch_size 15 --hidden_size 4572 --dropout 0.33706060703843832016 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.40064857527613639832,,1,,n1720,18579905,85_0,FAILED,SOBOL,74,0.06353041587015614832800736167,15,4572,0.337060607038438320159912109375,4,0.4006485752761363983154296875,leaky_relu,normal
86,1753194427,12,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 21 --learning_rate 0.03308185798358172225 --batch_size 2878 --hidden_size 2713 --dropout 0.37669687392190098763 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.60950737167149782181,,1,,n1720,18579906,86_0,FAILED,SOBOL,21,0.033081857983581722248977996514,2878,2713,0.376696873921900987625122070312,3,0.609507371671497821807861328125,leaky_relu,normal
87,1753194431,8,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 148 --learning_rate 0.09427284704456107001 --batch_size 1090 --hidden_size 6464 --dropout 0.1888857637532055378 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.16183656919747591019,,1,,n1720,18579913,87_0,FAILED,SOBOL,148,0.094272847044561070006807312893,1090,6464,0.188885763753205537796020507812,2,0.161836569197475910186767578125,leaky_relu,normal
88,1753194437,32,1753194469,1753194475,6,python3 .tests/mnist/train --epochs 136 --learning_rate 0.01717896947804838439 --batch_size 2700 --hidden_size 4895 --dropout 0.45279200002551078796 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78321972489356994629,,1,,n1720,18579917,88_0,FAILED,SOBOL,136,0.017178969478048384394996972446,2700,4895,0.4527920000255107879638671875,2,0.7832197248935699462890625,leaky_relu,normal
89,1753194436,38,1753194474,1753194480,6,python3 .tests/mnist/train --epochs 33 --learning_rate 0.05554123197095468811 --batch_size 1422 --hidden_size 185 --dropout 0.14013341814279556274 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.4918158799409866333,,1,,n1720,18579916,89_0,FAILED,SOBOL,33,0.055541231970954688113017994056,1422,185,0.140133418142795562744140625,3,0.49181587994098663330078125,leaky_relu,normal
90,1753194438,36,1753194474,1753194480,6,python3 .tests/mnist/train --epochs 62 --learning_rate 0.04697333680465817785 --batch_size 3766 --hidden_size 7164 --dropout 0.08583682356402277946 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.52929581049829721451,,1,,n1720,18579918,90_0,FAILED,SOBOL,62,0.046973336804658177845439581688,3766,7164,0.085836823564022779464721679688,4,0.529295810498297214508056640625,leaky_relu,normal
91,1753194438,31,1753194469,1753194475,6,python3 .tests/mnist/train --epochs 189 --learning_rate 0.08665265296651050719 --batch_size 444 --hidden_size 2141 --dropout 0.27265188051387667656 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.19569956604391336441,,1,,n1720,18579920,91_0,FAILED,SOBOL,189,0.086652652966510507193120815828,444,2141,0.272651880513876676559448242188,1,0.195699566043913364410400390625,leaky_relu,normal
92,1753194439,30,1753194469,1753194475,6,python3 .tests/mnist/train --epochs 156 --learning_rate 0.02618877211213111941 --batch_size 1666 --hidden_size 3091 --dropout 0.35766146052628755569 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.64904754702001810074,,1,,n1720,18579921,92_0,FAILED,SOBOL,156,0.026188772112131119412792301659,1666,3091,0.357661460526287555694580078125,2,0.649047547020018100738525390625,leaky_relu,normal
93,1753194438,33,1753194471,1753194477,6,python3 .tests/mnist/train --epochs 95 --learning_rate 0.09026378351030871217 --batch_size 2433 --hidden_size 8100 --dropout 0.04581201169639825821 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07521493081003427505,,1,,n1720,18579919,93_0,FAILED,SOBOL,95,0.090263783510308712165759459367,2433,8100,0.045812011696398258209228515625,3,0.075214930810034275054931640625,leaky_relu,normal
94,1753194539,20,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 42 --learning_rate 0.00673872546274215025 --batch_size 584 --hidden_size 1263 --dropout 0.24067642027512192726 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.91346754133701324463,,1,,n1720,18579977,94_0,FAILED,SOBOL,42,0.00673872546274215025036147253,584,1263,0.240676420275121927261352539062,4,0.91346754133701324462890625,leaky_relu,normal
95,1753194546,13,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 127 --learning_rate 0.07066741013498976931 --batch_size 3395 --hidden_size 5960 --dropout 0.42836176464334130287 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.36230000853538513184,,1,,n1720,18579978,95_0,FAILED,SOBOL,127,0.070667410134989769310287499593,3395,5960,0.428361764643341302871704101562,1,0.3623000085353851318359375,leaky_relu,normal
96,1753194552,7,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 124 --learning_rate 0.03017551072221249381 --batch_size 2145 --hidden_size 6641 --dropout 0.01051074592396616936 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96265801507979631424,,1,,n1720,18579979,96_0,FAILED,SOBOL,124,0.030175510722212493808225275416,2145,6641,0.010510745923966169357299804688,1,0.962658015079796314239501953125,leaky_relu,normal
97,1753194554,5,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 44 --learning_rate 0.09093353886464611291 --batch_size 1889 --hidden_size 2633 --dropout 0.32234481675550341606 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.26206128019839525223,,1,,n1720,18579980,97_0,FAILED,SOBOL,44,0.090933538864646112909184694217,1889,2633,0.322344816755503416061401367188,4,0.262061280198395252227783203125,leaky_relu,normal
98,1753194638,11,1753194649,1753194655,6,python3 .tests/mnist/train --epochs 99 --learning_rate 0.01211761482991278137 --batch_size 3171 --hidden_size 4364 --dropout 0.39312164857983589172 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.72482644394040107727,,1,,n1720,18580025,98_0,FAILED,SOBOL,99,0.012117614829912781368448371211,3171,4364,0.3931216485798358917236328125,3,0.7248264439404010772705078125,leaky_relu,normal
99,1753194639,10,1753194649,1753194655,6,python3 .tests/mnist/train --epochs 154 --learning_rate 0.07311952680340037813 --batch_size 871 --hidden_size 685 --dropout 0.20542116463184356689 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.05042326822876930237,,1,,n1720,18580026,99_0,FAILED,SOBOL,154,0.073119526803400378134334403057,871,685,0.20542116463184356689453125,2,0.0504232682287693023681640625,leaky_relu,normal
100,1753197683,30,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 193 --learning_rate 0.01416778107844293179 --batch_size 1199 --hidden_size 1794 --dropout 0.16731713199988007545 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.59701806679368019104,,1,,n1720,18580659,100_0,FAILED,SOBOL,193,0.014167781078442931788630154699,1199,1794,0.167317131999880075454711914062,1,0.5970180667936801910400390625,leaky_relu,normal
101,1753197686,27,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 60 --learning_rate 0.05077400377010927307 --batch_size 2988 --hidden_size 5460 --dropout 0.47999085346236824989 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.17847626283764839172,,1,,n1720,18580662,101_0,FAILED,SOBOL,60,0.050774003770109273070421096463,2988,5460,0.479990853462368249893188476562,4,0.1784762628376483917236328125,leaky_relu,normal
102,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 29 --learning_rate 0.04686264722701162511 --batch_size 157 --hidden_size 3615 --dropout 0.29989626724272966385 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.8404668392613530159,,1,,n1720,18580656,102_0,FAILED,SOBOL,29,0.046862647227011625106207759472,157,3615,0.299896267242729663848876953125,3,0.840466839261353015899658203125,leaky_relu,normal
103,1753197690,53,1753197743,1753197749,6,python3 .tests/mnist/train --epochs 138 --learning_rate 0.08205425914460794112 --batch_size 3990 --hidden_size 7608 --dropout 0.11309658829122781754 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38400879222899675369,,1,,n1720,18580668,103_0,FAILED,SOBOL,138,0.082054259144607941123261696248,3990,7608,0.113096588291227817535400390625,2,0.384008792228996753692626953125,leaky_relu,normal
104,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 150 --learning_rate 0.00345010499823838459 --batch_size 301 --hidden_size 6040 --dropout 0.37211761390790343285 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.51418208330869674683,,1,,n1720,18580654,104_0,FAILED,SOBOL,150,0.003450104998238384592518235294,301,6040,0.372117613907903432846069335938,2,0.514182083308696746826171875,leaky_relu,normal
105,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 17 --learning_rate 0.06771418604077772407 --batch_size 3624 --hidden_size 1087 --dropout 0.06040930887684226036 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21398711949586868286,,1,,n1720,18580653,105_0,FAILED,SOBOL,17,0.067714186040777724073791432602,3624,1087,0.060409308876842260360717773438,3,0.213987119495868682861328125,leaky_relu,normal
106,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 72 --learning_rate 0.03572720128446817828 --batch_size 1312 --hidden_size 8052 --dropout 0.22388185746967792511 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.79833360109478235245,,1,,n1720,18580664,106_0,FAILED,SOBOL,72,0.035727201284468178277275995924,1312,8052,0.22388185746967792510986328125,4,0.798333601094782352447509765625,leaky_relu,normal
107,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 181 --learning_rate 0.09945469889668748231 --batch_size 2589 --hidden_size 3299 --dropout 0.41170834563672542572 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.47352817747741937637,,1,,n1720,18580665,107_0,FAILED,SOBOL,181,0.09945469889668748231237316304,2589,3299,0.41170834563672542572021484375,1,0.473528177477419376373291015625,leaky_relu,normal
108,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 165 --learning_rate 0.03816469164416194659 --batch_size 3541 --hidden_size 2190 --dropout 0.46543164225295186043 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92589590046554803848,,1,,n1720,18580655,108_0,FAILED,SOBOL,165,0.038164691644161946593172274333,3541,2190,0.465431642252951860427856445312,2,0.925895900465548038482666015625,leaky_relu,normal
109,1753197690,23,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 87 --learning_rate 0.07672814268572256124 --batch_size 730 --hidden_size 6956 --dropout 0.15263954596593976021 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.34523297939449548721,,1,,n1720,18580663,109_0,FAILED,SOBOL,87,0.076728142685722561244787698342,730,6956,0.152639545965939760208129882812,3,0.345232979394495487213134765625,leaky_relu,normal
110,1753197681,32,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 56 --learning_rate 0.01973780593071132808 --batch_size 2547 --hidden_size 105 --dropout 0.067227180115878582 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63661927729845046997,,1,,n1720,18580652,110_0,FAILED,SOBOL,56,0.019737805930711328078475119696,2547,105,0.067227180115878582000732421875,4,0.636619277298450469970703125,leaky_relu,normal
111,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 112 --learning_rate 0.05922805095957592303 --batch_size 1780 --hidden_size 5072 --dropout 0.2539087226614356041 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.09228187054395675659,,1,,n1720,18580669,111_0,FAILED,SOBOL,112,0.059228050959575923029021282673,1780,5072,0.253908722661435604095458984375,1,0.092281870543956756591796875,leaky_relu,normal
112,1753197690,53,1753197743,1753197749,6,python3 .tests/mnist/train --epochs 106 --learning_rate 0.02340971753941848907 --batch_size 3823 --hidden_size 3857 --dropout 0.19880044041201472282 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.29719346947968006134,,1,,n1720,18580666,112_0,FAILED,SOBOL,106,0.023409717539418489068436812772,3823,3857,0.198800440412014722824096679688,3,0.29719346947968006134033203125,leaky_relu,normal
113,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 50 --learning_rate 0.06192438612077385413 --batch_size 500 --hidden_size 7331 --dropout 0.38600829197093844414 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.97440223582088947296,,1,,n1720,18580667,113_0,FAILED,SOBOL,50,0.061924386120773854125243218505,500,7331,0.386008291970938444137573242188,2,0.97440223582088947296142578125,leaky_relu,normal
114,1753197681,32,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 93 --learning_rate 0.04083409179253504051 --batch_size 2772 --hidden_size 2032 --dropout 0.3319071643054485321 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.0152916712686419487,,1,,n1720,18580651,114_0,FAILED,SOBOL,93,0.040834091792535040510436772365,2772,2032,0.3319071643054485321044921875,1,0.015291671268641948699951171875,leaky_relu,normal
115,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.08037311295494438401 --batch_size 1495 --hidden_size 5195 --dropout 0.01858875900506973267 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71308257710188627243,,1,,n1720,18580657,115_0,FAILED,SOBOL,171,0.080373112954944384012101465942,1495,5195,0.018588759005069732666015625,4,0.713082577101886272430419921875,leaky_relu,normal
116,1753197987,26,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 187 --learning_rate 0.03235107389418408891 --batch_size 543 --hidden_size 4130 --dropout 0.10353155666962265968 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.13553162943571805954,,1,,n1720,18580737,116_0,FAILED,SOBOL,187,0.032351073894184088908243523974,543,4130,0.103531556669622659683227539062,3,0.135531629435718059539794921875,leaky_relu,normal
117,1753197991,22,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 78 --learning_rate 0.09666393702477217575 --batch_size 3354 --hidden_size 954 --dropout 0.29182331869378685951 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.59308628272265195847,,1,,n1720,18580739,117_0,FAILED,SOBOL,78,0.096663937024772175754527836489,3354,954,0.291823318693786859512329101562,2,0.593086282722651958465576171875,leaky_relu,normal
118,1753197992,21,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 11 --learning_rate 0.00068003819109871985 --batch_size 1577 --hidden_size 6394 --dropout 0.48660663235932588577 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.42695306427776813507,,1,,n1720,18580740,118_0,FAILED,SOBOL,11,0.000680038191098719852802079178,1577,6394,0.486606632359325885772705078125,1,0.42695306427776813507080078125,leaky_relu,normal
119,1753197993,20,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 144 --learning_rate 0.06435875929761677994 --batch_size 2344 --hidden_size 2906 --dropout 0.17443305347114801407 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.84439802356064319611,,1,,n1720,18580741,119_0,FAILED,SOBOL,144,0.064358759297616779937456499283,2344,2906,0.174433053471148014068603515625,4,0.84439802356064319610595703125,leaky_relu,normal
120,1753197990,23,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 132 --learning_rate 0.04936128410929814525 --batch_size 1947 --hidden_size 382 --dropout 0.43395003443583846092 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.22566900309175252914,,1,,n1720,18580738,120_0,FAILED,SOBOL,132,0.049361284109298145250654954452,1947,382,0.433950034435838460922241210938,4,0.225669003091752529144287109375,leaky_relu,normal
121,1753197996,17,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 23 --learning_rate 0.08591872434075922826 --batch_size 2203 --hidden_size 4830 --dropout 0.24662380805239081383 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.54937376733869314194,,1,,n1720,18580742,121_0,FAILED,SOBOL,23,0.085918724340759228264019498056,2203,4830,0.246623808052390813827514648438,1,0.549373767338693141937255859375,leaky_relu,normal
122,1753197999,14,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 66 --learning_rate 0.01801045595323666829 --batch_size 945 --hidden_size 2455 --dropout 0.03521839715540409088 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.46184594742953777313,,1,,n1720,18580743,122_0,FAILED,SOBOL,66,0.018010455953236668286132626804,945,2455,0.03521839715540409088134765625,2,0.46184594742953777313232421875,leaky_relu,normal
123,1753198002,11,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 199 --learning_rate 0.05325084400437772592 --batch_size 3245 --hidden_size 6718 --dropout 0.3484186660498380661 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.76314133219420909882,,1,,n1720,18580744,123_0,FAILED,SOBOL,199,0.053250844004377725915411190272,3245,6718,0.34841866604983806610107421875,3,0.76314133219420909881591796875,leaky_relu,normal
124,1753198002,11,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 160 --learning_rate 0.0091280054598115376 --batch_size 2917 --hidden_size 7783 --dropout 0.27909516217187047005 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.34136378578841686249,,1,,n1720,18580746,124_0,FAILED,SOBOL,160,0.009128005459811537602998754437,2917,7783,0.279095162171870470046997070312,4,0.34136378578841686248779296875,leaky_relu,normal
125,1753198003,10,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 104 --learning_rate 0.06993481569029391665 --batch_size 1128 --hidden_size 3533 --dropout 0.09092916594818234444 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.88289154879748821259,,1,,n1720,18580747,125_0,FAILED,SOBOL,104,0.069934815690293916645714489277,1128,3533,0.090929165948182344436645507812,1,0.88289154879748821258544921875,leaky_relu,normal
126,1753198003,40,1753198043,1753198049,6,python3 .tests/mnist/train --epochs 38 --learning_rate 0.02701892589488998075 --batch_size 3935 --hidden_size 5766 --dropout 0.13039469998329877853 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.09615167137235403061,,1,,n1720,18580748,126_0,FAILED,SOBOL,38,0.027018925894889980754420832909,3935,5766,0.130394699983298778533935546875,2,0.096151671372354030609130859375,leaky_relu,normal
127,1753198097,37,1753198134,1753198140,6,python3 .tests/mnist/train --epochs 118 --learning_rate 0.0879720613626763237 --batch_size 102 --hidden_size 1333 --dropout 0.44269428309053182602 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.6796239977702498436,,1,,n1720,18580762,127_0,FAILED,SOBOL,118,0.087972061362676323703624348127,102,1333,0.442694283090531826019287109375,3,0.679623997770249843597412109375,leaky_relu,normal
128,1753198136,32,1753198168,1753198174,6,python3 .tests/mnist/train --epochs 118 --learning_rate 0.021333446187060328 --batch_size 2851 --hidden_size 5134 --dropout 0.15841000806540250778 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45364432875066995621,,1,,n1720,18580770,128_0,FAILED,SOBOL,118,0.021333446187060327997597752869,2851,5134,0.158410008065402507781982421875,1,0.453644328750669956207275390625,leaky_relu,normal
129,1753198153,10,1753198163,1753198169,6,python3 .tests/mnist/train --epochs 39 --learning_rate 0.05775597819834948216 --batch_size 1062 --hidden_size 1965 --dropout 0.47156402375549077988 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75495500210672616959,,1,,n1720,18580789,129_0,FAILED,SOBOL,39,0.05775597819834948215556025275,1062,1965,0.471564023755490779876708984375,4,0.754955002106726169586181640625,leaky_relu,normal
130,1753198160,38,1753198198,1753198204,6,python3 .tests/mnist/train --epochs 104 --learning_rate 0.03978310229601338815 --batch_size 3869 --hidden_size 7405 --dropout 0.30711014242842793465 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.2338400036096572876,,1,,n1720,18580791,130_0,FAILED,SOBOL,104,0.039783102296013388154971579524,3869,7405,0.307110142428427934646606445312,3,0.23384000360965728759765625,leaky_relu,normal
131,1753198159,34,1753198193,1753198199,6,python3 .tests/mnist/train --epochs 159 --learning_rate 0.07518128172624856387 --batch_size 36 --hidden_size 3909 --dropout 0.11979869799688458443 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.55752965807914733887,,1,,n1720,18580790,131_0,FAILED,SOBOL,159,0.075181281726248563868075791561,36,3909,0.119798697996884584426879882812,2,0.5575296580791473388671875,leaky_relu,normal
132,1753198322,21,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 198 --learning_rate 0.03735490096257999826 --batch_size 2010 --hidden_size 2846 --dropout 0.00354100950062274933 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10359027981758117676,,1,,n1720,18580888,132_0,FAILED,SOBOL,198,0.037354900962579998258128455291,2010,2846,0.00354100950062274932861328125,1,0.1035902798175811767578125,leaky_relu,normal
133,1753198320,28,1753198348,1753198354,6,python3 .tests/mnist/train --epochs 65 --learning_rate 0.09790483686719089751 --batch_size 2265 --hidden_size 6328 --dropout 0.31588684581220149994 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68704743683338165283,,1,,n1720,18580887,133_0,FAILED,SOBOL,65,0.097904836867190897509161118251,2265,6328,0.31588684581220149993896484375,4,0.68704743683338165283203125,leaky_relu,normal
134,1753198333,10,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 24 --learning_rate 0.00504874632460996543 --batch_size 1007 --hidden_size 1029 --dropout 0.40227291500195860863 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.33389449957758188248,,1,,n1720,18580890,134_0,FAILED,SOBOL,24,0.005048746324609965432927971563,1007,1029,0.402272915001958608627319335938,3,0.333894499577581882476806640625,leaky_relu,normal
135,1753198334,9,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 133 --learning_rate 0.06623282425329089784 --batch_size 3308 --hidden_size 4184 --dropout 0.21409213682636618614 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.87543772999197244644,,1,,n1720,18580892,135_0,FAILED,SOBOL,133,0.066232824253290897842383344596,3308,4184,0.214092136826366186141967773438,2,0.875437729991972446441650390625,leaky_relu,normal
136,1753198331,12,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 145 --learning_rate 0.04534093790641054861 --batch_size 609 --hidden_size 6772 --dropout 0.45895781833678483963 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.00762405619025230408,,1,,n1720,18580889,136_0,FAILED,SOBOL,145,0.045340937906410548607905042218,609,6772,0.458957818336784839630126953125,2,0.0076240561902523040771484375,leaky_relu,normal
137,1753198336,7,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 12 --learning_rate 0.08369629671014845729 --batch_size 3420 --hidden_size 2530 --dropout 0.14568566624075174332 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.70539985224604606628,,1,,n1720,18580894,137_0,FAILED,SOBOL,12,0.083696296710148457287381518199,3420,2530,0.145685666240751743316650390625,3,0.7053998522460460662841796875,leaky_relu,normal
138,1753198335,8,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 77 --learning_rate 0.01267208140352740937 --batch_size 1643 --hidden_size 4763 --dropout 0.07588253403082489967 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.30489151645451784134,,1,,n1720,18580893,138_0,FAILED,SOBOL,77,0.012672081403527409373954704108,1643,4763,0.075882534030824899673461914062,4,0.304891516454517841339111328125,leaky_relu,normal
139,1753198337,11,1753198348,1753198354,6,python3 .tests/mnist/train --epochs 186 --learning_rate 0.05234449238758534517 --batch_size 2410 --hidden_size 322 --dropout 0.26307560363784432411 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.98211557138711214066,,1,,n1720,18580896,139_0,FAILED,SOBOL,186,0.052344492387585345172240636202,2410,322,0.263075603637844324111938476562,1,0.982115571387112140655517578125,leaky_relu,normal
140,1753198468,26,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.01061262612873688227 --batch_size 3760 --hidden_size 1386 --dropout 0.36370639875531196594 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43489516247063875198,,1,,n1720,18580966,140_0,FAILED,SOBOL,171,0.010612626128736882269443242421,3760,1386,0.3637063987553119659423828125,2,0.434895162470638751983642578125,leaky_relu,normal
141,1753198467,29,1753198496,1753198502,6,python3 .tests/mnist/train --epochs 92 --learning_rate 0.07469301649089903072 --batch_size 438 --hidden_size 5841 --dropout 0.05148656666278839111 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.85235558915883302689,,1,,n1720,18580965,141_0,FAILED,SOBOL,92,0.074693016490899030723760176897,438,5841,0.05148656666278839111328125,3,0.852355589158833026885986328125,leaky_relu,normal
142,1753198480,14,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 51 --learning_rate 0.02865080033158883335 --batch_size 2710 --hidden_size 3466 --dropout 0.23059982387349009514 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.12761990353465080261,,1,,n1720,18581000,142_0,FAILED,SOBOL,51,0.028650800331588833352869372106,2710,3466,0.230599823873490095138549804688,4,0.1276199035346508026123046875,leaky_relu,normal
143,1753198481,13,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 106 --learning_rate 0.09258486545644700749 --batch_size 1432 --hidden_size 7721 --dropout 0.41890636784955859184 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.58515938743948936462,,1,,n1720,18581001,143_0,FAILED,SOBOL,106,0.092584865456447007492357670344,1432,7721,0.418906367849558591842651367188,1,0.5851593874394893646240234375,leaky_relu,normal
144,1753198487,7,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 112 --learning_rate 0.02536912309788167535 --batch_size 3475 --hidden_size 751 --dropout 0.09707343857735395432 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.80575696192681789398,,1,,n1720,18581002,144_0,FAILED,SOBOL,112,0.025369123097881675354958730395,3475,751,0.097073438577353954315185546875,3,0.80575696192681789398193359375,leaky_relu,normal
145,1753198500,22,1753198522,1753198529,7,python3 .tests/mnist/train --epochs 57 --learning_rate 0.08949829592024907687 --batch_size 664 --hidden_size 4425 --dropout 0.2848536735400557518 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.48096688650548458099,,1,,n1720,18581023,145_0,FAILED,SOBOL,57,0.089498295920249076873531635101,664,4425,0.284853673540055751800537109375,2,0.48096688650548458099365234375,leaky_relu,normal
146,1753198502,20,1753198522,1753198529,7,python3 .tests/mnist/train --epochs 86 --learning_rate 0.00755299160536378709 --batch_size 2481 --hidden_size 2579 --dropout 0.49527775170281529427 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.5067280670627951622,,1,,n1720,18581024,146_0,FAILED,SOBOL,86,0.007552991605363787094851169002,2481,2579,0.495277751702815294265747070312,1,0.506728067062795162200927734375,leaky_relu,normal
147,1753198606,8,1753198614,1753198620,6,python3 .tests/mnist/train --epochs 165 --learning_rate 0.07143828059667721442 --batch_size 1714 --hidden_size 6565 --dropout 0.18358422862365841866 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.2065180530771613121,,1,,n1719,18581073,147_0,FAILED,SOBOL,165,0.071438280596677214417944412617,1714,6565,0.183584228623658418655395507812,4,0.206518053077161312103271484375,leaky_relu,normal
148,1753198655,19,1753198674,1753198680,6,python3 .tests/mnist/train --epochs 180 --learning_rate 0.0164384431688115 --batch_size 364 --hidden_size 7676 --dropout 0.1903734598308801651 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.62843292858451604843,,1,,n1720,18581100,148_0,FAILED,SOBOL,180,0.016438443168811500000314751446,364,7676,0.19037345983088016510009765625,3,0.628432928584516048431396484375,leaky_relu,normal
149,1753198672,31,1753198703,1753198709,6,python3 .tests/mnist/train --epochs 71 --learning_rate 0.05474501988450065915 --batch_size 3686 --hidden_size 3676 --dropout 0.37710125558078289032 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.08408029284328222275,,1,,n1720,18581129,149_0,FAILED,SOBOL,71,0.05474501988450065914637576725,3686,3676,0.37710125558078289031982421875,2,0.084080292843282222747802734375,leaky_relu,normal
150,1753202113,44,1753202157,1753202170,13,python3 .tests/mnist/train --epochs 18 --learning_rate 0.04772077033855021133 --batch_size 1374 --hidden_size 5408 --dropout 0.3386094248853623867 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93405165337026119232,,1,,n1720,18582227,150_0,FAILED,SOBOL,18,0.047720770338550211331352102206,1374,5408,0.338609424885362386703491210938,1,0.93405165337026119232177734375,leaky_relu,normal
151,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 151 --learning_rate 0.08744195782830939401 --batch_size 2652 --hidden_size 1720 --dropout 0.02580254664644598961 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.35340414009988307953,,1,,n1720,18582229,151_0,FAILED,SOBOL,151,0.087441957828309394007426647022,2652,1720,0.025802546646445989608764648438,4,0.35340414009988307952880859375,leaky_relu,normal
152,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 139 --learning_rate 0.0021598750673234462 --batch_size 1265 --hidden_size 3225 --dropout 0.27017227280884981155 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.73278379719704389572,,1,,n1720,18582216,152_0,FAILED,SOBOL,139,0.002159875067323446199557546166,1265,3225,0.270172272808849811553955078125,4,0.732783797197043895721435546875,leaky_relu,normal
153,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 30 --learning_rate 0.06275859343213960329 --batch_size 3054 --hidden_size 8000 --dropout 0.08251804206520318985 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.05836557131260633469,,1,,n1720,18582225,153_0,FAILED,SOBOL,30,0.062758593432139603285335738292,3054,8000,0.082518042065203189849853515625,1,0.058365571312606334686279296875,leaky_relu,normal
154,1753202106,22,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 59 --learning_rate 0.03390246046278626302 --batch_size 223 --hidden_size 1148 --dropout 0.1375928693450987339 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.95473102666437625885,,1,,n1720,18582221,154_0,FAILED,SOBOL,59,0.033902460462786263017953558574,223,1148,0.137592869345098733901977539062,2,0.95473102666437625885009765625,leaky_relu,normal
155,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 192 --learning_rate 0.09503776225792244514 --batch_size 4056 --hidden_size 6107 --dropout 0.44941215822473168373 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25414963997900485992,,1,,n1720,18582215,155_0,FAILED,SOBOL,192,0.095037762257922445141566925031,4056,6107,0.449412158224731683731079101562,3,0.25414963997900485992431640625,leaky_relu,normal
156,1753202113,15,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 153 --learning_rate 0.04238247729111463413 --batch_size 2082 --hidden_size 4997 --dropout 0.42699600383639335632 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.83278396166861057281,,1,,n1720,18582224,156_0,FAILED,SOBOL,153,0.042382477291114634132540572864,2082,4997,0.4269960038363933563232421875,4,0.83278396166861057281494140625,leaky_relu,normal
157,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 98 --learning_rate 0.07875622721435503182 --batch_size 1827 --hidden_size 52 --dropout 0.24015007168054580688 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.37634132243692874908,,1,,n1720,18582218,157_0,FAILED,SOBOL,98,0.078756227214355031818193708659,1827,52,0.240150071680545806884765625,1,0.37634132243692874908447265625,leaky_relu,normal
158,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 45 --learning_rate 0.02488026538938284057 --batch_size 3109 --hidden_size 7017 --dropout 0.04438542900606989861 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60473136883229017258,,1,,n1720,18582230,158_0,FAILED,SOBOL,45,0.024880265389382840574006294787,3109,7017,0.044385429006069898605346679688,2,0.604731368832290172576904296875,leaky_relu,normal
159,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 124 --learning_rate 0.0603272213253192649 --batch_size 808 --hidden_size 2256 --dropout 0.35707393242046236992 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.18617433588951826096,,1,,n1720,18582219,159_0,FAILED,SOBOL,124,0.060327221325319264899622595522,808,2256,0.357073932420462369918823242188,3,0.186174335889518260955810546875,leaky_relu,normal
160,1753202113,15,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 127 --learning_rate 0.0389547594267874997 --batch_size 1605 --hidden_size 1639 --dropout 0.20484892511740326881 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.52109432034194469452,,1,,n1720,18582223,160_0,FAILED,SOBOL,127,0.038954759426787499698718875152,1605,1639,0.204848925117403268814086914062,3,0.52109432034194469451904296875,leaky_relu,normal
161,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 41 --learning_rate 0.07747481329878792844 --batch_size 2371 --hidden_size 5583 --dropout 0.39167971769347786903 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.18751312606036663055,,1,,n1720,18582217,161_0,FAILED,SOBOL,41,0.077474813298787928439459449237,2371,5583,0.391679717693477869033813476562,2,0.18751312606036663055419921875,leaky_relu,normal
162,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 96 --learning_rate 0.01894235527645796516 --batch_size 522 --hidden_size 3724 --dropout 0.32183369714766740799 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.79139085765928030014,,1,,n1720,18582226,162_0,FAILED,SOBOL,96,0.01894235527645796515749943012,522,3724,0.321833697147667407989501953125,1,0.791390857659280300140380859375,leaky_relu,normal
163,1753202106,22,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 157 --learning_rate 0.05848676321813837259 --batch_size 3334 --hidden_size 7468 --dropout 0.00912981573492288589 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.49997166451066732407,,1,,n1720,18582220,163_0,FAILED,SOBOL,157,0.058486763218138372588672524444,3334,7468,0.009129815734922885894775390625,4,0.499971664510667324066162109375,leaky_relu,normal
164,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 190 --learning_rate 0.00422173689212650138 --batch_size 2765 --hidden_size 6518 --dropout 0.10970139829441905022 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.92090628203004598618,,1,,n1720,18582228,164_0,FAILED,SOBOL,190,0.004221736892126501383692982472,2765,6518,0.109701398294419050216674804688,3,0.920906282030045986175537109375,leaky_relu,normal
165,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 63 --learning_rate 0.0685276907511986888 --batch_size 1487 --hidden_size 2788 --dropout 0.2973710070364177227 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.36972334142774343491,,1,,n1720,18582222,165_0,FAILED,SOBOL,63,0.068527690751198688801082425925,1487,2788,0.297371007036417722702026367188,2,0.369723341427743434906005859375,leaky_relu,normal
166,1753202486,1129,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 32 --learning_rate 0.03496247661523521622 --batch_size 3831 --hidden_size 4506 --dropout 0.47665690258145332336 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.64157838933169841766,,1,,n1720,18582388,166_0,FAILED,SOBOL,32,0.03496247661523521621518284519,3831,4506,0.4766569025814533233642578125,1,0.64157838933169841766357421875,leaky_relu,normal
167,1753202486,1129,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 135 --learning_rate 0.09863428696161136155 --batch_size 509 --hidden_size 576 --dropout 0.16485275328159332275 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.06776100210845470428,,1,,n1720,18582389,167_0,FAILED,SOBOL,135,0.098634286961611361554957966291,509,576,0.16485275328159332275390625,4,0.06776100210845470428466796875,leaky_relu,normal
168,1753202489,1126,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 147 --learning_rate 0.01496380262076854768 --batch_size 3910 --hidden_size 2080 --dropout 0.41215838165953755379 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.94030388724058866501,,1,,n1720,18582391,168_0,FAILED,SOBOL,147,0.014963802620768547682605920102,3910,2080,0.412158381659537553787231445312,4,0.940303887240588665008544921875,leaky_relu,normal
169,1753202487,1128,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 20 --learning_rate 0.05151433953521773745 --batch_size 77 --hidden_size 7097 --dropout 0.22544596390798687935 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.272727171890437603,,1,,n1720,18582390,169_0,FAILED,SOBOL,20,0.051514339535217737453542952153,77,7097,0.225445963907986879348754882812,1,0.272727171890437602996826171875,leaky_relu,normal
170,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 75 --learning_rate 0.0460735329093411583 --batch_size 2940 --hidden_size 260 --dropout 0.06079852115362882614 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.74721108563244342804,,1,,n1720,18582393,170_0,FAILED,SOBOL,75,0.046073532909341158303462293588,2940,260,0.060798521153628826141357421875,2,0.74721108563244342803955078125,leaky_relu,normal
171,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 178 --learning_rate 0.08130701615484431377 --batch_size 1151 --hidden_size 4949 --dropout 0.37362053897231817245 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.03978789038956165314,,1,,n1720,18582394,171_0,FAILED,SOBOL,178,0.081307016154844313771121733225,1151,4949,0.373620538972318172454833984375,3,0.03978789038956165313720703125,leaky_relu,normal
172,1753202485,1129,1753203614,1753203620,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.03094118885640054911 --batch_size 951 --hidden_size 5899 --dropout 0.25742581998929381371 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.61744958348572254181,,1,,n1720,18582386,172_0,FAILED,SOBOL,168,0.030941188856400549112013464992,951,5899,0.257425819989293813705444335938,4,0.61744958348572254180908203125,leaky_relu,normal
173,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 84 --learning_rate 0.09175337842302397351 --batch_size 3251 --hidden_size 1196 --dropout 0.069630445446819067 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.16979400999844074249,,1,,n1720,18582392,173_0,FAILED,SOBOL,84,0.091753378423023973509131678838,3251,1196,0.069630445446819067001342773438,1,0.16979400999844074249267578125,leaky_relu,normal
174,1753202486,1129,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 53 --learning_rate 0.01134655382409691798 --batch_size 1937 --hidden_size 8175 --dropout 0.15609570033848285675 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.82006583642214536667,,1,,n1720,18582387,174_0,FAILED,SOBOL,53,0.011346553824096917983954568854,1937,8175,0.15609570033848285675048828125,2,0.820065836422145366668701171875,leaky_relu,normal
175,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 115 --learning_rate 0.07230507011665031347 --batch_size 2193 --hidden_size 3144 --dropout 0.46777384541928768158 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39272155892103910446,,1,,n1720,18582395,175_0,FAILED,SOBOL,115,0.07230507011665031347202869938,2193,3144,0.46777384541928768157958984375,3,0.392721558921039104461669921875,leaky_relu,normal
176,1753202492,1123,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 109 --learning_rate 0.00838152539087459389 --batch_size 150 --hidden_size 4231 --dropout 0.01618542009964585304 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24613103363662958145,,1,,n1720,18582396,176_0,FAILED,SOBOL,109,0.008381525390874593889334320806,150,4231,0.016185420099645853042602539062,1,0.246131033636629581451416015625,leaky_relu,normal
177,1753202495,1120,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 47 --learning_rate 0.06914493845179676967 --batch_size 3983 --hidden_size 821 --dropout 0.32839011261239647865 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.54059995803982019424,,1,,n1720,18582401,177_0,FAILED,SOBOL,47,0.069144938451796769673940445955,3983,821,0.328390112612396478652954101562,4,0.540599958039820194244384765625,leaky_relu,normal
178,1753202493,1122,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 90 --learning_rate 0.02776002309219911812 --batch_size 1208 --hidden_size 6248 --dropout 0.38366613257676362991 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.44135338813066482544,,1,,n1720,18582397,178_0,FAILED,SOBOL,90,0.027760023092199118122103129735,1208,6248,0.383666132576763629913330078125,3,0.441353388130664825439453125,leaky_relu,normal
179,1753202494,1121,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 174 --learning_rate 0.08876732147280126661 --batch_size 2997 --hidden_size 3021 --dropout 0.19534421060234308243 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.77188461273908615112,,1,,n1720,18582399,179_0,FAILED,SOBOL,174,0.088767321472801266613039672393,2997,3021,0.195344210602343082427978515625,2,0.771884612739086151123046875,leaky_relu,normal
180,1753202495,1120,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 184 --learning_rate 0.04854758885474876051 --batch_size 3197 --hidden_size 3990 --dropout 0.17286902246996760368 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31891810148954391479,,1,,n1720,18582400,180_0,FAILED,SOBOL,184,0.048547588854748760511803595818,3197,3990,0.172869022469967603683471679688,1,0.318918101489543914794921875,leaky_relu,normal
181,1753202675,940,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 81 --learning_rate 0.08514690190274268322 --batch_size 897 --hidden_size 7230 --dropout 0.48615655256435275078 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89358795434236526489,,1,,n1720,18582455,181_0,FAILED,SOBOL,81,0.085146901902742683221347874678,897,7230,0.486156552564352750778198242188,4,0.893587954342365264892578125,leaky_relu,normal
182,1753202932,683,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 14 --learning_rate 0.01883105843244120559 --batch_size 2123 --hidden_size 1918 --dropout 0.29032034799456596375 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.11856682691723108292,,1,,n1720,18582507,182_0,FAILED,SOBOL,14,0.01883105843244120558566123691,2123,1918,0.2903203479945659637451171875,3,0.118566826917231082916259765625,leaky_relu,normal
183,1753202920,695,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 141 --learning_rate 0.05401575921773910799 --batch_size 1868 --hidden_size 5342 --dropout 0.10314241796731948853 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.6688970634713768959,,1,,n1720,18582498,183_0,FAILED,SOBOL,141,0.054015759217739107989064706317,1868,5342,0.103142417967319488525390625,2,0.668897063471376895904541015625,leaky_relu,normal
184,1753202921,694,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 129 --learning_rate 0.03161054758494720451 --batch_size 2551 --hidden_size 7929 --dropout 0.35094397189095616341 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29229540005326271057,,1,,n1720,18582499,184_0,FAILED,SOBOL,129,0.031610547584947204513561302974,2551,7929,0.350943971890956163406372070312,2,0.2922954000532627105712890625,leaky_relu,normal
185,1753202934,681,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 26 --learning_rate 0.09586772493831813291 --batch_size 1785 --hidden_size 3418 --dropout 0.03861351357772946358 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99886207655072212219,,1,,n1720,18582510,185_0,FAILED,SOBOL,26,0.095867724938318132910097801869,1785,3418,0.038613513577729463577270507812,3,0.9988620765507221221923828125,leaky_relu,normal
186,1753202925,690,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 69 --learning_rate 0.0014274717249907554 --batch_size 3530 --hidden_size 5666 --dropout 0.24908811133354902267 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.02022026199847459793,,1,,n1720,18582500,186_0,FAILED,SOBOL,69,0.001427471724990755398698727419,3530,5666,0.249088111333549022674560546875,4,0.020220261998474597930908203125,leaky_relu,normal
187,1753202928,687,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 196 --learning_rate 0.06514806415941566675 --batch_size 718 --hidden_size 1466 --dropout 0.43728402908891439438 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.68865325767546892166,,1,,n1720,18582504,187_0,FAILED,SOBOL,196,0.065148064159415666751762330478,718,1466,0.437284029088914394378662109375,1,0.688653257675468921661376953125,leaky_relu,normal
188,1753202930,685,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 162 --learning_rate 0.02259006852516904501 --batch_size 1287 --hidden_size 497 --dropout 0.44413617020472884178 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14241334516555070877,,1,,n1720,18582506,188_0,FAILED,SOBOL,162,0.022590068525169045010603241508,1287,497,0.444136170204728841781616210938,2,0.142413345165550708770751953125,leaky_relu,normal
189,1753202926,689,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 102 --learning_rate 0.06115889853071421883 --batch_size 2565 --hidden_size 4683 --dropout 0.13096701493486762047 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.5667038382962346077,,1,,n1720,18582501,189_0,FAILED,SOBOL,102,0.061158898530714218833015394239,2565,4683,0.130967014934867620468139648438,3,0.566703838296234607696533203125,leaky_relu,normal
190,1753202928,687,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 35 --learning_rate 0.04164835793515667822 --batch_size 325 --hidden_size 2322 --dropout 0.09231016971170902252 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.4201018698513507843,,1,,n1720,18582505,190_0,FAILED,SOBOL,35,0.041648357935156678222288206825,325,2322,0.09231016971170902252197265625,4,0.4201018698513507843017578125,leaky_relu,normal
191,1753202933,682,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 121 --learning_rate 0.08114398341663182912 --batch_size 3647 --hidden_size 6819 --dropout 0.27960623614490032196 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.87081098929047584534,,1,,n1720,18582509,191_0,FAILED,SOBOL,121,0.081143983416631829119758378965,3647,6819,0.27960623614490032196044921875,1,0.8708109892904758453369140625,leaky_relu,normal
192,1753202927,688,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 122 --learning_rate 0.03552222371743992552 --batch_size 419 --hidden_size 3378 --dropout 0.39527085889130830765 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92267550621181726456,,1,,n1720,18582503,192_0,FAILED,SOBOL,122,0.035522223717439925516625720547,419,3378,0.395270858891308307647705078125,2,0.922675506211817264556884765625,leaky_relu,normal
193,1753202932,683,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 34 --learning_rate 0.0996399555185809721 --batch_size 3742 --hidden_size 7809 --dropout 0.20711690280586481094 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.34891924355179071426,,1,,n1720,18582508,193_0,FAILED,SOBOL,34,0.099639955518580972104736304118,3742,7809,0.207116902805864810943603515625,3,0.348919243551790714263916015625,leaky_relu,normal
194,1753202926,689,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 100 --learning_rate 0.00365508275134488912 --batch_size 1446 --hidden_size 1490 --dropout 0.01225586468353867531 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63980954140424728394,,1,,n1720,18582502,194_0,FAILED,SOBOL,100,0.003655082751344889118588765697,1446,1490,0.012255864683538675308227539062,4,0.639809541404247283935546875,leaky_relu,normal
195,1753202934,681,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 165 --learning_rate 0.06752892923280597037 --batch_size 2723 --hidden_size 5737 --dropout 0.32456724951043725014 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.08856565505266189575,,1,,n1720,18582511,195_0,FAILED,SOBOL,165,0.06752892923280597037294370466,2723,5737,0.324567249510437250137329101562,1,0.088565655052661895751953125,leaky_relu,normal
196,1753202934,681,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 197 --learning_rate 0.02033616203693672936 --batch_size 3435 --hidden_size 4675 --dropout 0.30209196731448173523 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.51004946976900100708,,1,,n1720,18582512,196_0,FAILED,SOBOL,197,0.020336162036936729358149733571,3435,4675,0.3020919673144817352294921875,2,0.510049469769001007080078125,leaky_relu,normal
197,1753203010,605,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 67 --learning_rate 0.05865570375472307918 --batch_size 624 --hidden_size 410 --dropout 0.11474630981683731079 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21856939047574996948,,1,,n1720,18582558,197_0,FAILED,SOBOL,67,0.058655703754723079179633771219,624,410,0.114746309816837310791015625,3,0.218569390475749969482421875,leaky_relu,normal
198,1753203226,390,1753203616,1753203628,12,python3 .tests/mnist/train --epochs 25 --learning_rate 0.03756633572401479187 --batch_size 2393 --hidden_size 6875 --dropout 0.1690472322516143322 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.80243507120758295059,,1,,n1720,18582630,198_0,FAILED,SOBOL,25,0.037566335724014791874747487554,2393,6875,0.169047232251614332199096679688,4,0.802435071207582950592041015625,leaky_relu,normal
199,1753203226,390,1753203616,1753203622,6,python3 .tests/mnist/train --epochs 131 --learning_rate 0.07730048970449716894 --batch_size 1626 --hidden_size 2426 --dropout 0.48222783161327242851 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.4689150610938668251,,1,,n1720,18582631,199_0,FAILED,SOBOL,131,0.077300489704497168941266238562,1626,2426,0.482227831613272428512573242188,1,0.468915061093866825103759765625,leaky_relu,normal
200,1753207342,31,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.01229820330673828642 --batch_size 2282 --hidden_size 861 --dropout 0.22173619549721479416 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.60116343572735786438,,1,,n1720,18583239,200_0,FAILED,SOBOL,143,0.012298203306738286419430572494,2282,861,0.221736195497214794158935546875,1,0.6011634357273578643798828125,leaky_relu,normal
201,1753207349,54,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 13 --learning_rate 0.07290988071914762669 --batch_size 2026 --hidden_size 4351 --dropout 0.41000852640718221664 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.17388028278946876526,,1,,n1720,18583251,201_0,FAILED,SOBOL,13,0.072909880719147626693121821972,2026,4351,0.410008526407182216644287109375,4,0.1738802827894687652587890625,leaky_relu,normal
202,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 79 --learning_rate 0.02999492243146523879 --batch_size 3292 --hidden_size 2998 --dropout 0.37037657620385289192 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.83635142166167497635,,1,,n1720,18583242,202_0,FAILED,SOBOL,79,0.029994922431465238787939853182,3292,2998,0.370376576203852891921997070312,3,0.836351421661674976348876953125,leaky_relu,normal
203,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 185 --learning_rate 0.09114318476282060044 --batch_size 992 --hidden_size 6176 --dropout 0.05818332778289914131 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38863490242511034012,,1,,n1720,18583246,203_0,FAILED,SOBOL,185,0.091143184762820600441912688439,992,6176,0.058183327782899141311645507812,2,0.388634902425110340118408203125,leaky_relu,normal
204,1753207348,55,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 176 --learning_rate 0.04628868058314547507 --batch_size 1049 --hidden_size 7237 --dropout 0.06503550149500370026 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96586923021823167801,,1,,n1720,18583250,204_0,FAILED,SOBOL,176,0.046288680583145475067041729744,1049,7237,0.06503550149500370025634765625,1,0.965869230218231678009033203125,leaky_relu,normal
205,1753207349,54,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 88 --learning_rate 0.08265099543966353268 --batch_size 2839 --hidden_size 4077 --dropout 0.25225539319217205048 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.25838514883071184158,,1,,n1720,18583252,205_0,FAILED,SOBOL,88,0.082650995439663532682317281797,2839,4077,0.25225539319217205047607421875,4,0.258385148830711841583251953125,leaky_relu,normal
206,1753207348,55,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 46 --learning_rate 0.01474174790838733359 --batch_size 55 --hidden_size 5285 --dropout 0.46370514994487166405 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.72164607420563697815,,1,,n1720,18583249,206_0,FAILED,SOBOL,46,0.014741747908387333593216439453,55,5285,0.463705149944871664047241210938,3,0.7216460742056369781494140625,leaky_relu,normal
207,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 110 --learning_rate 0.05017726728897542454 --batch_size 3888 --hidden_size 1813 --dropout 0.15039854636415839195 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.05413054302334785461,,1,,n1720,18583245,207_0,FAILED,SOBOL,110,0.050177267288975424541774827958,3888,1813,0.150398546364158391952514648438,2,0.0541305430233478546142578125,leaky_relu,normal
208,1753207346,57,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 116 --learning_rate 0.01743496514242142553 --batch_size 1842 --hidden_size 7121 --dropout 0.33356049377471208572 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.33716441504657268524,,1,,n1720,18583248,208_0,FAILED,SOBOL,116,0.017434965142421425532415213411,1842,7121,0.333560493774712085723876953125,4,0.33716441504657268524169921875,leaky_relu,normal
209,1753207344,29,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.05384605650464073523 --batch_size 2098 --hidden_size 2152 --dropout 0.02078043762594461441 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.88755583576858043671,,1,,n1720,18583247,209_0,FAILED,SOBOL,52,0.053846056504640735229649806115,2098,2152,0.020780437625944614410400390625,1,0.88755583576858043670654296875,leaky_relu,normal
210,1753207344,29,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 82 --learning_rate 0.04993677473403514144 --batch_size 792 --hidden_size 4909 --dropout 0.20104144001379609108 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.10031989868730306625,,1,,n1720,18583243,210_0,FAILED,SOBOL,82,0.04993677473403514144312254075,792,4909,0.201041440013796091079711914062,2,0.100319898687303066253662109375,leaky_relu,normal
211,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.08532351202657446898 --batch_size 3092 --hidden_size 140 --dropout 0.38773478427901864052 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.67492886539548635483,,1,,n1720,18583241,211_0,FAILED,SOBOL,171,0.085323512026574468980477661262,3092,140,0.387734784279018640518188476562,3,0.674928865395486354827880859375,leaky_relu,normal
212,1753207343,35,1753207378,1753207384,6,python3 .tests/mnist/train --epochs 179 --learning_rate 0.02720103816650807846 --batch_size 3035 --hidden_size 1252 --dropout 0.48830645158886909485 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.22251155134290456772,,1,,n1720,18583244,212_0,FAILED,SOBOL,179,0.027201038166508078458560859758,3035,1252,0.4883064515888690948486328125,4,0.222511551342904567718505859375,leaky_relu,normal
213,1753207349,54,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 73 --learning_rate 0.08776393944537268232 --batch_size 1245 --hidden_size 6003 --dropout 0.17657871544361114502 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.55298183020204305649,,1,,n1720,18583253,213_0,FAILED,SOBOL,73,0.087763939445372682324197910475,1245,6003,0.17657871544361114501953125,1,0.552981830202043056488037109375,leaky_relu,normal
214,1753207342,31,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 19 --learning_rate 0.00894589300211518987 --batch_size 4069 --hidden_size 3137 --dropout 0.10575753776356577873 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.4649732690304517746,,1,,n1720,18583238,214_0,FAILED,SOBOL,19,0.008945893002115189868161948539,4069,3137,0.105757537763565778732299804688,2,0.46497326903045177459716796875,leaky_relu,normal
215,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 149 --learning_rate 0.07014293779367580806 --batch_size 235 --hidden_size 8087 --dropout 0.29356435639783740044 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.75950331799685955048,,1,,n1720,18583240,215_0,FAILED,SOBOL,149,0.070142937793675808055837705979,235,8087,0.293564356397837400436401367188,3,0.75950331799685955047607421875,leaky_relu,normal
216,1753207783,12,1753207795,1753207802,7,python3 .tests/mnist/train --epochs 137 --learning_rate 0.04143397243786603457 --batch_size 3673 --hidden_size 5559 --dropout 0.03356867562979459763 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.13869897555559873581,,1,,n1720,18583365,216_0,FAILED,SOBOL,137,0.041433972437866034566056328003,3673,5559,0.033568675629794597625732421875,3,0.138698975555598735809326171875,leaky_relu,normal
217,1753207784,16,1753207800,1753207806,6,python3 .tests/mnist/train --epochs 31 --learning_rate 0.07980229066135362259 --batch_size 350 --hidden_size 1568 --dropout 0.34622296597808599472 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.58946927916258573532,,1,,n1720,18583367,217_0,FAILED,SOBOL,31,0.079802290661353622591711598488,350,1568,0.346222965978085994720458984375,2,0.589469279162585735321044921875,leaky_relu,normal
218,1753207784,16,1753207800,1753207806,6,python3 .tests/mnist/train --epochs 61 --learning_rate 0.02280983670800924151 --batch_size 2670 --hidden_size 7508 --dropout 0.4317130562849342823 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.42381656356155872345,,1,,n1720,18583370,218_0,FAILED,SOBOL,61,0.022809836708009241512673526131,2670,7508,0.431713056284934282302856445312,1,0.42381656356155872344970703125,leaky_relu,normal
219,1753207803,22,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 191 --learning_rate 0.06249520860044285864 --batch_size 1392 --hidden_size 3844 --dropout 0.24489370780065655708 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.84804617054760456085,,1,,n1720,18583374,219_0,FAILED,SOBOL,191,0.0624952086004428586374359611,1392,3844,0.244893707800656557083129882812,4,0.84804617054760456085205078125,leaky_relu,normal
220,1753207804,21,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 159 --learning_rate 0.00047353571280837057 --batch_size 681 --hidden_size 2731 --dropout 0.12869896180927753448 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.30137889273464679718,,1,,n1720,18583375,220_0,FAILED,SOBOL,159,0.000473535712808370568525917488,681,2731,0.12869896180927753448486328125,3,0.30137889273464679718017578125,leaky_relu,normal
221,1753207818,7,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 94 --learning_rate 0.06454249138040468736 --batch_size 3492 --hidden_size 6413 --dropout 0.4405450727790594101 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.969750942662358284,,1,,n1720,18583379,221_0,FAILED,SOBOL,94,0.064542491380404687362215554458,3492,6413,0.44054507277905941009521484375,2,0.96975094266235828399658203125,leaky_relu,normal
222,1753207819,6,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 40 --learning_rate 0.03255757618639618794 --batch_size 1700 --hidden_size 583 --dropout 0.27687272941693663597 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.01113619934767484665,,1,,n1720,18583380,222_0,FAILED,SOBOL,40,0.032557576186396187944982472118,1700,583,0.276872729416936635971069335938,1,0.011136199347674846649169921875,leaky_relu,normal
223,1753207820,5,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 128 --learning_rate 0.09648020512806251836 --batch_size 2466 --hidden_size 4593 --dropout 0.08918404718860983849 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71776400040835142136,,1,,n1720,18583381,223_0,FAILED,SOBOL,128,0.096480205128062518360465560363,2466,4593,0.089184047188609838485717773438,4,0.717764000408351421356201171875,leaky_relu,normal
224,1753207821,34,1753207855,1753207861,6,python3 .tests/mnist/train --epochs 126 --learning_rate 0.00604750691261142503 --batch_size 3205 --hidden_size 8007 --dropout 0.475785065907984972 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11499126814305782318,,1,,n1720,18583383,224_0,FAILED,SOBOL,126,0.006047506912611425033965417697,3205,8007,0.475785065907984972000122070312,4,0.11499126814305782318115234375,leaky_relu,normal
225,1753207817,8,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 44 --learning_rate 0.06679947932446375636 --batch_size 905 --hidden_size 3312 --dropout 0.16395433293655514717 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.65659538470208644867,,1,,n1720,18583378,225_0,FAILED,SOBOL,44,0.066799479324463756357843635669,905,3312,0.163954332936555147171020507812,1,0.65659538470208644866943359375,leaky_relu,normal
226,1753207816,9,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 96 --learning_rate 0.0363492329638451378 --batch_size 2243 --hidden_size 6050 --dropout 0.12448543589562177658 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.32249319460242986679,,1,,n1720,18583377,226_0,FAILED,SOBOL,96,0.036349232963845137800440454612,2243,6050,0.124485435895621776580810546875,2,0.322493194602429866790771484375,leaky_relu,normal
227,1753207821,34,1753207855,1753207861,6,python3 .tests/mnist/train --epochs 154 --learning_rate 0.09734508920675144505 --batch_size 1988 --hidden_size 1044 --dropout 0.31218925770372152328 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90588916745036840439,,1,,n1720,18583382,227_0,FAILED,SOBOL,154,0.097345089206751445054521809652,1988,1044,0.312189257703721523284912109375,3,0.905889167450368404388427734375,leaky_relu,normal
228,1753207815,10,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 193 --learning_rate 0.03995742644853890468 --batch_size 126 --hidden_size 92 --dropout 0.31897845631465315819 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.45249922480434179306,,1,,n1720,18583376,228_0,FAILED,SOBOL,193,0.039957426448538904684149031254,126,92,0.318978456314653158187866210938,4,0.452499224804341793060302734375,leaky_relu,normal
229,1753207999,7,1753208006,1753208012,6,python3 .tests/mnist/train --epochs 58 --learning_rate 0.07656970487078652854 --batch_size 3960 --hidden_size 5117 --dropout 0.00630902638658881187 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77612775471061468124,,1,,n1720,18583406,229_0,FAILED,SOBOL,58,0.076569704870786528538850745917,3960,5117,0.006309026386588811874389648438,1,0.776127754710614681243896484375,leaky_relu,normal
230,1753208053,13,1753208066,1753208072,6,python3 .tests/mnist/train --epochs 28 --learning_rate 0.02116450472008436778 --batch_size 1104 --hidden_size 2232 --dropout 0.21771011687815189362 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.23498568497598171234,,1,,n1720,18583408,230_0,FAILED,SOBOL,28,0.021164504720084367783705658894,1104,2232,0.21771011687815189361572265625,2,0.23498568497598171234130859375,leaky_relu,normal
231,1753208061,35,1753208096,1753208102,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.05636217236826196464 --batch_size 2893 --hidden_size 6945 --dropout 0.40451408736407756805 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.53635730408132076263,,1,,n1720,18583409,231_0,FAILED,SOBOL,140,0.056362172368261964638946892592,2893,6945,0.40451408736407756805419921875,3,0.53635730408132076263427734375,leaky_relu,normal
232,1753208264,13,1753208277,1753208283,6,python3 .tests/mnist/train --epochs 152 --learning_rate 0.02926099455002695304 --batch_size 1534 --hidden_size 4418 --dropout 0.14158250624313950539 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.408718097023665905,,1,,n1720,18583430,232_0,FAILED,SOBOL,152,0.029260994550026953042731747701,1534,4418,0.141582506243139505386352539062,3,0.408718097023665904998779296875,leaky_relu,normal
233,1753208266,11,1753208277,1753208283,6,python3 .tests/mnist/train --epochs 16 --learning_rate 0.09353113132314756772 --batch_size 2813 --hidden_size 664 --dropout 0.453295102808624506 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86631846707314252853,,1,,n1720,18583431,233_0,FAILED,SOBOL,16,0.093531131323147567724340945006,2813,664,0.453295102808624505996704101562,2,0.866318467073142528533935546875,leaky_relu,normal
234,1753208283,23,1753208306,1753208313,7,python3 .tests/mnist/train --epochs 70 --learning_rate 0.01000781459584832236 --batch_size 461 --hidden_size 6622 --dropout 0.25850746501237154007 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15379759110510349274,,1,,n1720,18583432,234_0,FAILED,SOBOL,70,0.010007814595848322364313176536,461,6622,0.258507465012371540069580078125,1,0.15379759110510349273681640625,leaky_relu,normal
235,1753208283,24,1753208307,1753208313,6,python3 .tests/mnist/train --epochs 182 --learning_rate 0.07374136793864891071 --batch_size 3783 --hidden_size 2684 --dropout 0.07068526837974786758 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57119683362543582916,,1,,n1720,18583433,235_0,FAILED,SOBOL,182,0.073741367938648910707044592527,3783,2684,0.070685268379747867584228515625,4,0.57119683362543582916259765625,leaky_relu,normal
236,1753208306,31,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 166 --learning_rate 0.0140091527193784704 --batch_size 2320 --hidden_size 3636 --dropout 0.04826920805498957634 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02354929782450199127,,1,,n1720,18583435,236_0,FAILED,SOBOL,166,0.01400915271937847039751545708,2320,3636,0.048269208054989576339721679688,3,0.02354929782450199127197265625,leaky_relu,normal
237,1753208307,30,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 84 --learning_rate 0.05256654803035781115 --batch_size 1553 --hidden_size 7555 --dropout 0.36106464220210909843 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.7007122281938791275,,1,,n1720,18583437,237_0,FAILED,SOBOL,84,0.052566548030357811149837488074,1553,7555,0.361064642202109098434448242188,2,0.70071222819387912750244140625,leaky_relu,normal
238,1753208304,33,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 56 --learning_rate 0.04399695917982608673 --batch_size 3378 --hidden_size 1743 --dropout 0.41516239568591117859 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.28896588366478681564,,1,,n1720,18583434,238_0,FAILED,SOBOL,56,0.043996959179826086727693734701,3378,1743,0.4151623956859111785888671875,1,0.288965883664786815643310546875,leaky_relu,normal
239,1753208311,26,1753208337,1753208343,6,python3 .tests/mnist/train --epochs 114 --learning_rate 0.08348114847810939043 --batch_size 567 --hidden_size 5479 --dropout 0.22848419100046157837 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.98680262546986341476,,1,,n1720,18583440,239_0,FAILED,SOBOL,114,0.083481148478109390431711744895,567,5479,0.228484191000461578369140625,4,0.986802625469863414764404296875,leaky_relu,normal
240,1753208308,30,1753208338,1753208344,6,python3 .tests/mnist/train --epochs 108 --learning_rate 0.04754415965648368242 --batch_size 2613 --hidden_size 2474 --dropout 0.28749538632109761238 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.6526498282328248024,,1,,n1720,18583438,240_0,FAILED,SOBOL,108,0.047544159656483682419025882382,2613,2474,0.287495386321097612380981445312,2,0.652649828232824802398681640625,leaky_relu,normal
241,1753208307,30,1753208337,1753208343,6,python3 .tests/mnist/train --epochs 50 --learning_rate 0.08605277250725776317 --batch_size 1335 --hidden_size 6667 --dropout 0.10029087262228131294 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07206326071172952652,,1,,n1720,18583436,241_0,FAILED,SOBOL,50,0.086052772507257763168198039239,1335,6667,0.100290872622281312942504882812,3,0.072063260711729526519775390625,leaky_relu,normal
242,1753208310,27,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 90 --learning_rate 0.01660814681230112985 --batch_size 3599 --hidden_size 329 --dropout 0.18569993507117033005 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.90983530879020690918,,1,,n1720,18583439,242_0,FAILED,SOBOL,90,0.016608146812301129852107450802,3599,329,0.185699935071170330047607421875,4,0.9098353087902069091796875,leaky_relu,normal
243,1753208506,12,1753208518,1753208525,7,python3 .tests/mnist/train --epochs 172 --learning_rate 0.05614111224412918211 --batch_size 277 --hidden_size 4850 --dropout 0.49902167823165655136 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.36542154848575592041,,1,,n1720,18583471,243_0,FAILED,SOBOL,172,0.056141112244129182107243991595,277,4850,0.499021678231656551361083984375,1,0.36542154848575592041015625,leaky_relu,normal
244,1753208539,9,1753208548,1753208554,6,python3 .tests/mnist/train --epochs 187 --learning_rate 0.00655499319387599887 --batch_size 1740 --hidden_size 5817 --dropout 0.38276401674374938011 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78788585960865020752,,1,,n1720,18583489,244_0,FAILED,SOBOL,187,0.006554993193875998866437804224,1740,5817,0.382764016743749380111694335938,2,0.78788585960865020751953125,leaky_relu,normal
245,1753208558,20,1753208578,1753208584,6,python3 .tests/mnist/train --epochs 76 --learning_rate 0.07087391205504536829 --batch_size 2507 --hidden_size 1314 --dropout 0.19447654625400900841 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.48761466145515441895,,1,,n1720,18583490,245_0,FAILED,SOBOL,76,0.070873912055045368285632889638,2507,1314,0.194476546254009008407592773438,3,0.4876146614551544189453125,leaky_relu,normal
246,1753208728,31,1753208759,1753208766,7,python3 .tests/mnist/train --epochs 10 --learning_rate 0.02637250456707551996 --batch_size 770 --hidden_size 7762 --dropout 0.03099973686039447784 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.52459883037954568863,,1,,n1720,18583509,246_0,FAILED,SOBOL,10,0.026372504567075519960051011026,770,7762,0.03099973686039447784423828125,4,0.524598830379545688629150390625,leaky_relu,normal
247,1753208771,18,1753208789,1753208795,6,python3 .tests/mnist/train --epochs 146 --learning_rate 0.09005728140417486316 --batch_size 3581 --hidden_size 3586 --dropout 0.34317760728299617767 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.19986964110285043716,,1,,n1720,18583511,247_0,FAILED,SOBOL,146,0.090057281404174863159717290273,3581,3586,0.34317760728299617767333984375,1,0.199869641102850437164306640625,leaky_relu,normal
248,1753208780,9,1753208789,1753208795,6,python3 .tests/mnist/train --epochs 134 --learning_rate 0.02354395625004544745 --batch_size 847 --hidden_size 2022 --dropout 0.07975010061636567116 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82332811877131462097,,1,,n1720,18583517,248_0,FAILED,SOBOL,134,0.023543956250045447453622671219,847,2022,0.079750100616365671157836914062,1,0.8233281187713146209716796875,leaky_relu,normal
249,1753208793,26,1753208819,1753208825,6,python3 .tests/mnist/train --epochs 22 --learning_rate 0.06010745221208781131 --batch_size 3147 --hidden_size 5238 --dropout 0.26708061853423714638 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.40483203157782554626,,1,,n1720,18583518,249_0,FAILED,SOBOL,22,0.060107452212087811305174511745,3147,5238,0.267080618534237146377563476562,4,0.4048320315778255462646484375,leaky_relu,normal
250,1753213312,13,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 64 --learning_rate 0.04372416948815808363 --batch_size 1913 --hidden_size 3902 --dropout 0.44717094022780656815 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.61418682802468538284,,1,,n1720,18584512,250_0,FAILED,SOBOL,64,0.043724169488158083629603112286,1913,3902,0.447170940227806568145751953125,3,0.614186828024685382843017578125,leaky_relu,normal
251,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 199 --learning_rate 0.07897061326988041863 --batch_size 2168 --hidden_size 7318 --dropout 0.13397496286779642105 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.15768306422978639603,,1,,n1720,18584524,251_0,FAILED,SOBOL,199,0.078970613269880418627622020722,2168,7318,0.133974962867796421051025390625,2,0.157683064229786396026611328125,leaky_relu,normal
252,1753213313,13,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 160 --learning_rate 0.03328997971480712748 --batch_size 4030 --hidden_size 6351 --dropout 0.23460567323490977287 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.7358902590349316597,,1,,n1720,18584514,252_0,FAILED,SOBOL,160,0.033289979714807127475495462932,4030,6351,0.234605673234909772872924804688,1,0.735890259034931659698486328125,leaky_relu,normal
253,1753213318,7,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 102 --learning_rate 0.09409073421470821874 --batch_size 196 --hidden_size 2917 --dropout 0.42277500731870532036 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.0352476881816983223,,1,,n1720,18584517,253_0,FAILED,SOBOL,102,0.094090734214708218741129996943,196,2917,0.422775007318705320358276367188,4,0.035247688181698322296142578125,leaky_relu,normal
254,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 38 --learning_rate 0.00276544877672567965 --batch_size 2948 --hidden_size 4143 --dropout 0.35199486091732978821 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.95162519440054893494,,1,,n1720,18584521,254_0,FAILED,SOBOL,38,0.00276544877672567964571603838,2948,4143,0.3519948609173297882080078125,3,0.9516251944005489349365234375,leaky_relu,normal
255,1753213311,14,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 120 --learning_rate 0.06371252851393073569 --batch_size 1159 --hidden_size 909 --dropout 0.0396986156702041626 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.27726785466074943542,,1,,n1720,18584510,255_0,FAILED,SOBOL,120,0.063712528513930735685200090757,1159,909,0.03969861567020416259765625,2,0.2772678546607494354248046875,leaky_relu,normal
256,1753213316,10,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 119 --learning_rate 0.00251812175372615431 --batch_size 914 --hidden_size 6929 --dropout 0.21296145115047693253 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75749707501381635666,,1,,n1720,18584515,256_0,FAILED,SOBOL,119,0.002518121753726154307684304001,914,6929,0.212961451150476932525634765625,4,0.757497075013816356658935546875,leaky_relu,normal
257,1753213311,15,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 37 --learning_rate 0.06405588828902691878 --batch_size 3214 --hidden_size 2216 --dropout 0.40114222932606935501 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45529030542820692062,,1,,n1720,18584511,257_0,FAILED,SOBOL,37,0.064055888289026918780422192867,3214,2216,0.401142229326069355010986328125,1,0.455290305428206920623779296875,leaky_relu,normal
258,1753213318,8,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 103 --learning_rate 0.03362953009596094528 --batch_size 1972 --hidden_size 5101 --dropout 0.31481835851445794106 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.55501822568476200104,,1,,n1720,18584518,258_0,FAILED,SOBOL,103,0.033629530095960945279554010767,1972,5101,0.314818358514457941055297851562,2,0.55501822568476200103759765625,leaky_relu,normal
259,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 161 --learning_rate 0.09385026826895774554 --batch_size 2228 --hidden_size 76 --dropout 0.00247252220287919044 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.23222538270056247711,,1,,n1720,18584520,259_0,FAILED,SOBOL,161,0.093850268268957745543268345045,2228,76,0.002472522202879190444946289062,3,0.23222538270056247711181640625,leaky_relu,normal
260,1753213317,8,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 199 --learning_rate 0.04348446423029527635 --batch_size 3962 --hidden_size 1060 --dropout 0.12062423676252365112 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68477966822683811188,,1,,n1720,18584516,260_0,FAILED,SOBOL,199,0.04348446423029527635462088142,3962,1060,0.120624236762523651123046875,4,0.68477966822683811187744140625,leaky_relu,normal
261,1753213310,15,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 63 --learning_rate 0.07930939998589456308 --batch_size 129 --hidden_size 6066 --dropout 0.30793568119406700134 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10221932269632816315,,1,,n1720,18584509,261_0,FAILED,SOBOL,63,0.079309399985894563078758778829,129,6066,0.3079356811940670013427734375,1,0.10221932269632816314697265625,leaky_relu,normal
262,1753213319,37,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 23 --learning_rate 0.02388807969028130043 --batch_size 2888 --hidden_size 3328 --dropout 0.47244937671348452568 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.87773518543690443039,,1,,n1720,18584519,262_0,FAILED,SOBOL,23,0.023888079690281300432319611105,2888,3328,0.472449376713484525680541992188,2,0.877735185436904430389404296875,leaky_relu,normal
263,1753213312,14,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 135 --learning_rate 0.05985936450120062091 --batch_size 1099 --hidden_size 8023 --dropout 0.15929536102339625359 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.33529585879296064377,,1,,n1720,18584513,263_0,FAILED,SOBOL,135,0.059859364501200620911625094323,1099,8023,0.159295361023396253585815429688,3,0.335295858792960643768310546875,leaky_relu,normal
264,1753213319,37,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 146 --learning_rate 0.02652303517283871939 --batch_size 2809 --hidden_size 5495 --dropout 0.41979079600423574448 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.70402494631707668304,,1,,n1720,18584523,264_0,FAILED,SOBOL,146,0.026523035172838719392141015874,2809,5495,0.419790796004235744476318359375,3,0.70402494631707668304443359375,leaky_relu,normal
265,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 11 --learning_rate 0.09000583523381501527 --batch_size 1532 --hidden_size 1759 --dropout 0.23148425202816724777 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.00531443022191524506,,1,,n1720,18584522,265_0,FAILED,SOBOL,11,0.090005835233815015272718085271,1532,1759,0.231484252028167247772216796875,2,0.00531443022191524505615234375,leaky_relu,normal
266,1753213831,8,1753213839,1753213845,6,python3 .tests/mnist/train --epochs 75 --learning_rate 0.00650888077048584861 --batch_size 3788 --hidden_size 7571 --dropout 0.05230921553447842598 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.98345960583537817001,,1,,n1720,18584602,266_0,FAILED,SOBOL,75,0.006508880770485848607509460351,3788,7571,0.052309215534478425979614257812,1,0.983459605835378170013427734375,leaky_relu,normal
267,1753213831,8,1753213839,1753213845,6,python3 .tests/mnist/train --epochs 187 --learning_rate 0.07101605723053217023 --batch_size 465 --hidden_size 3652 --dropout 0.36452904762700200081 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.30717003252357244492,,1,,n1720,18584604,267_0,FAILED,SOBOL,187,0.071016057230532170230219435325,465,3652,0.364529047627002000808715820312,4,0.307170032523572444915771484375,leaky_relu,normal
268,1753213831,12,1753213843,1753213849,6,python3 .tests/mnist/train --epochs 173 --learning_rate 0.01675105565292760862 --batch_size 1544 --hidden_size 2668 --dropout 0.26200809888541698456 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.85394424106925725937,,1,,n1720,18584603,268_0,FAILED,SOBOL,173,0.016751055652927608619062738171,1544,2668,0.26200809888541698455810546875,3,0.853944241069257259368896484375,leaky_relu,normal
269,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 91 --learning_rate 0.05609423913285136593 --batch_size 2311 --hidden_size 6606 --dropout 0.07481502927839756012 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43741829600185155869,,1,,n1720,18584610,269_0,FAILED,SOBOL,91,0.056094239132851365925436226689,2311,6606,0.07481502927839756011962890625,2,0.437418296001851558685302734375,leaky_relu,normal
270,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 49 --learning_rate 0.04749347417401150045 --batch_size 582 --hidden_size 648 --dropout 0.14455781271681189537 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.58354081772267818451,,1,,n1720,18584611,270_0,FAILED,SOBOL,49,0.047493474174011500454906098412,582,648,0.144557812716811895370483398438,1,0.58354081772267818450927734375,leaky_relu,normal
271,1753213840,28,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 107 --learning_rate 0.08620253944788128231 --batch_size 3393 --hidden_size 4402 --dropout 0.45782996481284499168 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.12506661377847194672,,1,,n1720,18584609,271_0,FAILED,SOBOL,107,0.086202539447881282308472350451,3393,4402,0.457829964812844991683959960938,4,0.12506661377847194671630859375,leaky_relu,normal
272,1753213831,10,1753213841,1753213847,6,python3 .tests/mnist/train --epochs 113 --learning_rate 0.04404383229110390291 --batch_size 1347 --hidden_size 3570 --dropout 0.0266249561682343483 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.48265519365668296814,,1,,n1720,18584601,272_0,FAILED,SOBOL,113,0.044043832291103902909501499607,1347,3570,0.026624956168234348297119140625,2,0.4826551936566829681396484375,leaky_relu,normal
273,1753213840,28,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 55 --learning_rate 0.08333823963748292207 --batch_size 2624 --hidden_size 7746 --dropout 0.33943183440715074539 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.80825768038630485535,,1,,n1720,18584606,273_0,FAILED,SOBOL,55,0.083338239637482922073097313387,2624,7746,0.339431834407150745391845703125,3,0.8082576803863048553466796875,leaky_relu,normal
274,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 85 --learning_rate 0.01385938577875494952 --batch_size 264 --hidden_size 1298 --dropout 0.37798592308536171913 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.20485990215092897415,,1,,n1720,18584608,274_0,FAILED,SOBOL,85,0.013859385778754949522517669891,264,1298,0.377985923085361719131469726562,4,0.204859902150928974151611328125,leaky_relu,normal
275,1753213841,58,1753213899,1753213905,6,python3 .tests/mnist/train --epochs 167 --learning_rate 0.05261723351282999311 --batch_size 3587 --hidden_size 5801 --dropout 0.19125812733545899391 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.50425726640969514847,,1,,n1720,18584615,275_0,FAILED,SOBOL,167,0.052617233512829993113957272044,3587,5801,0.191258127335458993911743164062,1,0.504257266409695148468017578125,leaky_relu,normal
276,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 181 --learning_rate 0.01005926076620817199 --batch_size 2508 --hidden_size 4866 --dropout 0.18245661258697509766 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.08266675937920808792,,1,,n1720,18584614,276_0,FAILED,SOBOL,181,0.010059260766208171986035857515,2508,4866,0.18245661258697509765625,2,0.082666759379208087921142578125,leaky_relu,normal
277,1753213840,28,1753213868,1753213881,13,python3 .tests/mnist/train --epochs 69 --learning_rate 0.07359083733288571127 --batch_size 1741 --hidden_size 345 --dropout 0.49415013566613197327 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.62620674539357423782,,1,,n1720,18584607,277_0,FAILED,SOBOL,69,0.07359083733288571127495458768,1741,345,0.4941501356661319732666015625,3,0.626206745393574237823486328125,leaky_relu,normal
278,1753213834,34,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 17 --learning_rate 0.0291188493745401511 --batch_size 3574 --hidden_size 6683 --dropout 0.2837859313003718853 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.3548487834632396698,,1,,n1720,18584605,278_0,FAILED,SOBOL,17,0.029118849374540151098145202013,3574,6683,0.283785931300371885299682617188,4,0.3548487834632396697998046875,leaky_relu,normal
279,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 152 --learning_rate 0.09357724374653772492 --batch_size 763 --hidden_size 2490 --dropout 0.09600569633767008781 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93630870804190635681,,1,,n1720,18584612,279_0,FAILED,SOBOL,152,0.093577243746537724922163192787,763,2490,0.096005696337670087814331054688,1,0.9363087080419063568115234375,leaky_relu,normal
280,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.02082571800407022333 --batch_size 3146 --hidden_size 925 --dropout 0.35600520577281713486 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.05613546911627054214,,1,,n1720,18584613,280_0,FAILED,SOBOL,140,0.020825718004070223332568900787,3146,925,0.356005205772817134857177734375,1,0.056135469116270542144775390625,leaky_relu,normal
281,1753214059,21,1753214080,1753214086,6,python3 .tests/mnist/train --epochs 29 --learning_rate 0.05660187762612477191 --batch_size 846 --hidden_size 4159 --dropout 0.04331670235842466354 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.73132843617349863052,,1,,n1720,18584642,281_0,FAILED,SOBOL,29,0.056601877626124771913929123457,846,4159,0.043316702358424663543701171875,4,0.731328436173498630523681640625,leaky_relu,normal
282,1753214343,8,1753214351,1753214358,7,python3 .tests/mnist/train --epochs 57 --learning_rate 0.04020551415942609508 --batch_size 2176 --hidden_size 2933 --dropout 0.23901962535455822945 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25634934008121490479,,1,,n1720,18584693,282_0,FAILED,SOBOL,57,0.040205514159426095077698448677,2176,2933,0.239019625354558229446411132812,3,0.25634934008121490478515625,leaky_relu,normal
283,1753214388,23,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 193 --learning_rate 0.07622558143055066515 --batch_size 1920 --hidden_size 6367 --dropout 0.42586555751040577888 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.95615670084953308105,,1,,n1720,18584696,283_0,FAILED,SOBOL,193,0.076225581430550665151812950171,1920,6367,0.425865557510405778884887695312,2,0.9561567008495330810546875,leaky_relu,normal
284,1753214394,17,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 155 --learning_rate 0.03600587318874896164 --batch_size 186 --hidden_size 7302 --dropout 0.45029774866998195648 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.37878468632698059082,,1,,n1720,18584701,284_0,FAILED,SOBOL,155,0.036005873188748961644112256408,186,7302,0.45029774866998195648193359375,1,0.3787846863269805908203125,leaky_relu,normal
285,1753214392,19,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 97 --learning_rate 0.09759241622975096953 --batch_size 4019 --hidden_size 3886 --dropout 0.13847845979034900665 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.83445329964160919189,,1,,n1720,18584699,285_0,FAILED,SOBOL,97,0.097592416229750969525191806042,4019,3886,0.13847845979034900665283203125,4,0.83445329964160919189453125,leaky_relu,normal
286,1753214395,16,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 43 --learning_rate 0.00628797285836189997 --batch_size 1172 --hidden_size 5222 --dropout 0.0833433433435857296 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.18369961623102426529,,1,,n1720,18584703,286_0,FAILED,SOBOL,43,0.006287972858361899966550545571,1172,5222,0.083343343343585729598999023438,3,0.183699616231024265289306640625,leaky_relu,normal
287,1753214395,18,1753214413,1753214419,6,python3 .tests/mnist/train --epochs 125 --learning_rate 0.06645992894330993161 --batch_size 2961 --hidden_size 2006 --dropout 0.2709975740872323513 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60303139034658670425,,1,,n1720,18584704,287_0,FAILED,SOBOL,125,0.066459928943309931614891183926,2961,2006,0.270997574087232351303100585938,2,0.603031390346586704254150390625,leaky_relu,normal
288,1753214389,22,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 128 --learning_rate 0.03279804362077266139 --batch_size 3733 --hidden_size 2410 --dropout 0.16592121170833706856 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.19017333164811134338,,1,,n1720,18584697,288_0,FAILED,SOBOL,128,0.03279804362077266138841835641,3733,2410,0.165921211708337068557739257812,2,0.1901733316481113433837890625,leaky_relu,normal
289,1753214388,23,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 40 --learning_rate 0.09614065623553470774 --batch_size 411 --hidden_size 6860 --dropout 0.47772536100819706917 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.52260594442486763,,1,,n1720,18584695,289_0,FAILED,SOBOL,40,0.096140656235534707740875148829,411,6860,0.477725361008197069168090820312,3,0.5226059444248676300048828125,leaky_relu,normal
290,1753214395,16,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 94 --learning_rate 0.00013017444908618929 --batch_size 2739 --hidden_size 394 --dropout 0.2985017215833067894 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.49734185356646776199,,1,,n1720,18584702,290_0,FAILED,SOBOL,94,0.000130174449086189287713710705,2739,394,0.298501721583306789398193359375,4,0.497341853566467761993408203125,leaky_relu,normal
291,1753214390,21,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 158 --learning_rate 0.06478981691477821159 --batch_size 1461 --hidden_size 4659 --dropout 0.11083211284130811691 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.78990891296416521072,,1,,n1720,18584698,291_0,FAILED,SOBOL,158,0.064789816914778211587311318453,1461,4659,0.110832112841308116912841796875,1,0.789908912964165210723876953125,leaky_relu,normal
292,1753214394,17,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 191 --learning_rate 0.02305792590752243909 --batch_size 621 --hidden_size 5753 --dropout 0.00824443390592932701 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.36733814794570207596,,1,,n1720,18584700,292_0,FAILED,SOBOL,191,0.023057925907522439090691079855,621,5753,0.008244433905929327011108398438,2,0.367338147945702075958251953125,leaky_relu,normal
293,1753214588,35,1753214623,1753214629,6,python3 .tests/mnist/train --epochs 62 --learning_rate 0.06215108664883300937 --batch_size 3432 --hidden_size 1506 --dropout 0.32094831531867384911 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.91966895479708909988,,1,,n1720,18584731,293_0,FAILED,SOBOL,62,0.062151086648833009373760205563,3432,1506,0.320948315318673849105834960938,3,0.919668954797089099884033203125,leaky_relu,normal
294,1753214611,12,1753214623,1753214629,6,python3 .tests/mnist/train --epochs 30 --learning_rate 0.04109518423322588293 --batch_size 1631 --hidden_size 7825 --dropout 0.39085420779883861542 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.07017754390835762024,,1,,n1720,18584733,294_0,FAILED,SOBOL,30,0.041095184233225882930451433594,1631,7825,0.39085420779883861541748046875,4,0.0701775439083576202392578125,leaky_relu,normal
295,1753214610,15,1753214625,1753214631,6,python3 .tests/mnist/train --epochs 137 --learning_rate 0.08004199443059042962 --batch_size 2398 --hidden_size 3394 --dropout 0.2040234152227640152 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.64284634962677955627,,1,,n1720,18584732,295_0,FAILED,SOBOL,137,0.080041994430590429621119596959,2398,3394,0.20402341522276401519775390625,1,0.6428463496267795562744140625,leaky_relu,normal
296,1753214613,10,1753214623,1753214629,6,python3 .tests/mnist/train --epochs 149 --learning_rate 0.00880374633800238247 --batch_size 2029 --hidden_size 1829 --dropout 0.46695116767659783363 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.27146324608474969864,,1,,n1720,18584735,296_0,FAILED,SOBOL,149,0.008803746338002382473830742526,2029,1829,0.466951167676597833633422851562,1,0.271463246084749698638916015625,leaky_relu,normal
297,1753214612,13,1753214625,1753214631,6,python3 .tests/mnist/train --epochs 18 --learning_rate 0.07018904872843996501 --batch_size 2285 --hidden_size 5301 --dropout 0.1552730225957930088 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.93786896858364343643,,1,,n1720,18584734,297_0,FAILED,SOBOL,18,0.070189048728439965008085721365,2285,5301,0.155273022595793008804321289062,4,0.937868968583643436431884765625,leaky_relu,normal
298,1753214821,13,1753214834,1753214840,6,python3 .tests/mnist/train --epochs 74 --learning_rate 0.02725248582549393353 --batch_size 987 --hidden_size 4093 --dropout 0.06874604616314172745 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.04102165251970291138,,1,,n1720,18584768,298_0,FAILED,SOBOL,74,0.027252485825493933530028201062,987,4093,0.068746046163141727447509765625,3,0.041021652519702911376953125,leaky_relu,normal
299,1753214821,13,1753214834,1753214840,6,python3 .tests/mnist/train --epochs 179 --learning_rate 0.08761341032823548314 --batch_size 3287 --hidden_size 7253 --dropout 0.25654142070561647415 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.74961607903242111206,,1,,n1720,18584769,299_0,FAILED,SOBOL,179,0.087613410328235483137682138022,3287,7253,0.256541420705616474151611328125,2,0.749616079032421112060546875,leaky_relu,normal
300,1753219718,25,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 170 --learning_rate 0.04978700630478561512 --batch_size 2847 --hidden_size 6160 --dropout 0.37474836362525820732 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.17127143591642379761,,1,,n1720,18585663,300_0,FAILED,SOBOL,170,0.049787006304785615118380093236,2847,6160,0.374748363625258207321166992188,1,0.171271435916423797607421875,leaky_relu,normal
301,1753219712,31,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 82 --learning_rate 0.0853741960204206507 --batch_size 1059 --hidden_size 2982 --dropout 0.06192634580656886101 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.62009824067354202271,,1,,n1720,18585654,301_0,FAILED,SOBOL,82,0.085374196020420650699023212837,1059,2982,0.061926345806568861007690429688,4,0.620098240673542022705078125,leaky_relu,normal
302,1753219719,54,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.01748183974232524543 --batch_size 3874 --hidden_size 4335 --dropout 0.22651349753141403198 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39121301565319299698,,1,,n1720,18585665,302_0,FAILED,SOBOL,52,0.017481839742325245429244162665,3874,4335,0.226513497531414031982421875,3,0.391213015653192996978759765625,leaky_relu,normal
303,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 116 --learning_rate 0.05370314915264026018 --batch_size 40 --hidden_size 845 --dropout 0.41322591528296470642 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.81738630030304193497,,1,,n1720,18585656,303_0,FAILED,SOBOL,116,0.053703149152640260177715703094,40,845,0.4132259152829647064208984375,2,0.817386300303041934967041015625,leaky_relu,normal
304,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 110 --learning_rate 0.01469106391454115534 --batch_size 2087 --hidden_size 8071 --dropout 0.10225778119638562202 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.5421627415344119072,,1,,n1720,18585666,304_0,FAILED,SOBOL,110,0.014691063914541155344117839832,2087,8071,0.102257781196385622024536132812,4,0.542162741534411907196044921875,leaky_relu,normal
305,1753219714,31,1753219745,1753219751,6,python3 .tests/mnist/train --epochs 46 --learning_rate 0.05032703571822494393 --batch_size 1831 --hidden_size 3121 --dropout 0.28943571122363209724 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24874297808855772018,,1,,n1720,18585659,305_0,FAILED,SOBOL,46,0.050327035718224943927623371565,1831,3121,0.289435711223632097244262695312,1,0.248742978088557720184326171875,leaky_relu,normal
306,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 88 --learning_rate 0.04643158793514595012 --batch_size 3105 --hidden_size 5987 --dropout 0.48533411230891942978 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.77035270817577838898,,1,,n1720,18585668,306_0,FAILED,SOBOL,88,0.046431587935145950118975832765,3105,5987,0.485334112308919429779052734375,2,0.77035270817577838897705078125,leaky_relu,normal
307,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 176 --learning_rate 0.08260412083975970932 --batch_size 805 --hidden_size 1236 --dropout 0.17204658221453428268 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.43877256102859973907,,1,,n1720,18585655,307_0,FAILED,SOBOL,176,0.082604120839759709316041380589,805,1236,0.172046582214534282684326171875,3,0.43877256102859973907470703125,leaky_relu,normal
308,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 185 --learning_rate 0.02994881149670109224 --batch_size 1245 --hidden_size 156 --dropout 0.19641198357567191124 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89229971356689929962,,1,,n1720,18585657,308_0,FAILED,SOBOL,185,0.029948811496701092244032693657,1245,156,0.196411983575671911239624023438,4,0.89229971356689929962158203125,leaky_relu,normal
309,1753219715,28,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 80 --learning_rate 0.09128533142693341651 --batch_size 3033 --hidden_size 4925 --dropout 0.38473390555009245872 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31658093817532062531,,1,,n1720,18585662,309_0,FAILED,SOBOL,80,0.091285331426933416509861274335,3033,4925,0.384733905550092458724975585938,1,0.31658093817532062530517578125,leaky_relu,normal
310,1753219719,24,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 13 --learning_rate 0.0124487324238754804 --batch_size 242 --hidden_size 2168 --dropout 0.32951769791543483734 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.67021522950381040573,,1,,n1720,18585664,310_0,FAILED,SOBOL,13,0.012448732423875480401775917016,242,2168,0.32951769791543483734130859375,2,0.670215229503810405731201171875,leaky_relu,normal
311,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.07285843306016177856 --batch_size 4076 --hidden_size 7136 --dropout 0.01731300540268421173 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.12093415390700101852,,1,,n1720,18585658,311_0,FAILED,SOBOL,143,0.072858433060161778560548384576,4076,7136,0.01731300540268421173095703125,3,0.120934153907001018524169921875,leaky_relu,normal
312,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 131 --learning_rate 0.03791045767562464114 --batch_size 351 --hidden_size 4609 --dropout 0.28073671320453286171 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99649834446609020233,,1,,n1720,18585667,312_0,FAILED,SOBOL,131,0.037910457675624641138423243092,351,4609,0.280736713204532861709594726562,3,0.99649834446609020233154296875,leaky_relu,normal
313,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 25 --learning_rate 0.07705240050498396442 --batch_size 3673 --hidden_size 599 --dropout 0.09344064677134156227 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29095746390521526337,,1,,n1720,18585669,313_0,FAILED,SOBOL,25,0.077052400504983964424354780931,3673,599,0.093440646771341562271118164062,2,0.29095746390521526336669921875,leaky_relu,normal
314,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 68 --learning_rate 0.0200964582676999258 --batch_size 1385 --hidden_size 6429 --dropout 0.13203571084886789322 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.6909863566979765892,,1,,n1720,18585670,314_0,FAILED,SOBOL,68,0.020096458267699925798188687054,1385,6429,0.132035710848867893218994140625,1,0.690986356697976589202880859375,leaky_relu,normal
315,1753219715,28,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 197 --learning_rate 0.05899449195936322388 --batch_size 2663 --hidden_size 2747 --dropout 0.44520486611872911453 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.02152684982866048813,,1,,n1720,18585661,315_0,FAILED,SOBOL,197,0.05899449195936322387634476172,2663,2747,0.445204866118729114532470703125,4,0.021526849828660488128662109375,leaky_relu,normal
316,1753220288,29,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 164 --learning_rate 0.00399463164387270798 --batch_size 3503 --hidden_size 3828 --dropout 0.43645875854417681694 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.56928155478090047836,,1,,n1720,18585725,316_0,FAILED,SOBOL,164,0.003994631643872707978115688121,3503,3828,0.436458758544176816940307617188,3,0.569281554780900478363037109375,leaky_relu,normal
317,1753220289,28,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 100 --learning_rate 0.06728846179842949693 --batch_size 692 --hidden_size 7492 --dropout 0.24826284078881144524 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14396455045789480209,,1,,n1720,18585726,317_0,FAILED,SOBOL,100,0.067288461798429496929507820369,692,7492,0.248262840788811445236206054688,2,0.143964550457894802093505859375,leaky_relu,normal
318,1753220290,27,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 34 --learning_rate 0.03527489818306640129 --batch_size 2453 --hidden_size 1552 --dropout 0.03772789239883422852 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.8682035934180021286,,1,,n1720,18585727,318_0,FAILED,SOBOL,34,0.035274898183066401291529956552,2453,1552,0.037727892398834228515625,1,0.86820359341800212860107421875,leaky_relu,normal
319,1753220292,25,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 122 --learning_rate 0.09998331678230315545 --batch_size 1686 --hidden_size 5543 --dropout 0.35005835071206092834 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.41852026991546154022,,1,,n1720,18585728,319_0,FAILED,SOBOL,122,0.099983316782303155445532638623,1686,5543,0.3500583507120609283447265625,4,0.41852026991546154022216796875,leaky_relu,normal
320,1753220293,26,1753220319,1753220325,6,python3 .tests/mnist/train --epochs 120 --learning_rate 0.04170666369413957714 --batch_size 2356 --hidden_size 560 --dropout 0.48134340252727270126 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.35151926707476377487,,1,,n1720,18585732,320_0,FAILED,SOBOL,120,0.041706663694139577136521523926,2356,560,0.481343402527272701263427734375,3,0.351519267074763774871826171875,leaky_relu,normal
321,1753220300,50,1753220350,1753220356,6,python3 .tests/mnist/train --epochs 35 --learning_rate 0.08098964192830027109 --batch_size 1589 --hidden_size 4490 --dropout 0.16816280316561460495 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92424925696104764938,,1,,n1720,18585740,321_0,FAILED,SOBOL,35,0.080989641928300271089824491355,1589,4490,0.168162803165614604949951171875,2,0.924249256961047649383544921875,leaky_relu,normal
322,1753220299,18,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 102 --learning_rate 0.02245173423225060166 --batch_size 3342 --hidden_size 2772 --dropout 0.11392366187646985054 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.08599579520523548126,,1,,n1720,18585734,322_0,FAILED,SOBOL,102,0.022451734232250601663860578583,3342,2772,0.113923661876469850540161132812,1,0.08599579520523548126220703125,leaky_relu,normal
323,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 163 --learning_rate 0.061198151365481325 --batch_size 531 --hidden_size 6502 --dropout 0.30126931937411427498 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63826571591198444366,,1,,n1720,18585738,323_0,FAILED,SOBOL,163,0.061198151365481325003603529922,531,6502,0.301269319374114274978637695312,4,0.63826571591198444366455078125,leaky_relu,normal
324,1753220298,19,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 196 --learning_rate 0.00146596089461818345 --batch_size 1482 --hidden_size 7483 --dropout 0.32563475333154201508 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21624414809048175812,,1,,n1720,18585733,324_0,FAILED,SOBOL,196,0.001465960894618183445875514437,1482,7483,0.32563475333154201507568359375,3,0.21624414809048175811767578125,leaky_relu,normal
325,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 69 --learning_rate 0.06501049055438488933 --batch_size 2760 --hidden_size 3740 --dropout 0.01332336850464344025 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.50875026173889636993,,1,,n1720,18585736,325_0,FAILED,SOBOL,69,0.065010490554384889327899088585,2760,3740,0.01332336850464344024658203125,2,0.50875026173889636993408203125,leaky_relu,normal
326,1753220293,24,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.03145544540872798056 --batch_size 512 --hidden_size 5599 --dropout 0.20824475726112723351 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.47127142082899808884,,1,,n1720,18585731,326_0,FAILED,SOBOL,27,0.031455445408727980560747994332,512,5599,0.208244757261127233505249023438,1,0.471271420828998088836669921875,leaky_relu,normal
327,1753220292,25,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 129 --learning_rate 0.09592679436244071212 --batch_size 3834 --hidden_size 1655 --dropout 0.39639871334657073021 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.80376515816897153854,,1,,n1720,18585730,327_0,FAILED,SOBOL,129,0.095926794362440712116146812605,3834,1655,0.396398713346570730209350585938,4,0.803765158168971538543701171875,leaky_relu,normal
328,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 141 --learning_rate 0.01847931471569463566 --batch_size 81 --hidden_size 3160 --dropout 0.15152923110872507095 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.17255426757037639618,,1,,n1720,18585739,328_0,FAILED,SOBOL,141,0.018479314715694635656850763894,81,3160,0.151529231108725070953369140625,4,0.17255426757037639617919921875,leaky_relu,normal
329,1753220299,18,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 15 --learning_rate 0.05426842147633433727 --batch_size 3915 --hidden_size 8191 --dropout 0.46483583468943834305 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.59878873638808727264,,1,,n1720,18585735,329_0,FAILED,SOBOL,15,0.054268421476334337272273700137,3915,8191,0.464835834689438343048095703125,1,0.59878873638808727264404296875,leaky_relu,normal
330,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 81 --learning_rate 0.0487827195649035289 --batch_size 1148 --hidden_size 1212 --dropout 0.25332388142123818398 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38993052300065755844,,1,,n1720,18585737,330_0,FAILED,SOBOL,81,0.048782719564903528897126250286,1148,1212,0.253323881421238183975219726562,2,0.389930523000657558441162109375,leaky_relu,normal
331,1753220588,29,1753220617,1753220624,7,python3 .tests/mnist/train --epochs 184 --learning_rate 0.08481573546323925572 --batch_size 2937 --hidden_size 5915 --dropout 0.06610398972406983376 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.83869644161313772202,,1,,n1720,18585795,331_0,FAILED,SOBOL,184,0.084815735463239255720324649701,2937,5915,0.066103989724069833755493164062,3,0.838696441613137722015380859375,leaky_relu,normal
332,1753220905,15,1753220920,1753220926,6,python3 .tests/mnist/train --epochs 175 --learning_rate 0.02742809596480801776 --batch_size 3266 --hidden_size 4933 --dropout 0.0573577880859375 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.25992443319410085678,,1,,n1720,18585848,332_0,FAILED,SOBOL,175,0.027428095964808017759306579819,3266,4933,0.0573577880859375,4,0.259924433194100856781005859375,leaky_relu,normal
333,1753220914,34,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 90 --learning_rate 0.08900321584809571529 --batch_size 965 --hidden_size 244 --dropout 0.36955103650689125061 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96845791395753622055,,1,,n1720,18585852,333_0,FAILED,SOBOL,90,0.089003215848095715290178020496,965,244,0.3695510365068912506103515625,1,0.968457913957536220550537109375,leaky_relu,normal
334,1753220909,11,1753220920,1753220926,6,python3 .tests/mnist/train --epochs 47 --learning_rate 0.00863342398433014635 --batch_size 2183 --hidden_size 7081 --dropout 0.40912317438051104546 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.05255991034209728241,,1,,n1720,18585851,334_0,FAILED,SOBOL,47,0.008633423984330146350174572945,2183,7081,0.409123174380511045455932617188,2,0.05255991034209728240966796875,leaky_relu,normal
335,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 108 --learning_rate 0.06879395542293786914 --batch_size 1928 --hidden_size 2064 --dropout 0.22085084347054362297 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.71902675740420818329,,1,,n1720,18585861,335_0,FAILED,SOBOL,108,0.068793955422937869137456345925,1928,2064,0.220850843470543622970581054688,3,0.71902675740420818328857421875,leaky_relu,normal
336,1753220908,17,1753220925,1753220931,6,python3 .tests/mnist/train --epochs 114 --learning_rate 0.01111065944880247104 --batch_size 3971 --hidden_size 5326 --dropout 0.29463308211416006088 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.88905649259686470032,,1,,n1720,18585850,336_0,FAILED,SOBOL,114,0.011110659448802471041539696728,3971,5326,0.294633082114160060882568359375,1,0.8890564925968647003173828125,leaky_relu,normal
337,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 53 --learning_rate 0.07263699724404142077 --batch_size 137 --hidden_size 1902 --dropout 0.10682626347988843918 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.3398365415632724762,,1,,n1720,18585856,337_0,FAILED,SOBOL,53,0.072636997244041420773719153203,137,1902,0.106826263479888439178466796875,4,0.3398365415632724761962890625,leaky_relu,normal
338,1753220906,14,1753220920,1753220926,6,python3 .tests/mnist/train --epochs 84 --learning_rate 0.03129217188525944965 --batch_size 3008 --hidden_size 7214 --dropout 0.17770916270092129707 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.67345884162932634354,,1,,n1720,18585849,338_0,FAILED,SOBOL,84,0.031292171885259449648497565022,3008,7214,0.177709162700921297073364257812,3,0.673458841629326343536376953125,leaky_relu,normal
339,1753220915,33,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 169 --learning_rate 0.09150147982956842452 --batch_size 1219 --hidden_size 3974 --dropout 0.4894368988461792469 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.09767912048846483231,,1,,n1720,18585853,339_0,FAILED,SOBOL,169,0.091501479829568424517738378654,1219,3974,0.489436898846179246902465820312,2,0.097679120488464832305908203125,leaky_relu,normal
340,1753220916,32,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 178 --learning_rate 0.04582087065074592902 --batch_size 890 --hidden_size 3037 --dropout 0.38684919290244579315 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.55175547022372484207,,1,,n1720,18585860,340_0,FAILED,SOBOL,178,0.045820870650745929020253299768,890,3037,0.38684919290244579315185546875,1,0.551755470223724842071533203125,leaky_relu,normal
341,1753220916,32,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 75 --learning_rate 0.08165875987159089411 --batch_size 3190 --hidden_size 6264 --dropout 0.20015584863722324371 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.22011443693190813065,,1,,n1720,18585855,341_0,FAILED,SOBOL,75,0.081658759871590894108273062102,3190,6264,0.20015584863722324371337890625,4,0.220114436931908130645751953125,leaky_relu,normal
342,1753220916,32,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 21 --learning_rate 0.01529496906027197865 --batch_size 1869 --hidden_size 837 --dropout 0.01995513727888464928 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.76075935736298561096,,1,,n1720,18585854,342_0,FAILED,SOBOL,21,0.015294969060271978653076097032,1869,837,0.019955137278884649276733398438,3,0.7607593573629856109619140625,leaky_relu,normal
343,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 147 --learning_rate 0.05127920882506296213 --batch_size 2124 --hidden_size 4247 --dropout 0.33273519342765212059 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.46740077808499336243,,1,,n1720,18585857,343_0,FAILED,SOBOL,147,0.051279208825062962129326393779,2124,4247,0.332735193427652120590209960938,2,0.4674007780849933624267578125,leaky_relu,normal
344,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 135 --learning_rate 0.0351000502202659867 --batch_size 1792 --hidden_size 6835 --dropout 0.08836163673549890518 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.58704532776027917862,,1,,n1720,18585858,344_0,FAILED,SOBOL,135,0.035100050220265986700152183175,1792,6835,0.088361636735498905181884765625,2,0.587045327760279178619384765625,leaky_relu,normal
345,1753220916,33,1753220949,1753220955,6,python3 .tests/mnist/train --epochs 32 --learning_rate 0.09859579779198393568 --batch_size 2558 --hidden_size 2338 --dropout 0.27605031896382570267 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.13742312882095575333,,1,,n1720,18585859,345_0,FAILED,SOBOL,32,0.098595797791983935676185524244,2558,2338,0.276050318963825702667236328125,3,0.137423128820955753326416015625,leaky_relu,normal
346,1753221195,26,1753221221,1753221227,6,python3 .tests/mnist/train --epochs 63 --learning_rate 0.00416266746800392912 --batch_size 718 --hidden_size 4699 --dropout 0.4396604062058031559 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.85043924301862716675,,1,,n1720,18585889,346_0,FAILED,SOBOL,63,0.004162667468003929116537875643,718,4699,0.439660406205803155899047851562,4,0.850439243018627166748046875,leaky_relu,normal
347,1753221357,14,1753221371,1753221377,6,python3 .tests/mnist/train --epochs 190 --learning_rate 0.06868279292741791275 --batch_size 3529 --hidden_size 513 --dropout 0.12781429523602128029 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.42506129294633865356,,1,,n1720,18585915,347_0,FAILED,SOBOL,190,0.068682792927417912753895734568,3529,513,0.127814295236021280288696289062,1,0.425061292946338653564453125,leaky_relu,normal
348,1753221472,19,1753221491,1753221498,7,python3 .tests/mnist/train --epochs 157 --learning_rate 0.01909669676478952319 --batch_size 2578 --hidden_size 1450 --dropout 0.24602132290601730347 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.97238863259553909302,,1,,n1720,18585919,348_0,FAILED,SOBOL,157,0.01909669676478952318743331773,2578,1450,0.246021322906017303466796875,2,0.972388632595539093017578125,leaky_relu,normal
349,1753221475,16,1753221491,1753221498,7,python3 .tests/mnist/train --epochs 96 --learning_rate 0.05842845745915547367 --batch_size 1300 --hidden_size 5649 --dropout 0.43284067139029502869 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.30286823958158493042,,1,,n1720,18585920,349_0,FAILED,SOBOL,96,0.058428457459155473674439207343,1300,5649,0.4328406713902950286865234375,3,0.302868239581584930419921875,leaky_relu,normal
350,1753226895,29,1753226924,1753226930,6,python3 .tests/mnist/train --epochs 41 --learning_rate 0.03891550659202039353 --batch_size 3636 --hidden_size 3402 --dropout 0.34729070914909243584 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71509638521820306778,,1,,n1720,18586432,350_0,FAILED,SOBOL,41,0.038915506592020393528130739469,3636,3402,0.347290709149092435836791992188,4,0.715096385218203067779541015625,leaky_relu,normal
351,1753226894,29,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 126 --learning_rate 0.07761314759170637179 --batch_size 314 --hidden_size 7913 --dropout 0.03463641880080103874 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.00961668882519006729,,1,,n1720,18586429,351_0,FAILED,SOBOL,126,0.077613147591706371786202112162,314,7913,0.034636418800801038742065429688,1,0.009616688825190067291259765625,leaky_relu,normal
352,1753226887,6,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 124 --learning_rate 0.02484101404324173812 --batch_size 1077 --hidden_size 4168 --dropout 0.40533676603808999062 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.65907750651240348816,,1,,n1720,18586423,352_0,FAILED,SOBOL,124,0.024841014043241738118439343452,1077,4168,0.405336766038089990615844726562,1,0.6590775065124034881591796875,leaky_relu,normal
353,1753226886,7,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 45 --learning_rate 0.06046555710686370849 --batch_size 2866 --hidden_size 1013 --dropout 0.21853279555216431618 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11669912561774253845,,1,,n1720,18586421,353_0,FAILED,SOBOL,45,0.060465557106863708491939490841,2866,1013,0.218532795552164316177368164062,4,0.1166991256177425384521484375,leaky_relu,normal
354,1753226884,9,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 98 --learning_rate 0.04253681729082018498 --batch_size 27 --hidden_size 6312 --dropout 0.00719342473894357681 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90343791712075471878,,1,,n1720,18586420,354_0,FAILED,SOBOL,98,0.042536817290820184978006324172,27,6312,0.007193424738943576812744140625,3,0.903437917120754718780517578125,leaky_relu,normal
355,1753226893,30,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 153 --learning_rate 0.07869791996674613266 --batch_size 3860 --hidden_size 2830 --dropout 0.31986285466700792313 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.32081644702702760696,,1,,n1720,18586427,355_0,FAILED,SOBOL,153,0.078697919966746132658386159164,3860,2830,0.319862854667007923126220703125,2,0.320816447027027606964111328125,leaky_relu,normal
356,1753226882,11,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 192 --learning_rate 0.033843392527289691 --batch_size 2270 --hidden_size 3925 --dropout 0.31106143398210406303 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77392016816884279251,,1,,n1720,18586419,356_0,FAILED,SOBOL,192,0.03384339252728969099637268414,2270,3925,0.311061433982104063034057617188,1,0.773920168168842792510986328125,leaky_relu,normal
357,1753226894,30,1753226924,1753226930,6,python3 .tests/mnist/train --epochs 59 --learning_rate 0.09519286592276766934 --batch_size 2015 --hidden_size 7421 --dropout 0.12335761217400431633 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.45106614101678133011,,1,,n1720,18586428,357_0,FAILED,SOBOL,59,0.095192865922767669339954466068,2015,7421,0.123357612174004316329956054688,4,0.451066141016781330108642578125,leaky_relu,normal
358,1753226896,27,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 30 --learning_rate 0.00229744718372821817 --batch_size 3304 --hidden_size 1981 --dropout 0.16288679838180541992 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.538594808429479599,,1,,n1720,18586433,358_0,FAILED,SOBOL,30,0.002297447183728218173676127734,3304,1981,0.162886798381805419921875,3,0.5385948084294795989990234375,leaky_relu,normal
359,1753226894,29,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 139 --learning_rate 0.06272010277388617716 --batch_size 1005 --hidden_size 5150 --dropout 0.47471753135323524475 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.23644892498850822449,,1,,n1720,18586431,359_0,FAILED,SOBOL,139,0.06272010277388617716098906385,1005,5150,0.4747175313532352447509765625,2,0.2364489249885082244873046875,leaky_relu,normal
360,1753226888,5,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 151 --learning_rate 0.04805193528942764553 --batch_size 3416 --hidden_size 7737 --dropout 0.22741573350504040718 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86488170269876718521,,1,,n1720,18586424,360_0,FAILED,SOBOL,151,0.048051935289427645525694998696,3416,7737,0.227415733505040407180786132812,2,0.864881702698767185211181640625,leaky_relu,normal
361,1753226886,9,1753226895,1753226901,6,python3 .tests/mnist/train --epochs 18 --learning_rate 0.0872068256295286115 --batch_size 604 --hidden_size 3482 --dropout 0.4140939381904900074 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.40646844450384378433,,1,,n1720,18586422,361_0,FAILED,SOBOL,18,0.087206825629528611498741952346,604,3482,0.414093938190490007400512695312,3,0.406468444503843784332275390625,leaky_relu,normal
362,1753226894,29,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 71 --learning_rate 0.01618578239884227443 --batch_size 2413 --hidden_size 5857 --dropout 0.35993392672389745712 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57260295748710632324,,1,,n1720,18586430,362_0,FAILED,SOBOL,71,0.016185782398842274432126941974,2413,5857,0.359933926723897457122802734375,4,0.5726029574871063232421875,leaky_relu,normal
363,1753226893,30,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 180 --learning_rate 0.05509676508987322585 --batch_size 1647 --hidden_size 1402 --dropout 0.04713849257677793503 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15601588785648345947,,1,,n1720,18586426,363_0,FAILED,SOBOL,180,0.055096765089873225851313520707,1647,1402,0.047138492576777935028076171875,1,0.15601588785648345947265625,leaky_relu,normal
364,1753226882,11,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 165 --learning_rate 0.00790397314559668392 --batch_size 423 --hidden_size 306 --dropout 0.07157065114006400108 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.70236296951770782471,,1,,n1720,18586418,364_0,FAILED,SOBOL,165,0.007903973145596683916314084684,423,306,0.071570651140064001083374023438,2,0.70236296951770782470703125,leaky_relu,normal
365,1753226889,4,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 86 --learning_rate 0.07118638051459566518 --batch_size 3746 --hidden_size 4747 --dropout 0.25939284777268767357 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02601221203804016113,,1,,n1720,18586425,365_0,FAILED,SOBOL,86,0.071186380514595665180976880038,3746,4747,0.259392847772687673568725585938,3,0.0260122120380401611328125,leaky_relu,normal
366,1753227555,31,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 57 --learning_rate 0.02513323021121323039 --batch_size 1441 --hidden_size 2514 --dropout 0.454120611771941185 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.98512219730764627457,,1,,n1720,18586443,366_0,FAILED,SOBOL,57,0.025133230211213230392841566641,1441,2514,0.45412061177194118499755859375,4,0.985122197307646274566650390625,leaky_relu,normal
367,1753227552,4,1753227556,1753227562,6,python3 .tests/mnist/train --epochs 112 --learning_rate 0.08983022453626618442 --batch_size 2719 --hidden_size 6756 --dropout 0.14240801520645618439 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.2864725673571228981,,1,,n1720,18586439,367_0,FAILED,SOBOL,112,0.089830224536266184420796321319,2719,6756,0.14240801520645618438720703125,1,0.286472567357122898101806640625,leaky_relu,normal
368,1753227556,30,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 106 --learning_rate 0.02890270041367038953 --batch_size 676 --hidden_size 1704 --dropout 0.34204713115468621254 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07368968706578016281,,1,,n1720,18586444,368_0,FAILED,SOBOL,106,0.028902700413670389528730808593,676,1704,0.342047131154686212539672851562,3,0.073689687065780162811279296875,leaky_relu,normal
369,1753227557,29,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 51 --learning_rate 0.0922338839162141072 --batch_size 3488 --hidden_size 5392 --dropout 0.02986926073208451271 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.65521049778908491135,,1,,n1720,18586445,369_0,FAILED,SOBOL,51,0.092233883916214107201447802709,3488,5392,0.029869260732084512710571289062,2,0.655210497789084911346435546875,leaky_relu,normal
370,1753227558,28,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 92 --learning_rate 0.01028069751271977993 --batch_size 1703 --hidden_size 3660 --dropout 0.19340784940868616104 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.3638255242258310318,,1,,n1720,18586449,370_0,FAILED,SOBOL,92,0.010280697512719779926348984134,1703,3660,0.193407849408686161041259765625,1,0.36382552422583103179931640625,leaky_relu,normal
371,1753227553,33,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.07492890937756747916 --batch_size 2469 --hidden_size 7660 --dropout 0.38169531989842653275 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.90730432607233524323,,1,,n1720,18586442,371_0,FAILED,SOBOL,171,0.074928909377567479155324292606,2469,7660,0.381695319898426532745361328125,4,0.90730432607233524322509765625,leaky_relu,normal
372,1753227557,29,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 186 --learning_rate 0.01290721360230818321 --batch_size 3693 --hidden_size 6581 --dropout 0.49984694970771670341 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.48626325465738773346,,1,,n1720,18586447,372_0,FAILED,SOBOL,186,0.0129072136023081832090220189,3693,6581,0.499846949707716703414916992188,3,0.48626325465738773345947265625,leaky_relu,normal
373,1753227558,28,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 77 --learning_rate 0.05201332743670791792 --batch_size 371 --hidden_size 2595 --dropout 0.1865252065472304821 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78559949435293674469,,1,,n1720,18586448,373_0,FAILED,SOBOL,77,0.05201332743670791791679164362,371,2595,0.186525206547230482101440429688,2,0.78559949435293674468994140625,leaky_relu,normal
374,1753227552,34,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 12 --learning_rate 0.04498919270103797496 --batch_size 2651 --hidden_size 4441 --dropout 0.10117649286985397339 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.20125240366905927658,,1,,n1720,18586441,374_0,FAILED,SOBOL,12,0.044989192701037974964073384854,2651,4441,0.101176492869853973388671875,1,0.201252403669059276580810546875,leaky_relu,normal
375,1753227557,29,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 145 --learning_rate 0.08394895748011768633 --batch_size 1373 --hidden_size 767 --dropout 0.28838100656867027283 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.5269158361479640007,,1,,n1720,18586446,375_0,FAILED,SOBOL,145,0.083948957480117686325016279625,1373,767,0.2883810065686702728271484375,4,0.526915836147964000701904296875,leaky_relu,normal
376,1753227552,34,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 133 --learning_rate 0.0048936426597647369 --batch_size 3047 --hidden_size 2272 --dropout 0.04058325337246060371 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.40254195593297481537,,1,,n1720,18586440,376_0,FAILED,SOBOL,133,0.004893642659764736897731740584,3047,2272,0.040583253372460603713989257812,4,0.40254195593297481536865234375,leaky_relu,normal
377,1753227550,6,1753227556,1753227562,6,python3 .tests/mnist/train --epochs 24 --learning_rate 0.06629189218878746293 --batch_size 1258 --hidden_size 7033 --dropout 0.35287949861958622932 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82193461619317531586,,1,,n1720,18586438,377_0,FAILED,SOBOL,24,0.066291892188787462925070315123,1258,7033,0.352879498619586229324340820312,1,0.82193461619317531585693359375,leaky_relu,normal
378,1753227549,7,1753227556,1753227562,6,python3 .tests/mnist/train --epochs 65 --learning_rate 0.03739339162083343132 --batch_size 4057 --hidden_size 68 --dropout 0.42359744664281606674 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.15994298364967107773,,1,,n1720,18586437,378_0,FAILED,SOBOL,65,0.03739339162083343132136903364,4057,68,0.423597446642816066741943359375,2,0.159942983649671077728271484375,leaky_relu,normal
379,1753227858,30,1753227888,1753227894,6,python3 .tests/mnist/train --epochs 198 --learning_rate 0.09776726475078613421 --batch_size 224 --hidden_size 5013 --dropout 0.23542811255902051926 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.61555041279643774033,,1,,n1720,18586451,379_0,FAILED,SOBOL,198,0.097767264750786134208659916567,224,5013,0.235428112559020519256591796875,3,0.615550412796437740325927734375,leaky_relu,normal
380,1753227874,14,1753227888,1753227894,6,python3 .tests/mnist/train --epochs 159 --learning_rate 0.03964476651446894456 --batch_size 1813 --hidden_size 6091 --dropout 0.13290719082579016685 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.03775127138942480087,,1,,n1720,18586452,380_0,FAILED,SOBOL,159,0.039644766514468944562654684205,1813,6091,0.132907190825790166854858398438,4,0.037751271389424800872802734375,leaky_relu,normal
381,1753227878,15,1753227893,1753227899,6,python3 .tests/mnist/train --epochs 104 --learning_rate 0.07522053307238966979 --batch_size 2069 --hidden_size 1132 --dropout 0.44610316818580031395 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.73749750759452581406,,1,,n1720,18586453,381_0,FAILED,SOBOL,104,0.075220533072389669793089694849,2069,1132,0.446103168185800313949584960938,1,0.737497507594525814056396484375,leaky_relu,normal
382,1753228508,12,1753228520,1753228526,6,python3 .tests/mnist/train --epochs 39 --learning_rate 0.02139175343466922716 --batch_size 819 --hidden_size 7984 --dropout 0.26595303229987621307 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.2747331615537405014,,1,,n1720,18586459,382_0,FAILED,SOBOL,39,0.021391753434669227157405302364,819,7984,0.26595303229987621307373046875,2,0.27473316155374050140380859375,leaky_relu,normal
383,1753228508,12,1753228520,1753228533,13,python3 .tests/mnist/train --epochs 118 --learning_rate 0.05760163819864392437 --batch_size 3119 --hidden_size 3209 --dropout 0.07862251438200473785 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.9499870743602514267,,1,,n1720,18586458,383_0,FAILED,SOBOL,118,0.057601638198643924371200597534,3119,3209,0.07862251438200473785400390625,3,0.94998707436025142669677734375,leaky_relu,normal
384,1753228587,24,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 117 --learning_rate 0.02668166353190317905 --batch_size 1880 --hidden_size 7592 --dropout 0.30458817444741725922 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.16765619069337844849,,1,,n1720,18586462,384_0,FAILED,SOBOL,117,0.026681663531903179048532237516,1880,7592,0.30458817444741725921630859375,1,0.167656190693378448486328125,leaky_relu,normal
385,1753228591,20,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 38 --learning_rate 0.08821329097356647719 --batch_size 2135 --hidden_size 3599 --dropout 0.11640310473740100861 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.62324856966733932495,,1,,n1720,18586466,385_0,FAILED,SOBOL,38,0.08821329097356647719330169366,2135,3599,0.11640310473740100860595703125,4,0.623248569667339324951171875,leaky_relu,normal
386,1753228584,27,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 105 --learning_rate 0.00937456881767138872 --batch_size 886 --hidden_size 5444 --dropout 0.17154254158958792686 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39485910627990961075,,1,,n1720,18586460,386_0,FAILED,SOBOL,105,0.009374568817671388720746961098,886,5444,0.171542541589587926864624023438,3,0.394859106279909610748291015625,leaky_relu,normal
387,1753228587,24,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 160 --learning_rate 0.06958916789703072092 --batch_size 3186 --hidden_size 1778 --dropout 0.48388408636674284935 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.81426711473613977432,,1,,n1720,18586461,387_0,FAILED,SOBOL,160,0.069589167897030720921769386678,3186,1778,0.483884086366742849349975585938,2,0.814267114736139774322509765625,leaky_relu,normal
388,1753228587,25,1753228612,1753228619,7,python3 .tests/mnist/train --epochs 199 --learning_rate 0.01766557182511314592 --batch_size 2984 --hidden_size 700 --dropout 0.3969251653179526329 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.26680614147335290909,,1,,n1720,18586463,388_0,FAILED,SOBOL,199,0.017665571825113145915109313933,2984,700,0.396925165317952632904052734375,1,0.266806141473352909088134765625,leaky_relu,normal
389,1753228588,23,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 66 --learning_rate 0.05349664667434991111 --batch_size 1196 --hidden_size 4380 --dropout 0.20961038302630186081 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.94207546208053827286,,1,,n1720,18586465,389_0,FAILED,SOBOL,66,0.053496646674349911110279975901,1196,4380,0.209610383026301860809326171875,4,0.942075462080538272857666015625,leaky_relu,normal
390,1753228593,47,1753228640,1753228646,6,python3 .tests/mnist/train --epochs 23 --learning_rate 0.04960327440807596466 --batch_size 3995 --hidden_size 2649 --dropout 0.0139108230359852314 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.04570870846509933472,,1,,n1720,18586470,390_0,FAILED,SOBOL,23,0.049603274408075964663211721017,3995,2649,0.013910823035985231399536132812,3,0.045708708465099334716796875,leaky_relu,normal
391,1753228593,47,1753228640,1753228646,6,python3 .tests/mnist/train --epochs 132 --learning_rate 0.08558069831263274974 --batch_size 161 --hidden_size 6657 --dropout 0.32706150086596608162 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.7454397156834602356,,1,,n1720,18586472,391_0,FAILED,SOBOL,132,0.085580698312632749735762160981,161,6657,0.327061500865966081619262695312,2,0.745439715683460235595703125,leaky_relu,normal
392,1753228593,18,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 144 --learning_rate 0.00072538694934919481 --batch_size 3626 --hidden_size 5088 --dropout 0.06266313791275024414 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.3719813050702214241,,1,,n1720,18586467,392_0,FAILED,SOBOL,144,0.000725386949349194807244722849,3626,5088,0.062663137912750244140625,2,0.371981305070221424102783203125,leaky_relu,normal
393,1753228587,27,1753228614,1753228620,6,python3 .tests/mnist/train --epochs 12 --learning_rate 0.06421432610396296536 --batch_size 304 --hidden_size 121 --dropout 0.25096634402871131897 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.91547545511275529861,,1,,n1720,18586464,393_0,FAILED,SOBOL,12,0.064214326103962965364146953107,304,121,0.2509663440287113189697265625,3,0.915475455112755298614501953125,leaky_relu,normal
394,1753228593,52,1753228645,1753228651,6,python3 .tests/mnist/train --epochs 78 --learning_rate 0.03220283130658790904 --batch_size 2584 --hidden_size 6972 --dropout 0.46133392257615923882 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.06550324335694313049,,1,,n1720,18586471,394_0,FAILED,SOBOL,78,0.032202831306587909043770423523,2584,6972,0.461333922576159238815307617188,4,0.0655032433569431304931640625,leaky_relu,normal
395,1753228593,19,1753228612,1753228619,7,python3 .tests/mnist/train --epochs 187 --learning_rate 0.09671614686027170393 --batch_size 1306 --hidden_size 2206 --dropout 0.14911075262352824211 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.6470090039074420929,,1,,n1720,18586469,395_0,FAILED,SOBOL,187,0.096716146860271703933342735127,1306,2206,0.149110752623528242111206054688,1,0.6470090039074420928955078125,leaky_relu,normal
396,1753228593,18,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 172 --learning_rate 0.04088706231592223461 --batch_size 739 --hidden_size 3283 --dropout 0.22044656518846750259 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.19379847124218940735,,1,,n1720,18586468,396_0,FAILED,SOBOL,172,0.040887062315922234612131092035,739,3283,0.220446565188467502593994140625,2,0.1937984712421894073486328125,leaky_relu,normal
397,1753228825,27,1753228852,1753228858,6,python3 .tests/mnist/train --epochs 93 --learning_rate 0.08022410670220853079 --batch_size 3550 --hidden_size 8036 --dropout 0.40763534326106309891 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.51944667473435401917,,1,,n1720,18586474,397_0,FAILED,SOBOL,93,0.080224106702208530794706575762,3550,8036,0.407635343261063098907470703125,3,0.5194466747343540191650390625,leaky_relu,normal
398,1753229019,16,1753229035,1753229041,6,python3 .tests/mnist/train --epochs 50 --learning_rate 0.02326604801090434091 --batch_size 1765 --hidden_size 1071 --dropout 0.36908557871356606483 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.49368658382445573807,,1,,n1720,18586478,398_0,FAILED,SOBOL,50,0.023266048010904340909155152417,1765,1071,0.369085578713566064834594726562,4,0.493686583824455738067626953125,leaky_relu,normal
399,1753229045,17,1753229062,1753229068,6,python3 .tests/mnist/train --epochs 105 --learning_rate 0.06196897419113666511 --batch_size 2532 --hidden_size 6024 --dropout 0.0558091350831091404 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.79303823132067918777,,1,,n1720,18586481,399_0,FAILED,SOBOL,105,0.061968974191136665108370351618,2532,6024,0.055809135083109140396118164062,1,0.793038231320679187774658203125,leaky_relu,normal
400,1753235046,47,1753235093,1753235099,6,python3 .tests/mnist/train --epochs 111 --learning_rate 0.0198868121834471813 --batch_size 490 --hidden_size 2890 --dropout 0.49092468433082103729 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.56469120737165212631,,1,,n1720,18586661,400_0,FAILED,SOBOL,111,0.019886812183447181295870009876,490,2890,0.49092468433082103729248046875,3,0.564691207371652126312255859375,leaky_relu,normal
401,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 56 --learning_rate 0.05917508043618872893 --batch_size 3812 --hidden_size 6378 --dropout 0.17811351455748081207 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14808902796357870102,,1,,n1720,18586657,401_0,FAILED,SOBOL,56,0.059175080436188728927326963003,3812,6378,0.17811351455748081207275390625,2,0.148089027963578701019287109375,leaky_relu,normal
402,1753235043,17,1753235060,1753235067,7,python3 .tests/mnist/train --epochs 87 --learning_rate 0.03812010357379913561 --batch_size 1508 --hidden_size 938 --dropout 0.10837499191984534264 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.87282389216125011444,,1,,n1720,18586653,402_0,FAILED,SOBOL,87,0.03812010357379913561004514122,1508,938,0.108374991919845342636108398438,1,0.87282389216125011444091796875,leaky_relu,normal
403,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 166 --learning_rate 0.0768718122142367094 --batch_size 2786 --hidden_size 4114 --dropout 0.29509849613532423973 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.41442592255771160126,,1,,n1720,18586655,403_0,FAILED,SOBOL,166,0.076871812214236709404069358698,2786,4114,0.295098496135324239730834960938,4,0.41442592255771160125732421875,leaky_relu,normal
404,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 181 --learning_rate 0.03587163447812199979 --batch_size 3353 --hidden_size 5211 --dropout 0.33509277459233999252 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99282015673816204071,,1,,n1720,18586663,404_0,FAILED,SOBOL,181,0.035871634478121999789479446008,3353,5211,0.335092774592339992523193359375,3,0.99282015673816204071044921875,leaky_relu,normal
405,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 72 --learning_rate 0.09940935013843700541 --batch_size 542 --hidden_size 2048 --dropout 0.02339591365307569504 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29418599419295787811,,1,,n1720,18586660,405_0,FAILED,SOBOL,72,0.099409350138437005406366608895,542,2048,0.023395913653075695037841796875,2,0.29418599419295787811279296875,leaky_relu,normal
406,1753235035,24,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 18 --learning_rate 0.00339789516273885945 --batch_size 2351 --hidden_size 7347 --dropout 0.20257425354793667793 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.69469538982957601547,,1,,n1720,18586649,406_0,FAILED,SOBOL,18,0.003397895162738859449469419616,2351,7347,0.202574253547936677932739257812,1,0.694695389829576015472412109375,leaky_relu,normal
407,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 150 --learning_rate 0.067862428628373897 --batch_size 1584 --hidden_size 3873 --dropout 0.39035115065053105354 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.01832946296781301498,,1,,n1720,18586659,407_0,FAILED,SOBOL,150,0.067862428628373896999370629146,1584,3873,0.390351150650531053543090820312,4,0.018329462967813014984130859375,leaky_relu,normal
408,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 138 --learning_rate 0.04661684455703944685 --batch_size 2204 --hidden_size 1349 --dropout 0.12644874304533004761 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89596872217953205109,,1,,n1720,18586664,408_0,FAILED,SOBOL,138,0.04661684455703944685023287775,2204,1349,0.126448743045330047607421875,4,0.89596872217953205108642578125,leaky_relu,normal
409,1753235046,42,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 30 --learning_rate 0.08239914327273145656 --batch_size 1949 --hidden_size 5782 --dropout 0.43913390859961509705 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31336254067718982697,,1,,n1720,18586662,409_0,FAILED,SOBOL,30,0.082399143272731456555391105212,1949,5782,0.4391339085996150970458984375,1,0.31336254067718982696533203125,leaky_relu,normal
410,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 60 --learning_rate 0.01450580710656940858 --batch_size 3238 --hidden_size 3549 --dropout 0.2746235276572406292 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.66651609074324369431,,1,,n1720,18586656,410_0,FAILED,SOBOL,60,0.014505807106569408582164015797,3238,3549,0.274623527657240629196166992188,2,0.666516090743243694305419921875,leaky_relu,normal
411,1753235044,15,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 193 --learning_rate 0.05053201347133145366 --batch_size 938 --hidden_size 7799 --dropout 0.08777425764128565788 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.12412260007113218307,,1,,n1720,18586654,411_0,FAILED,SOBOL,193,0.050532013471331453657864329898,938,7799,0.087774257641285657882690429688,3,0.124122600071132183074951171875,leaky_relu,normal
412,1753235042,17,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 154 --learning_rate 0.01187638521902263135 --batch_size 1139 --hidden_size 6702 --dropout 0.03215690050274133682 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.54676584433764219284,,1,,n1720,18586652,412_0,FAILED,SOBOL,154,0.011876385219022631348217977632,1139,6702,0.032156900502741336822509765625,4,0.546765844337642192840576171875,leaky_relu,normal
413,1753235035,27,1753235062,1753235068,6,python3 .tests/mnist/train --epochs 99 --learning_rate 0.07345678916638717637 --batch_size 2928 --hidden_size 2439 --dropout 0.34397189784795045853 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24460479151457548141,,1,,n1720,18586651,413_0,FAILED,SOBOL,99,0.073456789166387176370776046497,2928,2439,0.343971897847950458526611328125,1,0.244604791514575481414794921875,leaky_relu,normal
414,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 44 --learning_rate 0.03052115851547568953 --batch_size 89 --hidden_size 4814 --dropout 0.43030003318563103676 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.76571846194565296173,,1,,n1720,18586658,414_0,FAILED,SOBOL,44,0.030521158515475689532170378016,89,4814,0.430300033185631036758422851562,2,0.76571846194565296173095703125,leaky_relu,normal
415,1753235035,24,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 123 --learning_rate 0.09068697550678626873 --batch_size 3923 --hidden_size 367 --dropout 0.24264151090756058693 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.4428799021989107132,,1,,n1720,18586650,415_0,FAILED,SOBOL,123,0.090686975506786268730330391463,3923,367,0.242641510907560586929321289062,3,0.44287990219891071319580078125,leaky_relu,normal
416,1753235786,26,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 127 --learning_rate 0.00708437176737934399 --batch_size 2639 --hidden_size 4048 --dropout 0.31646787328645586967 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.8581525823101401329,,1,,n1720,18586672,416_0,FAILED,SOBOL,127,0.007084371767379343994008866758,2639,4048,0.316467873286455869674682617188,3,0.858152582310140132904052734375,leaky_relu,normal
417,1753235785,27,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 42 --learning_rate 0.07042084528850392489 --batch_size 1362 --hidden_size 7267 --dropout 0.00466801552101969719 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43275934364646673203,,1,,n1720,18586670,417_0,FAILED,SOBOL,42,0.070420845288503924885858964444,1362,7267,0.004668015521019697189331054688,2,0.432759343646466732025146484375,leaky_relu,normal
418,1753235784,28,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 95 --learning_rate 0.02594754398986697311 --batch_size 3698 --hidden_size 1840 --dropout 0.21519863605499267578 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.57936260662972927094,,1,,n1720,18586668,418_0,FAILED,SOBOL,95,0.025947543989866973107583092428,3698,1840,0.21519863605499267578125,1,0.57936260662972927093505859375,leaky_relu,normal
419,1753235797,15,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 156 --learning_rate 0.09060104736192152453 --batch_size 375 --hidden_size 5258 --dropout 0.40287253633141517639 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.12975551746785640717,,1,,n1720,18586677,419_0,FAILED,SOBOL,156,0.090601047361921524525563143015,375,5258,0.4028725363314151763916015625,4,0.12975551746785640716552734375,leaky_relu,normal
420,1753235787,25,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 189 --learning_rate 0.04731136134415865613 --batch_size 1726 --hidden_size 4323 --dropout 0.47414538124576210976 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.7071694936603307724,,1,,n1720,18586673,420_0,FAILED,SOBOL,189,0.047311361344158656128122686368,1726,4323,0.474145381245762109756469726562,3,0.70716949366033077239990234375,leaky_relu,normal
421,1753235784,28,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 62 --learning_rate 0.08641066117910668753 --batch_size 2493 --hidden_size 891 --dropout 0.16144483769312500954 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.00170496664941310883,,1,,n1720,18586669,421_0,FAILED,SOBOL,62,0.086410661179106687534989816868,2493,891,0.161444837693125009536743164062,2,0.00170496664941310882568359375,leaky_relu,normal
422,1753235797,44,1753235841,1753235847,6,python3 .tests/mnist/train --epochs 33 --learning_rate 0.01693316829670220638 --batch_size 652 --hidden_size 6203 --dropout 0.12284640315920114517 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.98034620191901922226,,1,,n1720,18586678,422_0,FAILED,SOBOL,33,0.016933168296702206384596323119,652,6203,0.122846403159201145172119140625,1,0.980346201919019222259521484375,leaky_relu,normal
423,1753235797,15,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 136 --learning_rate 0.05588611758770421767 --batch_size 3464 --hidden_size 2971 --dropout 0.30968053359538316727 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.31081034149974584579,,1,,n1720,18586676,423_0,FAILED,SOBOL,136,0.055886117587704217668509443229,3464,2971,0.309680533595383167266845703125,4,0.310810341499745845794677734375,leaky_relu,normal
424,1753235797,44,1753235841,1753235847,6,python3 .tests/mnist/train --epochs 148 --learning_rate 0.03302964963670820125 --batch_size 829 --hidden_size 447 --dropout 0.05065567931160330772 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68161473609507083893,,1,,n1720,18586679,424_0,FAILED,SOBOL,148,0.033029649636708201254631234178,829,447,0.050655679311603307723999023438,4,0.68161473609507083892822265625,leaky_relu,normal
425,1753235797,44,1753235841,1753235847,6,python3 .tests/mnist/train --epochs 21 --learning_rate 0.09442109112078324318 --batch_size 3129 --hidden_size 4638 --dropout 0.36233716225251555443 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10585012473165988922,,1,,n1720,18586680,425_0,FAILED,SOBOL,21,0.094421091120783243177960741832,3129,4638,0.362337162252515554428100585938,1,0.10585012473165988922119140625,leaky_relu,normal
426,1753235786,26,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 74 --learning_rate 0.00311800202690064917 --batch_size 1807 --hidden_size 2391 --dropout 0.41755000315606594086 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.88087016623467206955,,1,,n1720,18586671,426_0,FAILED,SOBOL,74,0.003118002026900649169272039529,1807,2391,0.41755000315606594085693359375,2,0.880870166234672069549560546875,leaky_relu,normal
427,1753235788,24,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 177 --learning_rate 0.06348506562327967118 --batch_size 2063 --hidden_size 6910 --dropout 0.22975796647369861603 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.33163492660969495773,,1,,n1720,18586674,427_0,FAILED,SOBOL,177,0.06348506562327967117642657513,2063,6910,0.22975796647369861602783203125,3,0.331634926609694957733154296875,leaky_relu,normal
428,1753235797,15,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.02409458161033689941 --batch_size 4036 --hidden_size 7846 --dropout 0.14285825984552502632 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75330554228276014328,,1,,n1720,18586675,428_0,FAILED,SOBOL,168,0.024094581610336899407665001149,4036,7846,0.142858259845525026321411132812,4,0.753305542282760143280029296875,leaky_relu,normal
429,1753235993,30,1753236023,1753236029,6,python3 .tests/mnist/train --epochs 83 --learning_rate 0.0596756322323344704 --batch_size 203 --hidden_size 3341 --dropout 0.45568456919863820076 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45993149559944868088,,1,,n1720,18586682,429_0,FAILED,SOBOL,83,0.059675632232334470395063164005,203,3341,0.455684569198638200759887695312,1,0.459931495599448680877685546875,leaky_relu,normal
430,1753235993,32,1753236025,1753236032,7,python3 .tests/mnist/train --epochs 54 --learning_rate 0.04327796212416142735 --batch_size 3074 --hidden_size 5702 --dropout 0.25978185143321752548 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.55917891301214694977,,1,,n1720,18586683,430_0,FAILED,SOBOL,54,0.043277962124161427348578712326,3074,5702,0.259781851433217525482177734375,2,0.55917891301214694976806640625,leaky_relu,normal
431,1753235994,29,1753236023,1753236029,6,python3 .tests/mnist/train --epochs 115 --learning_rate 0.07949313244083897056 --batch_size 1284 --hidden_size 1524 --dropout 0.07307372521609067917 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.22755304910242557526,,1,,n1720,18586684,431_0,FAILED,SOBOL,115,0.079493132440838970564911392103,1284,1524,0.073073725216090679168701171875,3,0.22755304910242557525634765625,leaky_relu,normal
432,1753236541,24,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 109 --learning_rate 0.04041049228468910487 --batch_size 3327 --hidden_size 6448 --dropout 0.38013131869956851006 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.38201887905597686768,,1,,n1720,18586707,432_0,FAILED,SOBOL,109,0.040410492284689104869332965109,3327,6448,0.380131318699568510055541992188,1,0.38201887905597686767578125,leaky_relu,normal
433,1753236550,15,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 48 --learning_rate 0.07604032499473542539 --batch_size 1027 --hidden_size 2697 --dropout 0.19295768020674586296 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.83076944947242736816,,1,,n1720,18586714,433_0,FAILED,SOBOL,48,0.076040324994735425390146588143,1027,2697,0.192957680206745862960815429688,4,0.8307694494724273681640625,leaky_relu,normal
434,1753236541,24,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 89 --learning_rate 0.02062074006488546704 --batch_size 2245 --hidden_size 4556 --dropout 0.02836626023054122925 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.18049656692892313004,,1,,n1720,18586708,434_0,FAILED,SOBOL,89,0.020620740064885467041078115358,2245,4556,0.028366260230541229248046875,3,0.180496566928923130035400390625,leaky_relu,normal
435,1753236548,17,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 174 --learning_rate 0.05678713387586176858 --batch_size 1989 --hidden_size 620 --dropout 0.34165808185935020447 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60674608591943979263,,1,,n1720,18586712,435_0,FAILED,SOBOL,174,0.056787133875861768583792610343,1989,620,0.3416580818593502044677734375,2,0.606746085919439792633056640625,leaky_relu,normal
436,1753236542,23,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 183 --learning_rate 0.00568961656605824866 --batch_size 16 --hidden_size 1603 --dropout 0.28597781667485833168 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.06025797966867685318,,1,,n1720,18586709,436_0,FAILED,SOBOL,183,0.005689616566058248656179152647,16,1603,0.285977816674858331680297851562,1,0.060257979668676853179931640625,leaky_relu,normal
437,1753236549,16,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 80 --learning_rate 0.06703227558992803925 --batch_size 3849 --hidden_size 5525 --dropout 0.09765923256054520607 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.72674005571752786636,,1,,n1720,18586713,437_0,FAILED,SOBOL,80,0.067032275589928039249976166047,3849,5525,0.097659232560545206069946289062,4,0.726740055717527866363525390625,leaky_relu,normal
438,1753236551,14,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 15 --learning_rate 0.03660422966713085952 --batch_size 1082 --hidden_size 3807 --dropout 0.1841828981414437294 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25225695967674255371,,1,,n1720,18586716,438_0,FAILED,SOBOL,15,0.036604229667130859515733476428,1082,3807,0.184182898141443729400634765625,3,0.2522569596767425537109375,leaky_relu,normal
439,1753236545,20,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 142 --learning_rate 0.09702006939705461186 --batch_size 2871 --hidden_size 7545 --dropout 0.49639092851430177689 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.960775032639503479,,1,,n1720,18586710,439_0,FAILED,SOBOL,142,0.097020069397054611859410044872,2871,7545,0.496390928514301776885986328125,2,0.96077503263950347900390625,leaky_relu,normal
440,1753236550,15,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 130 --learning_rate 0.01367879786016419456 --batch_size 1421 --hidden_size 5976 --dropout 0.2368701486848294735 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.07852672506123781204,,1,,n1720,18586715,440_0,FAILED,SOBOL,130,0.013678797860164194563625805756,1421,5976,0.236870148684829473495483398438,2,0.078526725061237812042236328125,leaky_relu,normal
441,1753236545,20,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.05282687978316098765 --batch_size 2698 --hidden_size 1279 --dropout 0.42416955297812819481 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.63081169594079256058,,1,,n1720,18586711,441_0,FAILED,SOBOL,27,0.052826879783160987646972728271,2698,1279,0.424169552978128194808959960938,3,0.630811695940792560577392578125,leaky_relu,normal
442,1753236713,32,1753236745,1753236751,6,python3 .tests/mnist/train --epochs 68 --learning_rate 0.0442244203957729079 --batch_size 450 --hidden_size 8116 --dropout 0.35426035337150096893 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.35895797237753868103,,1,,n1720,18586767,442_0,FAILED,SOBOL,68,0.044224420395772907899090142791,450,8116,0.35426035337150096893310546875,4,0.3589579723775386810302734375,leaky_relu,normal
443,1753236714,31,1753236745,1753236751,6,python3 .tests/mnist/train --epochs 195 --learning_rate 0.08312859318107367057 --batch_size 3773 --hidden_size 3107 --dropout 0.04109453596174716949 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93167261406779289246,,1,,n1720,18586768,443_0,FAILED,SOBOL,195,0.083128593181073670570491174203,3773,3107,0.04109453596174716949462890625,1,0.9316726140677928924560546875,leaky_relu,normal
444,1753236716,29,1753236745,1753236751,6,python3 .tests/mnist/train --epochs 162 --learning_rate 0.02969281583232805111 --batch_size 2422 --hidden_size 2125 --dropout 0.08114785002544522285 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.47944257780909538269,,1,,n1720,18586769,444_0,FAILED,SOBOL,162,0.029692815832328051106614452692,2422,2125,0.081147850025445222854614257812,2,0.4794425778090953826904296875,leaky_relu,normal
445,1753236893,33,1753236926,1753236932,6,python3 .tests/mnist/train --epochs 101 --learning_rate 0.09298050689324736939 --batch_size 1655 --hidden_size 7148 --dropout 0.26934805931523442268 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.81192090734839439392,,1,,n1720,18586773,445_0,FAILED,SOBOL,101,0.092980506893247369393229462275,1655,7148,0.269348059315234422683715820312,3,0.8119209073483943939208984375,leaky_relu,normal
446,1753236901,25,1753236926,1753236932,6,python3 .tests/mnist/train --epochs 36 --learning_rate 0.00948529449449852027 --batch_size 3408 --hidden_size 168 --dropout 0.4485674416646361351 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.20804256666451692581,,1,,n1720,18586774,446_0,FAILED,SOBOL,36,0.009485294494498520273539909908,3408,168,0.448567441664636135101318359375,4,0.208042566664516925811767578125,leaky_relu,normal
447,1753236914,12,1753236926,1753236932,6,python3 .tests/mnist/train --epochs 121 --learning_rate 0.07418757400009781677 --batch_size 597 --hidden_size 4879 --dropout 0.1362412748858332634 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.50056390929967164993,,1,,n1720,18586775,447_0,FAILED,SOBOL,121,0.074187574000097816773191539141,597,4879,0.136241274885833263397216796875,1,0.500563909299671649932861328125,leaky_relu,normal
448,1753237138,29,1753237167,1753237173,6,python3 .tests/mnist/train --epochs 122 --learning_rate 0.0159792801066301754 --batch_size 3569 --hidden_size 1159 --dropout 0.00104593485593795776 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.69918790459632873535,,1,,n1720,18586778,448_0,FAILED,SOBOL,122,0.015979280106630175395387993831,3569,1159,0.001045934855937957763671875,2,0.6991879045963287353515625,leaky_relu,normal
449,1753237139,28,1753237167,1753237173,6,python3 .tests/mnist/train --epochs 34 --learning_rate 0.05528049698658287631 --batch_size 757 --hidden_size 5936 --dropout 0.3142308257520198822 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02971322834491729736,,1,,n1720,18586779,449_0,FAILED,SOBOL,34,0.055280496986582876306481892925,757,5936,0.3142308257520198822021484375,3,0.02971322834491729736328125,leaky_relu,normal
450,1753243795,25,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 100 --learning_rate 0.04825843776771799459 --batch_size 2518 --hidden_size 3179 --dropout 0.39977647317573428154 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.98832715395838022232,,1,,n1720,18586944,450_0,FAILED,SOBOL,100,0.048258437767717994593130725889,2518,3179,0.399776473175734281539916992188,4,0.988327153958380222320556640625,leaky_relu,normal
451,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 164 --learning_rate 0.08702309354674071795 --batch_size 1752 --hidden_size 8140 --dropout 0.21243510721251368523 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.28280174080282449722,,1,,n1720,18586953,451_0,FAILED,SOBOL,164,0.087023093546740717951770704985,1752,8140,0.212435107212513685226440429688,1,0.282801740802824497222900390625,leaky_relu,normal
452,1753243789,31,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 196 --learning_rate 0.02573311104262247795 --batch_size 290 --hidden_size 7060 --dropout 0.15675480756908655167 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86076491419225931168,,1,,n1720,18586936,452_0,FAILED,SOBOL,196,0.025733111042622477948604853282,290,7060,0.156754807569086551666259765625,2,0.860764914192259311676025390625,leaky_relu,normal
453,1753243787,33,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 66 --learning_rate 0.08925940205659717297 --batch_size 3612 --hidden_size 2118 --dropout 0.46906953025609254837 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.41109687928110361099,,1,,n1720,18586933,453_0,FAILED,SOBOL,66,0.089259402056597172969709674817,3612,2118,0.469069530256092548370361328125,3,0.411096879281103610992431640625,leaky_relu,normal
454,1753243797,26,1753243823,1753243829,6,python3 .tests/mnist/train --epochs 26 --learning_rate 0.00730409250026568813 --batch_size 1324 --hidden_size 4984 --dropout 0.30545607814565300941 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57675065100193023682,,1,,n1720,18586946,454_0,FAILED,SOBOL,26,0.007304092500265688125971053068,1324,4984,0.305456078145653009414672851562,4,0.57675065100193023681640625,leaky_relu,normal
455,1753243798,51,1753243849,1753243862,13,python3 .tests/mnist/train --epochs 131 --learning_rate 0.07175720280818641272 --batch_size 2602 --hidden_size 225 --dropout 0.11730545992031693459 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15141853690147399902,,1,,n1720,18586950,455_0,FAILED,SOBOL,131,0.071757202808186412723578939676,2602,225,0.117305459920316934585571289062,1,0.1514185369014739990234375,leaky_relu,normal
456,1753243789,31,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.04271892974851653618 --batch_size 1179 --hidden_size 2817 --dropout 0.3660778682678937912 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77802014816552400589,,1,,n1720,18586938,456_0,FAILED,SOBOL,143,0.042718929748516536182290082024,1179,2817,0.36607786826789379119873046875,1,0.778020148165524005889892578125,leaky_relu,normal
457,1753243790,30,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 14 --learning_rate 0.07848979786336422737 --batch_size 2968 --hidden_size 6489 --dropout 0.05277460254728794098 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.44645546842366456985,,1,,n1720,18586939,457_0,FAILED,SOBOL,14,0.078489797863364227370475134649,2968,6489,0.05277460254728794097900390625,4,0.446455468423664569854736328125,leaky_relu,normal
458,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 78 --learning_rate 0.02465890177162364041 --batch_size 177 --hidden_size 549 --dropout 0.23297194531187415123 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.53446463868021965027,,1,,n1720,18586952,458_0,FAILED,SOBOL,78,0.024658901771623640414299316603,177,549,0.232971945311874151229858398438,3,0.5344646386802196502685546875,leaky_relu,normal
459,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 184 --learning_rate 0.06067367902416736375 --batch_size 4010 --hidden_size 4532 --dropout 0.42019517486914992332 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.24102970585227012634,,1,,n1720,18586948,459_0,FAILED,SOBOL,184,0.060673679024167363749153736308,4010,4532,0.420195174869149923324584960938,2,0.2410297058522701263427734375,leaky_relu,normal
460,1753243788,32,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 176 --learning_rate 0.00172195655899122372 --batch_size 2148 --hidden_size 5612 --dropout 0.46024858113378286362 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.66227295622229576111,,1,,n1720,18586935,460_0,FAILED,SOBOL,176,0.001721956558991223715932017413,2148,5612,0.460248581133782863616943359375,1,0.6622729562222957611083984375,leaky_relu,normal
461,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 88 --learning_rate 0.06331531508807093644 --batch_size 1892 --hidden_size 1610 --dropout 0.14805962424725294113 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11297677084803581238,,1,,n1720,18586949,461_0,FAILED,SOBOL,88,0.063315315088070936444530900644,1892,1610,0.148059624247252941131591796875,4,0.1129767708480358123779296875,leaky_relu,normal
462,1753243789,31,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 46 --learning_rate 0.03441888333810493722 --batch_size 3166 --hidden_size 7440 --dropout 0.07717239903286099434 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90021138358861207962,,1,,n1720,18586937,462_0,FAILED,SOBOL,46,0.034418883338104937219537049486,3166,7440,0.077172399032860994338989257812,3,0.900211383588612079620361328125,leaky_relu,normal
463,1753243796,24,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 110 --learning_rate 0.0945976534225046739 --batch_size 866 --hidden_size 3750 --dropout 0.26544902147725224495 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.324507896788418293,,1,,n1720,18586945,463_0,FAILED,SOBOL,110,0.094597653422504673903503658039,866,3750,0.265449021477252244949340820312,2,0.324507896788418292999267578125,leaky_relu,normal
464,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 116 --learning_rate 0.03681942479088903125 --batch_size 2913 --hidden_size 4710 --dropout 0.1877562403678894043 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.03359824325889348984,,1,,n1720,18586947,464_0,FAILED,SOBOL,116,0.036819424790889031251506224862,2913,4710,0.187756240367889404296875,4,0.033598243258893489837646484375,leaky_relu,normal
465,1753243793,27,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.0983640012319199758 --batch_size 1124 --hidden_size 470 --dropout 0.37556735053658485413 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.74217744078487157822,,1,,n1720,18586942,465_0,FAILED,SOBOL,52,0.098364001231919975798412281165,1124,470,0.3755673505365848541259765625,1,0.742177440784871578216552734375,leaky_relu,normal
466,1753244584,20,1753244604,1753244610,6,python3 .tests/mnist/train --epochs 82 --learning_rate 0.00546760930363088867 --batch_size 3939 --hidden_size 6790 --dropout 0.33599095745012164116 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.27891709469258785248,,1,,n1720,18586981,466_0,FAILED,SOBOL,82,0.005467609303630888671621246289,3939,6790,0.335990957450121641159057617188,2,0.27891709469258785247802734375,leaky_relu,normal
467,1753244591,12,1753244603,1753244609,6,python3 .tests/mnist/train --epochs 170 --learning_rate 0.06569515589373187137 --batch_size 106 --hidden_size 2351 --dropout 0.02426751283928751945 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.94533822499215602875,,1,,n1720,18586984,467_0,FAILED,SOBOL,170,0.065695155893731871366014729574,106,2351,0.024267512839287519454956054688,3,0.94533822499215602874755859375,leaky_relu,normal
468,1753244582,20,1753244602,1753244609,7,python3 .tests/mnist/train --epochs 178 --learning_rate 0.02157234172541648218 --batch_size 1968 --hidden_size 3445 --dropout 0.09554038289934396744 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.39939931593835353851,,1,,n1720,18586979,468_0,FAILED,SOBOL,178,0.021572341725416482177690724598,1968,3445,0.095540382899343967437744140625,4,0.39939931593835353851318359375,leaky_relu,normal
469,1753244585,16,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 72 --learning_rate 0.0573919923004694299 --batch_size 2224 --hidden_size 7903 --dropout 0.28223706502467393875 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82558794878423213959,,1,,n1720,18586982,469_0,FAILED,SOBOL,72,0.057391992300469429899578699406,2224,7903,0.282237065024673938751220703125,1,0.82558794878423213958740234375,leaky_relu,normal
470,1753244593,8,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 20 --learning_rate 0.03946417803764343951 --batch_size 926 --hidden_size 1437 --dropout 0.49374571302905678749 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.16311551537364721298,,1,,n1720,18586986,470_0,FAILED,SOBOL,20,0.039464178037643439511672482922,926,1437,0.493745713029056787490844726562,2,0.163115515373647212982177734375,leaky_relu,normal
471,1753244594,7,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 149 --learning_rate 0.07543017915664240736 --batch_size 3226 --hidden_size 5694 --dropout 0.18096899474039673805 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.61192726995795965195,,1,,n1720,18586988,471_0,FAILED,SOBOL,149,0.07543017915664240735651446812,3226,5694,0.180968994740396738052368164062,3,0.611927269957959651947021484375,leaky_relu,normal
472,1753244587,15,1753244602,1753244609,7,python3 .tests/mnist/train --epochs 138 --learning_rate 0.01087905343286693118 --batch_size 555 --hidden_size 7195 --dropout 0.42924544773995876312 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.48938431777060031891,,1,,n1720,18586983,472_0,FAILED,SOBOL,138,0.010879053432866931175326818959,555,7195,0.42924544773995876312255859375,3,0.48938431777060031890869140625,leaky_relu,normal
473,1753244584,18,1753244602,1753244609,7,python3 .tests/mnist/train --epochs 32 --learning_rate 0.07435656235879287146 --batch_size 3367 --hidden_size 4025 --dropout 0.24156010337173938751 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78196678496897220612,,1,,n1720,18586980,473_0,FAILED,SOBOL,32,0.074356562358792871458845752386,3367,4025,0.24156010337173938751220703125,2,0.78196678496897220611572265625,leaky_relu,normal
474,1753244594,7,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 60 --learning_rate 0.02830434430744498825 --batch_size 1566 --hidden_size 5379 --dropout 0.04663540562614798546 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.19810025673359632492,,1,,n1720,18586987,474_0,FAILED,SOBOL,60,0.028304344307444988249056194718,1566,5379,0.046635405626147985458374023438,1,0.198100256733596324920654296875,leaky_relu,normal
475,1753244594,36,1753244630,1753244636,6,python3 .tests/mnist/train --epochs 190 --learning_rate 0.09280623112106696493 --batch_size 2332 --hidden_size 1881 --dropout 0.35848485445603728294 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.53051764052361249924,,1,,n1720,18586989,475_0,FAILED,SOBOL,190,0.092806231121066964928623121978,2332,1881,0.358484854456037282943725585938,4,0.530517640523612499237060546875,leaky_relu,normal
476,1753244591,10,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 158 --learning_rate 0.04478421494793147217 --batch_size 3794 --hidden_size 786 --dropout 0.271585061214864254 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07786023896187543869,,1,,n1720,18586985,476_0,FAILED,SOBOL,158,0.044784214947931472172726330427,3794,786,0.271585061214864253997802734375,3,0.077860238961875438690185546875,leaky_relu,normal
477,1753244975,16,1753244991,1753244998,7,python3 .tests/mnist/train --epochs 94 --learning_rate 0.08413421428808942615 --batch_size 472 --hidden_size 4266 --dropout 0.0847700042650103569 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.65051399450749158859,,1,,n1720,18586992,477_0,FAILED,SOBOL,94,0.084134214288089426148076199752,472,4266,0.084770004265010356903076171875,2,0.650513994507491588592529296875,leaky_relu,normal
478,1753244992,28,1753245020,1753245027,7,python3 .tests/mnist/train --epochs 40 --learning_rate 0.0131121911693364377 --batch_size 2800 --hidden_size 3058 --dropout 0.13900487916544079781 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.35962478257715702057,,1,,n1720,18586994,478_0,FAILED,SOBOL,40,0.013112191169336437704395770254,2800,3058,0.139004879165440797805786132812,1,0.35962478257715702056884765625,leaky_relu,normal
479,1753244992,28,1753245020,1753245027,7,python3 .tests/mnist/train --epochs 128 --learning_rate 0.05182807081481442119 --batch_size 1522 --hidden_size 6210 --dropout 0.45166346104815602303 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.91197093762457370758,,1,,n1720,18586995,479_0,FAILED,SOBOL,128,0.051828070814814421185534598635,1522,6210,0.451663461048156023025512695312,4,0.91197093762457370758056640625,leaky_relu,normal
480,1753244995,25,1753245020,1753245027,7,python3 .tests/mnist/train --epochs 125 --learning_rate 0.04899084111005068409 --batch_size 248 --hidden_size 5870 --dropout 0.11221311381086707115 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.26455102022737264633,,1,,n1720,18586996,480_0,FAILED,SOBOL,125,0.048990841110050684092946937653,248,5870,0.112213113810867071151733398438,4,0.264551020227372646331787109375,leaky_relu,normal
481,1753244981,10,1753244991,1753244998,7,python3 .tests/mnist/train --epochs 43 --learning_rate 0.08463362281946465449 --batch_size 4081 --hidden_size 1357 --dropout 0.29901279276236891747 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96434297319501638412,,1,,n1720,18586993,481_0,FAILED,SOBOL,43,0.0846336228194646544853441128,4081,1357,0.299012792762368917465209960938,1,0.964342973195016384124755859375,leaky_relu,normal
482,1753245346,6,1753245352,1753245358,6,python3 .tests/mnist/train --epochs 97 --learning_rate 0.0182711929844692339 --batch_size 1234 --hidden_size 7694 --dropout 0.47916725091636180878 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.04796440713107585907,,1,,n1720,18586999,482_0,FAILED,SOBOL,97,0.01827119298446923389978024943,1234,7694,0.47916725091636180877685546875,2,0.04796440713107585906982421875,leaky_relu,normal
483,1753245745,563,1753246308,1753246314,6,python3 .tests/mnist/train --epochs 155 --learning_rate 0.05445053430618718854 --batch_size 3023 --hidden_size 3493 --dropout 0.16649352945387363434 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.72317260317504405975,,1,,n1720,18587003,483_0,FAILED,SOBOL,155,0.054450534306187188537951016087,3023,3493,0.16649352945387363433837890625,3,0.72317260317504405975341796875,leaky_relu,normal
484,1753245755,553,1753246308,1753246314,6,python3 .tests/mnist/train --epochs 194 --learning_rate 0.0080382118562236423 --batch_size 3080 --hidden_size 2559 --dropout 0.2064877157099545002 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.1762610655277967453,,1,,n1720,18587004,484_0,FAILED,SOBOL,194,0.00803821185622364230149994313,3080,2559,0.206487715709954500198364257812,4,0.17626106552779674530029296875,leaky_relu,normal
485,1753245810,500,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 59 --learning_rate 0.06936944660590961542 --batch_size 779 --hidden_size 6742 --dropout 0.39418819965794682503 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.5956078898161649704,,1,,n1720,18587007,485_0,FAILED,SOBOL,59,0.06936944660590961542201426937,779,6742,0.394188199657946825027465820312,1,0.59560788981616497039794921875,leaky_relu,normal
486,1753245810,499,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.02802330790683627004 --batch_size 2109 --hidden_size 295 --dropout 0.32347362395375967026 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38625391479581594467,,1,,n1720,18587006,486_0,FAILED,SOBOL,27,0.028023307906836270042560954607,2109,295,0.323473623953759670257568359375,2,0.386253914795815944671630859375,leaky_relu,normal
487,1753245812,497,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.08842772485120221904 --batch_size 1854 --hidden_size 4790 --dropout 0.01163955312222242355 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.84190717991441488266,,1,,n1720,18587008,487_0,FAILED,SOBOL,140,0.0884277248512022190363168761,1854,4790,0.011639553122222423553466796875,3,0.841907179914414882659912109375,leaky_relu,normal
488,1753245810,499,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 151 --learning_rate 0.02226800177730619765 --batch_size 2446 --hidden_size 6291 --dropout 0.25503845466300845146 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21252745576202869415,,1,,n1720,18587005,488_0,FAILED,SOBOL,151,0.022268001777306197647154917263,2446,6291,0.255038454663008451461791992188,3,0.21252745576202869415283203125,leaky_relu,normal
489,1753245817,492,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 16 --learning_rate 0.06140465347161516707 --batch_size 1679 --hidden_size 2883 --dropout 0.06835691211745142937 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.51194004900753498077,,1,,n1720,18587012,489_0,FAILED,SOBOL,16,0.061404653471615167070751795109,1679,2883,0.068356912117451429367065429688,2,0.51194004900753498077392578125,leaky_relu,normal
490,1753245817,492,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 71 --learning_rate 0.04189039596300572765 --batch_size 3512 --hidden_size 4219 --dropout 0.15370898693799972534 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.47495720814913511276,,1,,n1720,18587013,490_0,FAILED,SOBOL,71,0.041890395963005727653083454243,3512,4219,0.153708986937999725341796875,1,0.474957208149135112762451171875,leaky_relu,normal
491,1753245819,490,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 182 --learning_rate 0.08078314000824467211 --batch_size 701 --hidden_size 995 --dropout 0.46650108322501182556 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.80054428707808256149,,1,,n1720,18587016,491_0,FAILED,SOBOL,182,0.08078314000824467211447910131,701,995,0.4665010832250118255615234375,4,0.800544287078082561492919921875,leaky_relu,normal
492,1753245815,495,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 167 --learning_rate 0.0320262680744752351 --batch_size 1413 --hidden_size 1928 --dropout 0.41088376054540276527 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.34690662752836942673,,1,,n1720,18587011,492_0,FAILED,SOBOL,167,0.032026268074475235103637515977,1413,1928,0.410883760545402765274047851562,3,0.346906627528369426727294921875,leaky_relu,normal
493,1753245813,496,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 85 --learning_rate 0.09532691408926621812 --batch_size 2691 --hidden_size 5170 --dropout 0.22305727237835526466 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92835120391100645065,,1,,n1720,18587010,493_0,FAILED,SOBOL,85,0.095326914089266218121920815065,2691,5170,0.223057272378355264663696289062,2,0.928351203911006450653076171875,leaky_relu,normal
494,1753245819,491,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 55 --learning_rate 0.0008951380427926779 --batch_size 331 --hidden_size 3944 --dropout 0.05952300224453210831 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.09057854302227497101,,1,,n1720,18587015,494_0,FAILED,SOBOL,55,0.000895138042792677896507258506,331,3944,0.059523002244532108306884765625,1,0.09057854302227497100830078125,leaky_relu,normal
495,1753245818,491,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 113 --learning_rate 0.06561037101363763335 --batch_size 3653 --hidden_size 7371 --dropout 0.37123130727559328079 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63413357920944690704,,1,,n1720,18587014,495_0,FAILED,SOBOL,113,0.065610371013637633352821865174,3653,7371,0.371231307275593280792236328125,4,0.63413357920944690704345703125,leaky_relu,normal
496,1753246157,153,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 107 --learning_rate 0.00473501430070027724 --batch_size 1606 --hidden_size 17 --dropout 0.17550273379310965538 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.97603630274534225464,,1,,n1720,18587018,496_0,FAILED,SOBOL,107,0.004735014300700277241340518941,1606,17,0.175502733793109655380249023438,2,0.976036302745342254638671875,leaky_relu,normal
497,1753246172,138,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 49 --learning_rate 0.068084436449036001 --batch_size 2373 --hidden_size 5031 --dropout 0.48767631268128752708 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.29973126202821731567,,1,,n1720,18587019,497_0,FAILED,SOBOL,49,0.068084436449036001004486706734,2373,5031,0.487676312681287527084350585938,3,0.299731262028217315673828125,leaky_relu,normal
498,1753246218,92,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 91 --learning_rate 0.03452770357364789294 --batch_size 644 --hidden_size 2293 --dropout 0.2929528113454580307 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71147890482097864151,,1,,n1720,18587020,498_0,FAILED,SOBOL,91,0.034527703573647892942855008869,644,2293,0.29295281134545803070068359375,4,0.711478904820978641510009765625,leaky_relu,normal
499,1753246342,32,1753246374,1753246380,6,python3 .tests/mnist/train --epochs 173 --learning_rate 0.09919415408428758352 --batch_size 3455 --hidden_size 6980 --dropout 0.10466104932129383087 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.01278355810791254044,,1,,n1720,18587021,499_0,FAILED,SOBOL,173,0.099194154084287583517109965214,3455,6980,0.10466104932129383087158203125,1,0.012783558107912540435791015625,leaky_relu,normal
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select {
border: 1px solid #7f9db9;
background-image: url("data:image/svg+xml;charset=utf-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 -0.5 15 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e6eefc' d='M0 0h1'/%3E%3Cpath stroke='%23d1e0fd' d='M1 0h1M0 1h1m3 0h2M2 3h1M2 4h1'/%3E%3Cpath stroke='%23cad8f9' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23c4d3f7' d='M3 0h1M0 3h1M0 4h1'/%3E%3Cpath stroke='%23bfd0f8' d='M4 0h2M0 5h1'/%3E%3Cpath stroke='%23bdcef7' d='M6 0h1M0 6h1'/%3E%3Cpath stroke='%23baccf4' d='M7 0h1m6 2h1m-1 5h1m-1 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M8 0h1M0 7h1M0 8h1'/%3E%3Cpath stroke='%23b7caf5' d='M9 0h2M0 9h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 0h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 0h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 0h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 0h1'/%3E%3Cpath stroke='%23e1eafe' d='M1 1h1'/%3E%3Cpath stroke='%23dae6fe' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23d4e1fc' d='M3 1h1M1 3h1M1 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M6 1h1M1 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M7 1h1M4 2h2'/%3E%3Cpath stroke='%23cad9fd' d='M8 1h1M6 2h1M3 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M9 1h2'/%3E%3Cpath stroke='%23c5d6fc' d='M11 1h1M2 11h4'/%3E%3Cpath stroke='%23c2d3fc' d='M12 1h1m-2 1h1M1 11h1m0 1h2m-2 1h2'/%3E%3Cpath stroke='%23bccefa' d='M13 1h1m-1 1h1m-1 1h1m-1 1h1M3 15h4'/%3E%3Cpath stroke='%23b9c9f3' d='M14 1h1M3 16h4'/%3E%3Cpath stroke='%23d8e3fc' d='M2 2h1'/%3E%3Cpath stroke='%23d1defd' d='M3 2h1'/%3E%3Cpath stroke='%23c9d8fc' d='M7 2h1M4 3h3M4 4h3M3 6h1m1 0h2M1 7h1M1 8h1'/%3E%3Cpath stroke='%23c5d5fc' d='M8 2h1m-8 8h5'/%3E%3Cpath stroke='%23c5d3fc' d='M9 2h2'/%3E%3Cpath stroke='%23bed0fc' d='M12 2h1M8 3h1M8 4h1m-8 8h1m-1 1h1m0 1h1m1 0h3'/%3E%3Cpath stroke='%23cddbfc' d='M3 3h1M3 4h1M1 6h2'/%3E%3Cpath stroke='%23c8d5fb' d='M7 3h1M7 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M9 3h4M9 4h4M8 5h1M7 6h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 3h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23ceddfd' d='M2 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M4 5h4M1 9h3'/%3E%3Cpath stroke='%23bacdfc' d='M9 5h2m1 0h2M1 14h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1M8 6h2m2 0h2m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%234d6185' d='M4 6h1m5 0h1M3 7h3m3 0h3M4 8h3m1 0h3M5 9h5m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1m-1 1h1'/%3E%3Cpath stroke='%23cad8fd' d='M2 7h1M2 8h2'/%3E%3Cpath stroke='%23c1d3fb' d='M6 7h2M7 8h1M4 9h1'/%3E%3Cpath stroke='%23b6cefb' d='M8 7h1m2 1h1m-2 1h3m-2 1h2'/%3E%3Cpath stroke='%23b6cdfb' d='M13 9h1m-6 6h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 9h1'/%3E%3Cpath stroke='%23b4c8f6' d='M0 10h1'/%3E%3Cpath stroke='%23bdd3fb' d='M9 10h2m-4 4h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 10h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 10h1'/%3E%3Cpath stroke='%23b1c7f6' d='M0 11h1'/%3E%3Cpath stroke='%23c3d5fd' d='M6 11h1'/%3E%3Cpath stroke='%23bad4fc' d='M8 11h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M9 11h4m-2 3h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 11h1m-3 4h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 11h1m-7 5h3'/%3E%3Cpath stroke='%23adc3f6' d='M0 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c2d5fc' d='M4 12h4m-4 1h4'/%3E%3Cpath stroke='%23b7d3fc' d='M9 12h2m-2 1h2m-3 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 12h1m-1 1h1'/%3E%3Cpath stroke='%23afcdfb' d='M12 12h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afcbfa' d='M13 12h1m-1 1h1'/%3E%3Cpath stroke='%23b2c8f4' d='M14 12h1m-1 1h1m-4 3h1'/%3E%3Cpath stroke='%23c1d2fb' d='M3 14h1'/%3E%3Cpath stroke='%23b6d1fb' d='M9 14h2'/%3E%3Cpath stroke='%23adc9f9' d='M13 14h1m-2 1h1'/%3E%3Cpath stroke='%23b1c6f3' d='M14 14h1m-3 2h1'/%3E%3Cpath stroke='%23abc1f4' d='M0 15h1'/%3E%3Cpath stroke='%23b7cbf9' d='M1 15h1'/%3E%3Cpath stroke='%23b9cefb' d='M2 15h1'/%3E%3Cpath stroke='%23b9cffb' d='M7 15h1'/%3E%3Cpath stroke='%23b2cdfb' d='M9 15h2'/%3E%3Cpath stroke='%23aec8f7' d='M13 15h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 15h1m-2 1h1'/%3E%3Cpath stroke='%23dbe3f8' d='M0 16h1'/%3E%3Cpath stroke='%23b7c6f1' d='M1 16h1'/%3E%3Cpath stroke='%23b8c9f2' d='M2 16h1m4 0h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 16h1'/%3E%3C/svg%3E");
background-size: 15px;
font-size: 11px;
border: none;
background-color: #fff;
box-sizing: border-box;
height: 21px;
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
position: relative;
padding: 5px 32px 32px 5px;
background-position: top 50% right 2px;
background-repeat: no-repeat;
border-radius: 0;
border: 1px solid black;
}
body {
font-variant: oldstyle-nums;
font-family: sans-serif;
background-color: #fafafa;
text-shadow: 0 0.05em 0.1em rgba(0,0,0,0.2);
scroll-behavior: smooth;
text-wrap: balance;
text-rendering: optimizeLegibility;
-webkit-font-smoothing: antialiased;
-moz-osx-font-smoothing: grayscale;
font-feature-settings: "ss02", "liga", "onum";
}
.marked_text {
background-color: yellow;
}
.time_picker_container {
font-variant: small-caps;
width: 100%;
}
.time_picker_container > input {
width: 50px;
}
#loader {
display: grid;
justify-content: center;
align-items: center;
height: 100%;
}
.no_linebreak {
line-break: auto;
}
.dark_code_bg {
background-color: #363636;
color: white;
}
.code_bg {
background-color: #C0C0C0;
}
#commands {
line-break: anywhere;
}
.color_red {
color: red;
}
.color_orange {
color: orange;
}
table > tbody > tr:nth-child(odd) {
background-color: #fafafa;
}
table > tbody > tr:nth-child(even) {
background-color: #ddd;
}
table {
border-collapse: collapse;
margin: 0 0;
min-width: 200px;
}
th {
background-color: #4eae46;
color: #ffffff;
text-align: left;
border: 0px;
}
.error_element {
background-color: #e57373;
border-radius: 10px;
padding: 4px;
display: none;
}
button {
background-color: #4eae46;
border: 1px solid #2A8387;
border-radius: 4px;
box-shadow: rgba(0, 0, 0, 0.12) 0 1px 1px;
cursor: pointer;
display: block;
line-height: 100%;
outline: 0;
padding: 11px 15px 12px;
text-align: center;
transition: box-shadow .05s ease-in-out, opacity .05s ease-in-out;
user-select: none;
-webkit-user-select: none;
touch-action: manipulation;
font-family: sans-serif;
}
button:hover {
box-shadow: rgba(255, 255, 255, 0.3) 0 0 2px inset, rgba(0, 0, 0, 0.4) 0 1px 2px;
text-decoration: none;
transition-duration: .15s, .15s;
}
button:active {
box-shadow: rgba(0, 0, 0, 0.15) 0 2px 4px inset, rgba(0, 0, 0, 0.4) 0 1px 1px;
}
button:disabled {
cursor: not-allowed;
opacity: .6;
}
button:disabled:active {
pointer-events: none;
}
button:disabled:hover {
box-shadow: none;
}
.half_width_td {
vertical-align: baseline;
width: 50%;
}
#scads_bar {
width: 100%;
margin: 0;
padding: 0;
user-select: none;
user-drag: none;
-webkit-user-drag: none;
user-select: none;
-moz-user-select: none;
-webkit-user-select: none;
-ms-user-select: none;
display: -webkit-box;
}
.tab {
display: inline-block;
padding: 0px;
margin: 0px;
font-size: 16px;
font-weight: bold;
text-align: center;
border-radius: 25px;
text-decoration: none !important;
transition: background-color 0.3s, color 0.3s;
color: unset !important;
}
.tooltipster-base {
border: 1px solid black;
position: absolute;
border-radius: 8px;
padding: 2px;
color: white;
background-color: #61686f;
width: 70%;
min-width: 200px;
pointer-events: none;
}
td {
padding-top: 3px;
padding-bottom: 3px;
}
.left_side {
text-align: right;
}
.right_side {
text-align: left;
}
.spinner {
border: 8px solid rgba(0, 0, 0, 0.1);
border-left: 8px solid #3498db;
border-radius: 50%;
width: 50px;
height: 50px;
animation: spin 1s linear infinite;
}
@keyframes spin {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
#spinner-overlay {
-webkit-text-stroke: 1px black;
white !important;
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
display: flex;
justify-content: center;
align-items: center;
z-index: 9999;
}
#spinner-container {
text-align: center;
color: #fff;
display: contents;
}
#spinner-text {
font-size: 3vw;
margin-left: 10px;
}
a, a:visited, a:active, a:hover, a:link {
color: #007bff;
text-decoration: none;
}
.copy-container {
display: inline-block;
position: relative;
cursor: pointer;
margin-left: 10px;
color: blue;
}
.copy-container:hover {
text-decoration: underline;
}
.clipboard-icon {
position: absolute;
top: 5px;
right: 5px;
font-size: 1.5em;
}
#main_tab {
overflow: scroll;
width: max-content;
}
.ui-tabs .ui-tabs-nav li {
user-select: none;
}
.stacktrace_table {
background-color: black !important;
color: white !important;
}
#breadcrumb {
user-select: none;
}
#statusBar {
user-select: none;
}
.error_line {
background-color: red !important;
color: white !important;
}
.header_table {
border: 0px !important;
padding: 0px !important;
width: revert !important;
min-width: revert !important;
}
.img_auto_width {
max-width: revert !important;
}
#main_dir_or_plot_view {
display: inline-grid;
}
#refresh_button {
width: 300px;
}
._share_link {
color: black !important;
}
#footer_element {
height: 30px;
background-color: #f8f9fa;
padding: 0px;
text-align: center;
border-top: 1px solid #dee2e6;
width: 100%;
box-sizing: border-box;
position: fixed;
bottom: 0;
z-index: 2;
margin-left: -9px;
z-index: 99;
}
.switch {
position: relative;
display: inline-block;
width: 50px;
height: 26px;
}
.switch input {
opacity: 0;
width: 0;
height: 0;
}
.slider {
position: absolute;
cursor: pointer;
top: 0;
left: 0;
right: 0;
bottom: 0;
background-color: #ccc;
transition: .4s;
border-radius: 26px;
}
.slider:before {
position: absolute;
content: "";
height: 20px;
width: 20px;
left: 3px;
bottom: 3px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #444;
}
input:checked + .slider:before {
transform: translateX(24px);
}
.mode-text {
position: absolute;
top: 5px;
left: 65px;
font-size: 14px;
color: black;
transition: .4s;
width: 65px;
display: block;
font-size: 0.7rem;
text-align: center;
}
input:checked + .slider .mode-text {
content: "Dark Mode";
color: white;
}
#mainContent {
height: fit-content;
min-height: 100%;
}
li {
text-align: left;
}
#share_path {
margin-bottom: 20px;
margin-top: 20px;
}
#sortForm {
margin-bottom: 20px;
}
.share_folder_buttons {
margin-top: 10px;
margin-bottom: 10px;
}
.nav_tab_button {
margin: 10px;
}
.header_table {
margin: 10px;
}
.no_border {
border: unset !important;
}
.gui_table {
padding: 5px !important;
}
.gui_parameter_row {
}
.gui_parameter_row_cell {
border: unset !important;
}
.gui_param_table {
width: 95%;
margin: unset !important;
}
table td, table tr,
.parameterRow table {
padding: 2px !important;
}
.parameterRow table {
margin: 0px;
border: unset;
}
.parameterRow > td {
border: 0px !important;
}
.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
border: 0px !important;
}
.green_text {
color: green;
}
.remove_parameter {
white-space: pre;
}
select {
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
background-color: #fff;
color: #222;
padding: 5px 30px 5px 5px;
border: 1px solid #555;
border-radius: 5px;
cursor: pointer;
outline: none;
transition: all 0.3s ease;
background:
url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
no-repeat right 10px center,
linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
background-size: 12px, auto;
}
select:hover {
border-color: #888;
}
select:focus {
border-color: #4caf50;
box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
}
select::-ms-expand {
display: none;
}
input, textarea {
border-radius: 5px;
border: solid 1px;
}
#search {
width: 200px;
max-width: 70%;
background-image: url(images/search.svg);
background-repeat: no-repeat;
background-size: auto 40px;
height: 40px;
line-height: 40px;
padding-left: 40px;
box-sizing: border-box;
}
input[type="checkbox"] {
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
width: 25px;
height: 25px;
border: 2px solid #3498db;
border-radius: 5px;
background-color: #fff;
position: relative;
cursor: pointer;
transition: all 0.3s ease;
width: 25px !important;
}
input[type="checkbox"]:checked {
background-color: #3498db;
border-color: #2980b9;
}
input[type="checkbox"]:checked::before {
content: '✔';
position: absolute;
left: 4px;
top: 2px;
color: #fff;
}
input[type="checkbox"]:hover {
border-color: #2980b9;
background-color: #3caffc;
}
.toc {
margin-bottom: 20px;
}
.toc li {
margin-bottom: 5px;
}
.toc a {
text-decoration: none;
color: #007bff;
}
.toc a:hover {
text-decoration: underline;
}
.table-container {
width: 100%;
overflow-x: auto;
}
.section-header {
background-color: #1d6f9a !important;
color: white;
}
.warning {
color: red;
}
.li_list a {
text-decoration: none;
}
.gridjs-td {
white-space: nowrap;
}
th, td {
border: 1px solid gray !important;
}
.no_border {
border: 0px !important;
}
.no_break {
}
img {
user-select: none;
pointer-events: none;
}
#config_table, #hidden_config_table {
user-select: none;
}
.copy_clipboard_button {
margin-bottom: 10px;
}
.badge_table {
background-color: unset !important;
}
.make_markable {
user-select: text;
}
.header-container {
display: flex;
flex-wrap: wrap;
align-items: center;
justify-content: space-between;
gap: 1rem;
padding: 10px;
background: var(--header-bg, #fff);
border-bottom: 1px solid #ccc;
}
.header-logo-group {
display: flex;
gap: 1rem;
align-items: center;
flex: 1 1 auto;
min-width: 200px;
}
.logo-img {
max-height: 45px;
height: auto;
width: auto;
object-fit: contain;
pointer-events: unset;
}
.header-badges {
flex-direction: column;
gap: 5px;
align-items: flex-start;
flex: 0 1 auto;
margin-top: auto;
margin-bottom: auto;
}
.badge-img {
height: auto;
max-width: 130px;
margin-top: 3px;
}
.header-tabs {
margin-top: 10px;
display: flex;
flex-wrap: wrap;
gap: 10px;
flex: 2 1 100%;
justify-content: center;
}
.nav-tab {
display: inline-block;
text-decoration: none;
padding: 8px 16px;
border-radius: 20px;
background: linear-gradient(to right, #4a90e2, #357ABD);
color: white;
font-weight: bold;
white-space: nowrap;
transition: background 0.2s ease-in-out, transform 0.2s;
box-shadow: 0 2px 4px rgba(0,0,0,0.2);
}
.nav-tab:hover {
background: linear-gradient(to right, #5aa0f2, #4a90e2);
transform: translateY(-2px);
}
.current-tag {
padding-left: 10px;
font-size: 0.9rem;
color: #666;
}
.header-theme-toggle {
flex: 1 1 auto;
align-items: center;
margin-top: 20px;
min-width: 120px;
}
.switch {
position: relative;
display: inline-block;
width: 60px;
height: 30px;
}
.switch input {
display: none;
}
.slider {
position: absolute;
top: 0; left: 0; right: 0; bottom: 0;
background-color: #ccc;
border-radius: 34px;
cursor: pointer;
}
.slider::before {
content: "";
position: absolute;
height: 24px;
width: 24px;
left: 3px;
bottom: 3px;
background-color: white;
transition: .4s;
border-radius: 50%;
}
input:checked + .slider {
background-color: #2196F3;
}
input:checked + .slider::before {
transform: translateX(30px);
}
@media (max-width: 768px) {
.header-logo-group,
.header-badges,
.header-theme-toggle {
justify-content: center;
flex: 1 1 100%;
text-align: center;
width: inherit;
}
.logo-img {
max-height: 50px;
pointer-events: unset;
}
.badge-img {
max-width: 100px;
}
.hide_on_mobile {
display: none;
}
.nav-tab {
font-size: 0.9rem;
padding: 6px 12px;
}
.header_button {
white-space: pre;
font-size: 2em;
}
}
.header_button {
white-space: pre;
margin-top: 20px;
margin: 5px;
}
.line_break_anywhere {
line-break: anywhere;
}
.responsive-container {
display: flex;
flex-wrap: wrap;
justify-content: space-between;
gap: 20px;
}
.responsive-container .half {
flex: 1 1 48%;
box-sizing: border-box;
min-width: 500px;
}
.config-section table {
width: 100%;
border-collapse: collapse;
}
@media (max-width: 768px) {
.responsive-container .half {
flex: 1 1 100%;
}
}
@keyframes spin {
0% {
transform: rotate(0deg);
}
100% {
transform: rotate(360deg);
}
}
.rotate {
animation: spin 2s linear infinite;
display: inline-block;
}
input::placeholder {
font-family: sans-serif;
}
.gridjs-th-content {
overflow: visible !important;
}
.error_text {
color: red;
}
h1, h2, h3, h4, h5, h6 {
margin-top: 1em;
font-weight: bold;
color: #333;
border-left: 5px solid #ccc;
padding-left: 0.5em;
}
.no_cursive {
font-style: normal;
}
.caveat {
background-color: #fff8b3;
border: 1px solid #f2d600;
padding: 1em 1em 1em 70px;
position: relative;
font-family: sans-serif;
color: #665500;
margin: 1em 0;
border-radius: 4px;
}
.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
margin-top: 0;
margin-bottom: 0.5em;
font-weight: bold;
}
.caveat::before {
content: "⚠️";
font-size: 50px;
line-height: 1;
position: absolute;
left: 10px;
top: 50%;
transform: translateY(-50%);
pointer-events: none;
user-select: none;
}
.caveat.warning::before { content: "⚠️"; }
.caveat.stop::before { content: "🛑"; }
.caveat.exclamation::before { content: "❗"; }
.caveat.alarm::before { content: "🚨"; }
.caveat.tip::before { content: "💡"; }
.tutorial_icon {
display: inline-block;
font-size: 1.3em;
line-height: 1;
vertical-align: middle;
transform: translateY(-10%);
padding: 0.2em 0;
}
.highlight {
background-color: yellow;
font-weight: bold;
}
#searchResults li {
opacity: 0;
transform: translateY(8px);
animation: fadeInUp 0.3s ease-out forwards;
animation-delay: 0.05s;
list-style: none;
margin-bottom: 5px;
}
@keyframes fadeInUp {
to {
opacity: 1;
transform: translateY(0);
}
}
.search_headline {
font-weight: bold;
margin-top: 1em;
margin-bottom: 0.3em;
color: #444;
}
.search_share_path {
color: black;
display: block ruby;
margin-top: 20px;
}
@media print {
#scads_bar {
display: none !important;
}
}
/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
body{
color: #222
}
.surface{
background: #ece9d8
}
u{
text-decoration: none;
border-bottom: .5px solid #222
}
a{
color: #00f
}
a: focus{
outline: 1px dotted #00f
}
code,code *{
font-family: monospace
}
pre{
display: block;
padding: 12px 8px;
background-color: #000;
color: silver;
font-size: 1rem;
margin: 0;
overflow: scroll;
}
summary: focus{
outline: 1px dotted #000
}
: :-webkit-scrollbar{
width: 16px
}
: :-webkit-scrollbar: horizontal{
height: 17px
}
: :-webkit-scrollbar-track{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb{
background-color: #dfdfdf;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}
: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
display: block
}
: :-webkit-scrollbar-button: vertical: start{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: end{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: horizontal: start{
width: 16px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: horizontal: end{
width: 16px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
}
button{
border: none;
background: #ece9d8;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
border-radius: 0;
min-width: 75px;
min-height: 23px;
padding: 0 12px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
}
button.focused,button: focus{
outline: 1px dotted #000;
outline-offset: -4px
}
label{
display: inline-flex;
align-items: center
}
textarea{
padding: 3px 4px;
border: none;
background-color: #fff;
box-sizing: border-box;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
border-radius: 0
}
textarea: focus{
outline: none
}
select: focus option{
color: #000;
background-color: #fff
}
.vertical-bar{
width: 4px;
height: 20px;
background: silver;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}
&: disabled,&: disabled+label{
color: grey;
text-shadow: 1px 1px 0 #fff
}
input[type=radio]+label{
line-height: 13px;
position: relative;
margin-left: 19px
}
input[type=radio]+label: before{
content: "";
position: absolute;
top: 0;
left: -19px;
display: inline-block;
width: 13px;
height: 13px;
margin-right: 6px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
}
input[type=radio]: active+label: before{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}
input[type=radio]: checked+label: after{
content: "";
display: block;
width: 5px;
height: 5px;
top: 5px;
left: -14px;
position: absolute;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=radio][disabled]+label: before{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
}
input[type=email],input[type=password]{
padding: 3px 4px;
border: 1px solid #7f9db9;
background-color: #fff;
box-sizing: border-box;
-webkit-appearance: none;
-moz-appearance: none;
appearance: none;
border-radius: 0;
height: 21px;
line-height: 2
}
input[type=email]: focus,input[type=password]: focus{
outline: none
}
input[type=range]{
-webkit-appearance: none;
width: 100%;
background: transparent
}
input[type=range]: focus{
outline: none
}
input[type=range]: :-webkit-slider-thumb{
-webkit-appearance: none;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range]: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range]: :-webkit-slider-runnable-track{
background: #000;
border-right: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}
input[type=range]: :-moz-range-track{
background: #000;
border-right: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}
.is-vertical{
display: inline-block;
width: 4px;
height: 150px;
transform: translateY(50%)
}
.is-vertical>input[type=range]{
width: 150px;
height: 4px;
margin: 0 16px 0 10px;
transform-origin: left;
transform: rotate(270deg) translateX(calc(-50% + 8px))
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid grey;
border-bottom: 1px solid grey;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}
.is-vertical>input[type=range]: :-webkit-slider-thumb{
transform: translateY(-8px) scaleX(-1)
}
.is-vertical>input[type=range]: :-moz-range-thumb{
transform: translateY(2px) scaleX(-1)
}
.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
transform: translateY(-10px) scaleX(-1)
}
.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
transform: translateY(0) scaleX(-1)
}
.window{
font-size: 11px;
box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
background: #ece9d8;
padding: 3px
}
.window fieldset{
margin-bottom: 9px
}
.title-bar{
background: #000;
padding: 3px 2px 3px 3px;
display: flex;
justify-content: space-between;
align-items: center
}
.title-bar-text{
font-weight: 700;
color: #fff;
letter-spacing: 0;
margin-right: 24px
}
.title-bar-controls button{
padding: 0;
display: block;
min-width: 16px;
min-height: 14px
}
.title-bar-controls button: focus{
outline: none
}
.window-body{
margin: 8px
}
.window-body pre{
margin: -8px
}
.status-bar{
margin: 0 1px;
display: flex;
gap: 1px
}
.status-bar-field{
box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
flex-grow: 1;
padding: 2px 3px;
margin: 0
}
ul.tree-view{
display: block;
background: #fff;
padding: 6px;
margin: 0
}
ul.tree-view li{
list-style-type: none;
margin-top: 3px
}
ul.tree-view a{
text-decoration: none;
color: #000
}
ul.tree-view a: focus{
background-color: #2267cb;
color: #fff
}
ul.tree-view ul{
margin-top: 3px;
margin-left: 16px;
padding-left: 16px;
border-left: 1px dotted grey
}
ul.tree-view ul>li{
position: relative
}
ul.tree-view ul>li: before{
content: "";
display: block;
position: absolute;
left: -16px;
top: 6px;
width: 12px;
border-bottom: 1px dotted grey
}
ul.tree-view ul>li: last-child: after{
content: "";
display: block;
position: absolute;
left: -20px;
top: 7px;
bottom: 0;
width: 8px;
background: #fff
}
ul.tree-view ul details>summary: before{
margin-left: -22px;
position: relative;
z-index: 1
}
ul.tree-view details{
margin-top: 0
}
ul.tree-view details>summary: before{
text-align: center;
display: block;
float: left;
content: "+";
border: 1px solid grey;
width: 8px;
height: 9px;
line-height: 9px;
margin-right: 5px;
padding-left: 1px;
background-color: #fff
}
ul.tree-view details[open] summary{
margin-bottom: 0
}
ul.tree-view details[open]>summary: before{
content: "-"
}
fieldset{
border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
padding: 10px;
padding-block-start: 8px;
margin: 0
}
legend{
background: #ece9d8
}
menu[role=tablist]{
position: relative;
margin: 0 0 -2px;
text-indent: 0;
list-style-type: none;
display: flex;
padding-left: 3px
}
menu[role=tablist] button{
z-index: 1;
display: block;
color: #222;
text-decoration: none;
min-width: unset
}
menu[role=tablist] button[aria-selected=true]{
padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
}
menu[role=tablist] button: focus{
outline: 1px dotted #222;outline-offset: -4px
}
menu[role=tablist].justified button{
flex-grow: 1;text-align: center
}
[role=tabpanel]{
padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
}
: :-webkit-scrollbar{
width: 17px
}
: :-webkit-scrollbar-corner{
background: #dfdfdf
}
: :-webkit-scrollbar-track: vertical{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-track: horizontal{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb{
background-position: 50%;
background-repeat: no-repeat;
background-color: #c8d6fb;
background-size: 7px;
border: 1px solid #fff;
border-radius: 2px;
box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
}
: :-webkit-scrollbar-thumb: vertical{
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-thumb: horizontal{
background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: start{
height: 17px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 7h1'/%3E%3Cpath stroke='%23c5d5fc' d='M9 3h1M3 9h1m3 0h1'/%3E%3Cpath stroke='%23c5d3fc' d='M10 3h1'/%3E%3Cpath stroke='%23bed0fc' d='M12 3h1M9 4h1m-7 7h1m0 1h1'/%3E%3Cpath stroke='%23bccdfa' d='M13 3h1'/%3E%3Cpath stroke='%23baccf4' d='M14 3h1'/%3E%3Cpath stroke='%23bdcbda' d='M16 3h1'/%3E%3Cpath stroke='%23c4d4f7' d='M2 4h1'/%3E%3Cpath stroke='%23cddbfc' d='M5 4h1M3 6h1'/%3E%3Cpath stroke='%23c8d5fb' d='M8 4h1'/%3E%3Cpath stroke='%23bbcefd' d='M10 4h3M9 5h1'/%3E%3Cpath stroke='%23bcccf3' d='M14 4h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c2d5' d='M16 4h1'/%3E%3Cpath stroke='%23bed0f8' d='M2 5h1'/%3E%3Cpath stroke='%23ceddfd' d='M4 5h1'/%3E%3Cpath stroke='%23c8d6fb' d='M6 5h2M3 8h2'/%3E%3Cpath stroke='%234d6185' d='M8 5h1M7 6h3M6 7h5M5 8h3m1 0h3M4 9h3m3 0h3m-8 1h1m5 0h1'/%3E%3Cpath stroke='%23bacdfc' d='M10 5h1m1 0h2M3 12h1'/%3E%3Cpath stroke='%23b9cdfb' d='M11 5h1m-2 1h1m1 0h2m-1 1h1'/%3E%3Cpath stroke='%23a8bbd4' d='M16 5h1'/%3E%3Cpath stroke='%23cddafc' d='M4 6h1'/%3E%3Cpath stroke='%23b7cdfc' d='M11 6h1m0 1h1'/%3E%3Cpath stroke='%23a4b8d3' d='M16 6h1'/%3E%3Cpath stroke='%23cad8fd' d='M4 7h2'/%3E%3Cpath stroke='%23b6cefb' d='M11 7h1m0 1h1'/%3E%3Cpath stroke='%23bacbf4' d='M14 7h1'/%3E%3Cpath stroke='%23a0b5d3' d='M16 7h1m-1 1h1m-1 5h1'/%3E%3Cpath stroke='%23c1d3fb' d='M8 8h1'/%3E%3Cpath stroke='%23b6cdfb' d='M13 8h1m-5 5h1'/%3E%3Cpath stroke='%23b9cbf3' d='M14 8h1'/%3E%3Cpath stroke='%23b4c8f6' d='M2 9h1'/%3E%3Cpath stroke='%23c2d5fc' d='M8 9h1m-1 1h1m-3 1h2'/%3E%3Cpath stroke='%23bdd3fb' d='M9 9h1m-2 3h1'/%3E%3Cpath stroke='%23b5cdfa' d='M13 9h1'/%3E%3Cpath stroke='%23b5c9f3' d='M14 9h1'/%3E%3Cpath stroke='%239fb5d2' d='M16 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b1c7f6' d='M2 10h1'/%3E%3Cpath stroke='%23c3d5fd' d='M7 10h1'/%3E%3Cpath stroke='%23bad4fc' d='M9 10h1m-1 1h1'/%3E%3Cpath stroke='%23b2cffb' d='M10 10h1m1 0h1m-2 2h1'/%3E%3Cpath stroke='%23b1cbfa' d='M13 10h1'/%3E%3Cpath stroke='%23b3c8f5' d='M14 10h1m-6 4h2'/%3E%3Cpath stroke='%23adc3f6' d='M2 11h1'/%3E%3Cpath stroke='%23c3d3fd' d='M5 11h1'/%3E%3Cpath stroke='%23c1d5fb' d='M8 11h1'/%3E%3Cpath stroke='%23b7d3fc' d='M10 11h1m-2 1h1'/%3E%3Cpath stroke='%23b3d1fc' d='M11 11h1'/%3E%3Cpath stroke='%23afcefb' d='M12 11h1'/%3E%3Cpath stroke='%23aecafa' d='M13 11h1'/%3E%3Cpath stroke='%23b1c8f3' d='M14 11h1'/%3E%3Cpath stroke='%23acc2f5' d='M2 12h1'/%3E%3Cpath stroke='%23c1d2fb' d='M5 12h1'/%3E%3Cpath stroke='%23bed1fc' d='M6 12h2'/%3E%3Cpath stroke='%23b6d1fb' d='M10 12h1'/%3E%3Cpath stroke='%23afccfb' d='M12 12h1'/%3E%3Cpath stroke='%23adc9f9' d='M13 12h1m-2 1h1'/%3E%3Cpath stroke='%23b1c5f3' d='M14 12h1'/%3E%3Cpath stroke='%23aac0f3' d='M2 13h1'/%3E%3Cpath stroke='%23b7cbf9' d='M3 13h1'/%3E%3Cpath stroke='%23b9cefb' d='M4 13h1'/%3E%3Cpath stroke='%23bbcef9' d='M7 13h1'/%3E%3Cpath stroke='%23b9cffb' d='M8 13h1'/%3E%3Cpath stroke='%23b2cdfb' d='M10 13h1'/%3E%3Cpath stroke='%23b0cbf9' d='M11 13h1'/%3E%3Cpath stroke='%23aec8f7' d='M13 13h1'/%3E%3Cpath stroke='%23b0c5f2' d='M14 13h1'/%3E%3Cpath stroke='%23dbe3f8' d='M2 14h1'/%3E%3Cpath stroke='%23b7c6f1' d='M3 14h1'/%3E%3Cpath stroke='%23b8c9f2' d='M4 14h1m3 0h1'/%3E%3Cpath stroke='%23b2c8f4' d='M11 14h1'/%3E%3Cpath stroke='%23b1c6f3' d='M12 14h1'/%3E%3Cpath stroke='%23b0c4f2' d='M13 14h1'/%3E%3Cpath stroke='%23d9e3f6' d='M14 14h1'/%3E%3Cpath stroke='%23aec0d6' d='M16 14h1'/%3E%3Cpath stroke='%23c3d4e7' d='M1 15h1'/%3E%3Cpath stroke='%23aec4e5' d='M15 15h1'/%3E%3Cpath stroke='%23edf1f3' d='M1 16h1'/%3E%3Cpath stroke='%23aac0e1' d='M2 16h1'/%3E%3Cpath stroke='%2394b1d9' d='M3 16h1'/%3E%3Cpath stroke='%2388a7d8' d='M4 16h1'/%3E%3Cpath stroke='%2383a4d3' d='M5 16h1'/%3E%3Cpath stroke='%237da0d4' d='M6 16h1m3 0h3'/%3E%3Cpath stroke='%237e9fd2' d='M7 16h1'/%3E%3Cpath stroke='%237c9fd3' d='M8 16h2'/%3E%3Cpath stroke='%2382a4d6' d='M13 16h1'/%3E%3Cpath stroke='%2394b0dd' d='M14 16h1'/%3E%3Cpath stroke='%23ecf2f7' d='M15 16h1'/%3E%3C/svg%3E")
}
: :-webkit-scrollbar-button: vertical: end{
height: 17px;
background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h3'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M6 6h2M3 7h1'/%3E%3Cpath 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}
.window{
box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
border-top-left-radius: 8px;
border-top-right-radius: 8px;
padding: 0 0 3px;
-webkit-font-smoothing: antialiased
}
.title-bar{
background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
padding: 3px 5px 3px 3px;
border-top: 1px solid #0831d9;
border-left: 1px solid #0831d9;
border-right: 1px solid #001ea0;
border-top-left-radius: 8px;
border-top-right-radius: 7px;
font-size: 13px;
text-shadow: 1px 1px #0f1089;
height: 21px
}
.title-bar-text{
padding-left: 3px
}
.title-bar-controls{
display: flex
}
.title-bar-controls button{
min-width: 21px;
min-height: 21px;
margin-left: 2px;
background-repeat: no-repeat;
background-position: 50%;
box-shadow: none;
background-color: #0050ee;
transition: background .1s;
border: none
}
.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
box-shadow: none!important
}
.title-bar-controls button[aria-label=Minimize]{
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}
.title-bar-controls button[aria-label=Maximize]: not(: disabled): active{
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}
.title-bar-controls button[aria-label=Restore]{
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}
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}
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stroke='%23b5381a' d='M9 4h1M4 9h1'/%3E%3Cpath stroke='%23b8391a' d='M10 4h1m-7 6h1'/%3E%3Cpath stroke='%23ba3a1b' d='M11 4h1m-8 7h2'/%3E%3Cpath stroke='%23bc3b1c' d='M12 4h1m-9 8h1'/%3E%3Cpath stroke='%23bd3c1c' d='M13 4h1m-1 1h1m-2 1h1m-7 6h1m-3 1h2'/%3E%3Cpath stroke='%23be3d1c' d='M14 4h3m-1 1h1m-1 1h1M4 14h1m-1 1h1m-1 1h2'/%3E%3Cpath stroke='%23bf3d1c' d='M17 4h3m-3 1h3m-2 1h2m-1 1h1M4 17h2m-2 1h4m-4 1h4'/%3E%3Cpath stroke='%235b1d0d' d='M1 5h1'/%3E%3Cpath stroke='%239c3016' d='M3 5h1'/%3E%3Cpath stroke='%23a43217' d='M4 5h1'/%3E%3Cpath stroke='%23b8553e' d='M5 5h1'/%3E%3Cpath stroke='%23d59485' d='M6 5h1M5 6h1'/%3E%3Cpath stroke='%23b33619' d='M7 5h1'/%3E%3Cpath stroke='%23b53719' d='M8 5h1'/%3E%3Cpath stroke='%23b8381a' d='M9 5h1M6 8h1'/%3E%3Cpath stroke='%23b9391b' d='M10 5h1'/%3E%3Cpath stroke='%23ba391b' d='M11 5h1M6 9h1m-2 1h1'/%3E%3Cpath stroke='%23bc3b1b' d='M12 5h1m-2 1h1m-6 5h1m-2 1h1'/%3E%3Cpath stroke='%23dc9887' d='M14 5h1'/%3E%3Cpath stroke='%23c85d42' d='M15 5h1M5 15h1'/%3E%3Cpath stroke='%23611f0e' d='M1 6h1'/%3E%3Cpath stroke='%23a23217' d='M3 6h1'/%3E%3Cpath stroke='%23d79585' d='M6 6h1'/%3E%3Cpath stroke='%23d89585' d='M7 6h1'/%3E%3Cpath stroke='%23b8371a' d='M8 6h1'/%3E%3Cpath stroke='%23ba391a' d='M9 6h1'/%3E%3Cpath stroke='%23bb3a1b' d='M10 6h1m-5 4h1'/%3E%3Cpath stroke='%23dd9887' d='M13 6h3m-4 1h1m-2 1h1M9 9h1m-2 2h1m-2 1h1m-2 1h1m-2 1h2'/%3E%3Cpath stroke='%23c03e1d' d='M17 6h1m-2 1h3m0 1h1m-1 1h1M7 16h1m-2 1h2m0 1h1'/%3E%3Cpath stroke='%2365200e' d='M1 7h1'/%3E%3Cpath stroke='%23902d15' d='M2 7h1'/%3E%3Cpath stroke='%23a73418' d='M3 7h1'/%3E%3Cpath stroke='%23af3518' d='M4 7h1'/%3E%3Cpath stroke='%23b43619' d='M5 7h1'/%3E%3Cpath stroke='%23d99585' d='M6 7h1'/%3E%3Cpath stroke='%23da9686' d='M7 7h1'/%3E%3Cpath stroke='%23db9686' d='M8 7h1M7 8h1'/%3E%3Cpath stroke='%23bc3a1b' d='M9 7h1M7 9h1'/%3E%3Cpath stroke='%23bd3b1b' d='M10 7h1m-4 3h1'/%3E%3Cpath stroke='%23be3c1c' d='M11 7h1m-2 1h1m-3 2h1m-2 1h1'/%3E%3Cpath stroke='%23de9987' d='M13 7h2m-3 1h2m-4 1h2m-3 1h1m-2 2h1m-2 2h1'/%3E%3Cpath stroke='%23c03f1d' d='M15 7h1m-9 8h1'/%3E%3Cpath stroke='%236a220f' d='M1 8h1'/%3E%3Cpath stroke='%23952f15' d='M2 8h1'/%3E%3Cpath stroke='%23ac3518' d='M3 8h1'/%3E%3Cpath stroke='%23b63719' d='M5 8h1'/%3E%3Cpath stroke='%23dc9786' d='M8 8h2M8 9h1'/%3E%3Cpath stroke='%23c2401d' d='M14 8h1m2 0h1m1 3h1M8 14h1m-1 2h1m-1 1h1m0 1h1m1 1h1'/%3E%3Cpath stroke='%23c2401e' d='M15 8h2m1 1h1M8 15h1'/%3E%3Cpath stroke='%23c13f1d' d='M18 8h1m0 2h1M9 19h2'/%3E%3Cpath stroke='%23702410' d='M1 9h1'/%3E%3Cpath stroke='%239b3016' d='M2 9h1'/%3E%3Cpath stroke='%23b03619' d='M3 9h1'/%3E%3Cpath stroke='%23b9381a' d='M5 9h1'/%3E%3Cpath stroke='%23df9a88' d='M12 9h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23c4421e' d='M13 9h1m2 0h2m0 1h1M9 13h1m9 1h1m-1 1h1M9 16h1m9 0h1M9 17h1m0 1h1m3 1h3'/%3E%3Cpath stroke='%23c5431e' d='M14 9h1'/%3E%3Cpath stroke='%23c5431f' d='M15 9h1m-4 1h1m5 1h1m-9 1h1m-2 2h1m-1 1h1m0 2h1m0 1h1m6 0h1'/%3E%3Cpath stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
}
.status-bar{
margin: 0 3px;
box-shadow: inset 0 1px 2px grey;
padding: 2px 1px;
gap: 0
}
.status-bar-field{
-webkit-font-smoothing: antialiased;
box-shadow: none;
padding: 1px 2px;
border-right: 1px solid rgba(208,206,191,.75);
border-left: 1px solid hsla(0,0%,100%,.75)
}
.status-bar-field: first-of-type{
border-left: none
}
.status-bar-field: last-of-type{
border-right: none
}
button{
-webkit-font-smoothing: antialiased;
box-sizing: border-box;
border: 1px solid #003c74;
background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
box-shadow: none;
border-radius: 3px
}
button: not(: disabled).active,button: not(: disabled): active{
box-shadow: none;
background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
}
button: not(: disabled): hover{
box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
}
button.focused,button: focus{
box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
}
button: :-moz-focus-inner{
border: 0
}
input,label,option,select,textarea{
-webkit-font-smoothing: antialiased
}
input[type=radio]{
appearance: none;
-webkit-appearance: none;
-moz-appearance: none;
margin: 0;
background: 0;
position: fixed;
opacity: 0;
border: none
}
input[type=radio]+label{
line-height: 16px
}
input[type=radio]+label: before{
background: linear-gradient(135deg,#dcdcd7,#fff);
border-radius: 50%;
border: 1px solid #1d5281
}
input[type=radio]: not([disabled]): not(: active)+label: hover: before{
box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
}
input[type=radio]: active+label: before{
background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
}
input[type=radio]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
}
input[type=radio]: focus+label{
outline: 1px dotted #000
}
input[type=radio][disabled]+label: before{
border: 1px solid #cac8bb;
background: #fff
}
input[type=radio][disabled]: checked+label: after{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
}
input[type=email],input[type=password],textarea: :selection{
background: #2267cb;
color: #fff
}
input[type=range]: :-webkit-slider-thumb{
height: 21px;
width: 11px;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(-8px)
}
input[type=range]: :-moz-range-thumb{
height: 21px;
width: 11px;
border: 0;
border-radius: 0;
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
transform: translateY(2px)
}
input[type=range]: :-webkit-slider-runnable-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range]: :-moz-range-track{
width: 100%;
height: 2px;
box-sizing: border-box;
background: #ecebe4;
border-right: 1px solid #f3f2ea;
border-bottom: 1px solid #f3f2ea;
border-radius: 2px;
box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
}
input[type=range].has-box-indicator: :-webkit-slider-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
}
input[type=range].has-box-indicator: :-moz-range-thumb{
background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
}
.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
.is-vertical>input[type=range]: :-moz-range-track{
border-left: 1px solid #f3f2ea;
border-right: 0;
border-bottom: 1px solid #f3f2ea;
box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
}
fieldset{
box-shadow: none;
background: #fff;
border: 1px solid #d0d0bf;
border-radius: 4px;
padding-top: 10px
}
legend{
background: transparent;
color: #0046d5
}
.field-row{
display: flex;
align-items: center
}
.field-row>*+*{
margin-left: 6px
}
[class^=field-row]+[class^=field-row]{
margin-top: 6px
}
.field-row-stacked{
display: flex;
flex-direction: column
}
.field-row-stacked *+*{
margin-top: 6px
}
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1753247281.593822,
50,
0,
0
],
[
1753247296.7244096,
50,
0,
0
],
[
1753247296.978789,
50,
0,
0
],
[
1753247297.2880907,
50,
0,
0
],
[
1753247297.3868835,
50,
0,
0
],
[
1753247297.419098,
50,
0,
0
],
[
1753247297.5253851,
50,
0,
0
],
[
1753247776.4311693,
50,
0,
0
],
[
1753247812.7575724,
50,
0,
0
],
[
1753247812.9249675,
50,
0,
0
],
[
1753247815.3376403,
50,
0,
0
]
];
var tab_main_worker_cpu_ram_csv_json = [
[
1753189697,
646.7578125,
26.2
],
[
1753189707,
647.015625,
25.1
],
[
1753189712,
647.38671875,
24.4
],
[
1753189712,
647.38671875,
18.5
],
[
1753189713,
647.64453125,
24.3
],
[
1753189713,
647.64453125,
25
],
[
1753189713,
647.64453125,
25.6
],
[
1753191773,
731.7734375,
29.4
],
[
1753191773,
731.7734375,
27.8
],
[
1753191774,
731.7734375,
23.4
],
[
1753191774,
731.7734375,
16
],
[
1753195160,
797.4140625,
16.1
],
[
1753195160,
797.4140625,
18.7
],
[
1753195160,
797.4140625,
14.8
],
[
1753195160,
797.4140625,
15
],
[
1753199334,
828.75,
15.2
],
[
1753199334,
828.75,
14.7
],
[
1753199334,
828.75,
14.9
],
[
1753199334,
828.75,
20
],
[
1753203520,
856.85546875,
14.9
],
[
1753203520,
856.85546875,
17.6
],
[
1753203521,
856.85546875,
14.2
],
[
1753203521,
856.85546875,
21.4
],
[
1753209737,
859.828125,
14.8
],
[
1753209737,
859.828125,
12.7
],
[
1753209737,
859.828125,
14.2
],
[
1753209737,
859.828125,
21.4
],
[
1753215819,
914.84765625,
14.8
],
[
1753215819,
914.84765625,
15.8
],
[
1753215819,
914.84765625,
14.3
],
[
1753215819,
914.84765625,
14.3
],
[
1753222643,
974.59765625,
14.8
],
[
1753222643,
974.59765625,
17.6
],
[
1753222643,
974.59765625,
14.3
],
[
1753230276,
997.90234375,
14.8
],
[
1753230276,
997.90234375,
15.8
],
[
1753230276,
997.90234375,
14.4
],
[
1753238536,
1034.3828125,
14.8
],
[
1753238536,
1034.3828125,
15.8
],
[
1753238536,
1034.3828125,
14.3
],
[
1753238536,
1034.3828125,
20
],
[
1753247812,
1098.640625,
14.8
],
[
1753247812,
1098.640625,
18.8
],
[
1753247812,
1098.640625,
14.3
],
[
1753247815,
1090.8125,
14.4
],
[
1753247815,
1090.8125,
20
]
];
var tab_main_worker_cpu_ram_headers_json = [
"timestamp",
"ram_usage_mb",
"cpu_usage_percent"
];
"use strict";
function add_default_layout_data (layout, no_height = 0) {
layout["width"] = get_graph_width();
if (!no_height) {
layout["height"] = get_graph_height();
}
layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
return layout;
}
function get_marker_size() {
return 12;
}
function get_text_color() {
return theme == "dark" ? "white" : "black";
}
function get_font_size() {
return 14;
}
function get_graph_height() {
return 800;
}
function get_font_data() {
return {
size: get_font_size(),
color: get_text_color()
}
}
function get_axis_title_data(name, axis_type = "") {
if(axis_type) {
return {
text: name,
type: axis_type,
font: get_font_data()
};
}
return {
text: name,
font: get_font_data()
};
}
function get_graph_width() {
var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
return Math.max(800, Math.floor(width * 0.9));
}
function createTable(data, headers, table_name) {
if (!$("#" + table_name).length) {
console.error("#" + table_name + " not found");
return;
}
new gridjs.Grid({
columns: headers,
data: data,
search: true,
sort: true,
ellipsis: false
}).render(document.getElementById(table_name));
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
colorize_table_entries();
add_colorize_to_gridjs_table();
}
function download_as_file(id, filename) {
var text = $("#" + id).text();
var blob = new Blob([text], {
type: "text/plain"
});
var link = document.createElement("a");
link.href = URL.createObjectURL(blob);
link.download = filename;
document.body.appendChild(link);
link.click();
document.body.removeChild(link);
}
function copy_to_clipboard_from_id (id) {
var text = $("#" + id).text();
copy_to_clipboard(text);
}
function copy_to_clipboard(text) {
if (!navigator.clipboard) {
let textarea = document.createElement("textarea");
textarea.value = text;
document.body.appendChild(textarea);
textarea.select();
try {
document.execCommand("copy");
} catch (err) {
console.error("Copy failed:", err);
}
document.body.removeChild(textarea);
return;
}
navigator.clipboard.writeText(text).then(() => {
console.log("Text copied to clipboard");
}).catch(err => {
console.error("Failed to copy text:", err);
});
}
function filterNonEmptyRows(data) {
var new_data = [];
for (var row_idx = 0; row_idx < data.length; row_idx++) {
var line = data[row_idx];
var line_has_empty_data = false;
for (var col_idx = 0; col_idx < line.length; col_idx++) {
var col_header_name = tab_results_headers_json[col_idx];
var single_data_point = line[col_idx];
if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
line_has_empty_data = true;
continue;
}
}
if(!line_has_empty_data) {
new_data.push(line);
}
}
return new_data;
}
function make_text_in_parallel_plot_nicer() {
$(".parcoords g > g > text").each(function() {
if (theme == "dark") {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "white")
.css("stroke", "black")
.css("stroke-width", "2px")
.css("paint-order", "stroke fill");
} else {
$(this)
.css("text-shadow", "unset")
.css("font-size", "0.9em")
.css("fill", "black")
.css("stroke", "unset")
.css("stroke-width", "unset")
.css("paint-order", "stroke fill");
}
});
}
function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = [], reload = false) {
try {
if ($("#parallel-plot").data("loaded") === "true" && !reload) {
return;
}
// Filter rows ohne leere Werte (wie in deinem Originalcode)
dataArray = filterNonEmptyRows(dataArray);
const ignoreSet = new Set(ignoreColumns);
const numericalCols = [];
const categoricalCols = [];
const categoryMappings = {};
const enable_slurm_id_if_exists = $("#enable_slurm_id_if_exists").is(":checked");
// Spalten einteilen in numerisch oder kategorisch + category mappings aufbauen
headers.forEach((header, colIndex) => {
if (ignoreSet.has(header)) return;
if (!enable_slurm_id_if_exists && header === "OO_Info_SLURM_JOB_ID") return;
const values = dataArray.map(row => row[colIndex]);
if (values.every(val => !isNaN(parseFloat(val)))) {
numericalCols.push({ name: header, index: colIndex });
} else {
categoricalCols.push({ name: header, index: colIndex });
const uniqueValues = [...new Set(values)];
categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
}
});
// Erzeuge UI für Checkboxen und Min/Max Inputs für numerische Spalten
const controlContainerId = "parallel-plot-controls";
let controlContainer = $("#" + controlContainerId);
if (controlContainer.length === 0) {
controlContainer = $('<div id="' + controlContainerId + '" style="margin-bottom:10px; display: flex;"></div>');
$("#parallel-plot").before(controlContainer);
} else {
controlContainer.empty();
}
// Map um Checkbox-Zustände und Min/Max-Werte zu speichern
const columnVisibility = {};
const minMaxLimits = {};
// Checkboxen + Min/Max Felder generieren mit Boxen, max-Breite, Umbruch und Zeilenumbruch nach jeder Box
headers.forEach((header) => {
try {
if (ignoreSet.has(header)) return;
if (!enable_slurm_id_if_exists && header === "OO_Info_SLURM_JOB_ID") return;
const isNumerical = numericalCols.some(col => col.name === header);
const checkboxId = `chk_${header}`;
const minInputId = `min_${header}`;
const maxInputId = `max_${header}`;
columnVisibility[header] = true;
minMaxLimits[header] = { min: null, max: null };
// Wrapper Box mit max-Breite, Umbruch, Block-Level-Element für newline nach jeder Box
const boxWrapper = $('<div></div>').css({
border: "1px solid #ddd",
borderRadius: "8px",
padding: "12px 16px",
marginBottom: "12px",
boxShadow: "0 2px 6px rgba(0,0,0,0.1)",
backgroundColor: "#fff",
display: "flex",
flexWrap: "wrap",
alignItems: "center",
gap: "15px",
maxWidth: "350px",
width: "100%", // damit bei kleinen Screens die Box maximal voll breit ist
boxSizing: "border-box"
});
// Innerer Container mit Flexbox für Ausrichtung der Elemente, flex-grow damit Inputs genug Platz bekommen
const container = $('<div></div>').css({
display: "flex",
alignItems: "center",
gap: "10px",
flexWrap: "wrap",
flexGrow: 1,
minWidth: "0" // wichtig für flexbox Overflow Handling
});
// Checkbox mit Label
const checkbox = $(`<input type="checkbox" id="${checkboxId}" checked />`);
const label = $(`<label for="${checkboxId}" style="font-weight: 600; min-width: 140px; cursor: pointer; white-space: nowrap;">${header}</label>`);
container.append(checkbox).append(label);
if (isNumerical) {
// Werte ermitteln (nur gültige Zahlen)
const numericValues = dataArray
.map(row => parseFloat(row[headers.indexOf(header)]))
.filter(val => !isNaN(val));
const minVal = numericValues.length > 0 ? Math.min(...numericValues) : 0;
const maxVal = numericValues.length > 0 ? Math.max(...numericValues) : 100;
// Min Input mit Label
const minWrapper = $('<div></div>').css({
display: "flex",
flexDirection: "column",
alignItems: "flex-start",
minWidth: "90px"
});
const minLabel = $('<label></label>').attr("for", minInputId).text("Min").css({
fontSize: "0.75rem",
color: "#555",
marginBottom: "2px"
});
const minInput = $(`<input type="number" id="${minInputId}" placeholder="min" />`).css({
width: "80px",
padding: "5px 8px",
borderRadius: "5px",
border: "1px solid #ccc",
boxShadow: "inset 0 1px 3px rgba(0,0,0,0.1)",
transition: "border-color 0.3s ease"
});
minInput.attr("min", minVal);
minInput.attr("max", maxVal);
minInput.on("focus", function () {
$(this).css("border-color", "#007BFF");
});
minInput.on("blur", function () {
$(this).css("border-color", "#ccc");
});
minWrapper.append(minLabel).append(minInput);
// Max Input mit Label
const maxWrapper = $('<div></div>').css({
display: "flex",
flexDirection: "column",
alignItems: "flex-start",
minWidth: "90px"
});
const maxLabel = $('<label></label>').attr("for", maxInputId).text("Max").css({
fontSize: "0.75rem",
color: "#555",
marginBottom: "2px"
});
const maxInput = $(`<input type="number" id="${maxInputId}" placeholder="max" />`).css({
width: "80px",
padding: "5px 8px",
borderRadius: "5px",
border: "1px solid #ccc",
boxShadow: "inset 0 1px 3px rgba(0,0,0,0.1)",
transition: "border-color 0.3s ease"
});
maxInput.attr("min", minVal);
maxInput.attr("max", maxVal);
maxInput.on("focus", function () {
$(this).css("border-color", "#007BFF");
});
maxInput.on("blur", function () {
$(this).css("border-color", "#ccc");
});
maxWrapper.append(maxLabel).append(maxInput);
// Events für min/max Eingaben
minInput.on("input", function () {
const val = parseFloat($(this).val());
minMaxLimits[header].min = isNaN(val) ? null : val;
updatePlot();
});
maxInput.on("input", function () {
const val = parseFloat($(this).val());
minMaxLimits[header].max = isNaN(val) ? null : val;
updatePlot();
});
container.append(minWrapper).append(maxWrapper);
}
// Checkbox Change Event
checkbox.on("change", function () {
columnVisibility[header] = $(this).is(":checked");
updatePlot();
});
boxWrapper.append(container);
// Jede Box bekommt ihren eigenen Block (also newline)
controlContainer.append(boxWrapper);
} catch (error) {
console.error(`Fehler bei Header '${header}':`, error);
}
});
// Erzeuge Ergebnis-Auswahl für Farbskala (color by result)
const resultSelectId = "result-select";
let resultSelect = $(`#${resultSelectId}`);
if (resultSelect.length === 0) {
resultSelect = $(`<select id="${resultSelectId}"></select>`);
controlContainer.before(resultSelect);
} else {
resultSelect.empty();
}
resultSelect.append('<option value="none">No color</option>');
for (let i = 0; i < resultNames.length; i++) {
let minMaxInfo = "min [auto]";
if (typeof result_min_max !== "undefined" && result_min_max[i] !== undefined) {
minMaxInfo = result_min_max[i];
}
resultSelect.append(`<option value="${resultNames[i]}">${resultNames[i]} (${minMaxInfo})</option>`);
}
let colorValues = null;
let colorScale = null;
resultSelect.off("change").on("change", function () {
const selectedResult = $(this).val();
if (selectedResult === "none") {
colorValues = null;
colorScale = null;
} else {
const col = numericalCols.find(c => c.name.toLowerCase() === selectedResult.toLowerCase());
if (!col) {
colorValues = null;
colorScale = null;
updatePlot();
return;
}
colorValues = dataArray.map(row => parseFloat(row[col.index]));
let invertColor = false;
if (typeof result_min_max !== "undefined") {
const idx = resultNames.indexOf(selectedResult);
if (idx !== -1) {
invertColor = result_min_max[idx] === "max";
}
}
colorScale = invertColor
? [[0, 'red'], [1, 'green']]
: [[0, 'green'], [1, 'red']];
}
updatePlot();
});
// Initial Auswahl: kein Farbwert, oder erstes Ergebnis falls nur eins
if (resultNames.length === 1) {
resultSelect.val(resultNames[0]).trigger("change");
} else {
resultSelect.val("none").trigger("change");
}
function updatePlot() {
try {
// Filter Spalten nach Checkboxen
const filteredNumericalCols = numericalCols.filter(col => columnVisibility[col.name]);
const filteredCategoricalCols = categoricalCols.filter(col => columnVisibility[col.name]);
// Filtere die Datenzeilen, um nur die zu behalten, die innerhalb aller gesetzten Min/Max Limits liegen
const filteredData = dataArray.filter(row => {
for (let col of filteredNumericalCols) {
const val = parseFloat(row[col.index]);
if (isNaN(val)) return false; // ungültiger Wert raus
const limits = minMaxLimits[col.name];
if (limits.min !== null && val < limits.min) return false;
if (limits.max !== null && val > limits.max) return false;
}
// Kategorische Werte ignorieren Filter (könntest hier evtl. erweitern)
return true;
});
const dimensions = [];
// Füge numerische Dimensionen hinzu mit Min/Max Limits (Range anhand gefilterter Daten)
filteredNumericalCols.forEach(col => {
let vals = filteredData.map(row => parseFloat(row[col.index]));
// Fallback falls alle Werte NaN (sollte eigentlich nicht vorkommen)
const realMin = vals.length > 0 ? Math.min(...vals) : 0;
const realMax = vals.length > 0 ? Math.max(...vals) : 100;
dimensions.push({
label: col.name,
values: vals,
range: [realMin, realMax]
});
});
// Kategorische Dimensionen (aus gefilterten Daten)
filteredCategoricalCols.forEach(col => {
const vals = filteredData.map(row => categoryMappings[col.name][row[col.index]]);
dimensions.push({
label: col.name,
values: vals,
tickvals: Object.values(categoryMappings[col.name]),
ticktext: Object.keys(categoryMappings[col.name])
});
});
// Linienfarbe bestimmen, falls Farbskala gesetzt ist
let filteredColorValues = null;
if (colorValues) {
// Da colorValues für alle Daten sind, filtere sie auch entsprechend
filteredColorValues = filteredData.map(row => {
const col = numericalCols.find(c => c.name.toLowerCase() === resultSelect.val().toLowerCase());
return col ? parseFloat(row[col.index]) : null;
});
}
const trace = {
type: 'parcoords',
dimensions: dimensions,
line: filteredColorValues ? { color: filteredColorValues, colorscale: colorScale } : {},
unselected: {
line: {
color: get_text_color(),
opacity: 0
}
},
};
dimensions.forEach(dim => {
if (!dim.line) {
dim.line = {};
}
if (!dim.line.color) {
dim.line.color = 'rgba(169,169,169, 0.01)';
}
});
Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
make_text_in_parallel_plot_nicer();
} catch (error) {
console.error("Fehler in updatePlot():", error);
}
}
updatePlot();
$("#parallel-plot").data("loaded", "true");
make_text_in_parallel_plot_nicer();
} catch (err) {
console.error("Error in createParallelPlot:", err);
}
}
function plotWorkerUsage() {
if($("#workerUsagePlot").data("loaded") == "true") {
return;
}
var data = tab_worker_usage_csv_json;
if (!Array.isArray(data) || data.length === 0) {
console.error("Invalid or empty data provided.");
return;
}
let timestamps = [];
let desiredWorkers = [];
let realWorkers = [];
for (let i = 0; i < data.length; i++) {
let entry = data[i];
if (!Array.isArray(entry) || entry.length < 3) {
console.warn("Skipping invalid entry:", entry);
continue;
}
let unixTime = parseFloat(entry[0]);
let desired = parseInt(entry[1], 10);
let real = parseInt(entry[2], 10);
if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
console.warn("Skipping invalid numerical values:", entry);
continue;
}
timestamps.push(new Date(unixTime * 1000).toISOString());
desiredWorkers.push(desired);
realWorkers.push(real);
}
let trace1 = {
x: timestamps,
y: desiredWorkers,
mode: 'lines+markers',
name: 'Desired Workers',
line: {
color: 'blue'
}
};
let trace2 = {
x: timestamps,
y: realWorkers,
mode: 'lines+markers',
name: 'Real Workers',
line: {
color: 'red'
}
};
let layout = {
title: "Worker Usage Over Time",
xaxis: {
title: get_axis_title_data("Time", "date")
},
yaxis: {
title: get_axis_title_data("Number of Workers")
},
legend: {
x: 0,
y: 1
}
};
Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
$("#workerUsagePlot").data("loaded", "true");
}
function plotCPUAndRAMUsage() {
if($("#mainWorkerCPURAM").data("loaded") == "true") {
return;
}
var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
var trace1 = {
x: timestamps,
y: cpuUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'CPU Usage (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: ramUsage,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'RAM Usage (MB)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'CPU and RAM Usage Over Time',
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
overlaying: 'y',
side: 'right',
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var data = [trace1, trace2];
Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
$("#mainWorkerCPURAM").data("loaded", "true");
}
function plotScatter2d() {
if ($("#plotScatter2d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter2d");
var minInput = document.getElementById("minValue");
var maxInput = document.getElementById("maxValue");
if (!minInput || !maxInput) {
minInput = document.createElement("input");
minInput.id = "minValue";
minInput.type = "number";
minInput.placeholder = "Min Value";
minInput.step = "any";
maxInput = document.createElement("input");
maxInput.id = "maxValue";
maxInput.type = "number";
maxInput.placeholder = "Max Value";
maxInput.step = "any";
var inputContainer = document.createElement("div");
inputContainer.style.marginBottom = "10px";
inputContainer.appendChild(minInput);
inputContainer.appendChild(maxInput);
plotDiv.appendChild(inputContainer);
}
var resultSelect = document.getElementById("resultSelect");
if (result_names.length > 1 && !resultSelect) {
resultSelect = document.createElement("select");
resultSelect.id = "resultSelect";
resultSelect.style.marginBottom = "10px";
var sortedResults = [...result_names].sort();
sortedResults.forEach(result => {
var option = document.createElement("option");
option.value = result;
option.textContent = result;
resultSelect.appendChild(option);
});
var selectContainer = document.createElement("div");
selectContainer.style.marginBottom = "10px";
selectContainer.appendChild(resultSelect);
plotDiv.appendChild(selectContainer);
}
minInput.addEventListener("input", updatePlots);
maxInput.addEventListener("input", updatePlots);
if (resultSelect) {
resultSelect.addEventListener("change", updatePlots);
}
updatePlots();
async function updatePlots() {
var minValue = parseFloat(minInput.value);
var maxValue = parseFloat(maxInput.value);
if (isNaN(minValue)) minValue = -Infinity;
if (isNaN(maxValue)) maxValue = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var selectedResult = resultSelect ? resultSelect.value : result_names[0];
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 2) {
console.error("Not enough columns for Scatter-Plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
showlegend: false
};
let subDiv = document.createElement("div");
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
symbol: data.map(d => d.result === null ? 'x' : 'circle'),
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter',
showlegend: false
};
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
$("#plotScatter2d").data("loaded", "true");
}
function plotScatter3d() {
if ($("#plotScatter3d").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotScatter3d");
if (!plotDiv) {
console.error("Div element with id 'plotScatter3d' not found");
return;
}
plotDiv.innerHTML = "";
var minInput3d = document.getElementById("minValue3d");
var maxInput3d = document.getElementById("maxValue3d");
if (!minInput3d || !maxInput3d) {
minInput3d = document.createElement("input");
minInput3d.id = "minValue3d";
minInput3d.type = "number";
minInput3d.placeholder = "Min Value";
minInput3d.step = "any";
maxInput3d = document.createElement("input");
maxInput3d.id = "maxValue3d";
maxInput3d.type = "number";
maxInput3d.placeholder = "Max Value";
maxInput3d.step = "any";
var inputContainer3d = document.createElement("div");
inputContainer3d.style.marginBottom = "10px";
inputContainer3d.appendChild(minInput3d);
inputContainer3d.appendChild(maxInput3d);
plotDiv.appendChild(inputContainer3d);
}
var select3d = document.getElementById("select3dScatter");
if (result_names.length > 1 && !select3d) {
if (!select3d) {
select3d = document.createElement("select");
select3d.id = "select3dScatter";
select3d.style.marginBottom = "10px";
select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
select3d.addEventListener("change", updatePlots3d);
plotDiv.appendChild(select3d);
}
}
minInput3d.addEventListener("input", updatePlots3d);
maxInput3d.addEventListener("input", updatePlots3d);
updatePlots3d();
async function updatePlots3d() {
var selectedResult = select3d ? select3d.value : result_names[0];
var minValue3d = parseFloat(minInput3d.value);
var maxValue3d = parseFloat(maxInput3d.value);
if (isNaN(minValue3d)) minValue3d = -Infinity;
if (isNaN(maxValue3d)) maxValue3d = Infinity;
while (plotDiv.children.length > 2) {
plotDiv.removeChild(plotDiv.lastChild);
}
var resultIndex = tab_results_headers_json.findIndex(header =>
header.toLowerCase() === selectedResult.toLowerCase()
);
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 3) {
console.error("Not enough columns for 3D scatter plots");
return;
}
for (let i = 0; i < numericColumns.length; i++) {
for (let j = i + 1; j < numericColumns.length; j++) {
for (let k = j + 1; k < numericColumns.length; k++) {
let xCol = numericColumns[i];
let yCol = numericColumns[j];
let zCol = numericColumns[k];
let xIndex = tab_results_headers_json.indexOf(xCol);
let yIndex = tab_results_headers_json.indexOf(yCol);
let zIndex = tab_results_headers_json.indexOf(zCol);
let data = tab_results_csv_json.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
z: parseFloat(row[zIndex]),
result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
}));
data = data.filter(d => d.result >= minResult && d.result <= maxResult);
let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
let layout = {
title: layoutTitle,
scene: {
xaxis: {
title: get_axis_title_data(xCol)
},
yaxis: {
title: get_axis_title_data(yCol)
},
zaxis: {
title: get_axis_title_data(zCol)
}
},
showlegend: false
};
let spinnerContainer = document.createElement("div");
spinnerContainer.style.display = "flex";
spinnerContainer.style.alignItems = "center";
spinnerContainer.style.justifyContent = "center";
spinnerContainer.style.width = layout.width + "px";
spinnerContainer.style.height = layout.height + "px";
spinnerContainer.style.position = "relative";
let spinner = document.createElement("div");
spinner.className = "spinner";
spinner.style.width = "40px";
spinner.style.height = "40px";
let loadingText = document.createElement("span");
loadingText.innerText = `Loading ${layoutTitle}`;
loadingText.style.marginLeft = "10px";
spinnerContainer.appendChild(spinner);
spinnerContainer.appendChild(loadingText);
plotDiv.appendChild(spinnerContainer);
await new Promise(resolve => setTimeout(resolve, 50));
let colors = data.map(d => {
if (d.result === null) {
return 'rgb(0, 0, 0)';
} else {
let norm = (d.result - minResult) / (maxResult - minResult);
if (invertColor) {
norm = 1 - norm;
}
return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
}
});
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
z: data.map(d => d.z),
mode: 'markers',
marker: {
size: get_marker_size(),
color: data.map(d => d.result !== null ? d.result : null),
colorscale: invertColor ? [
[0, 'red'],
[1, 'green']
] : [
[0, 'green'],
[1, 'red']
],
colorbar: {
title: 'Result',
tickvals: [minResult, maxResult],
ticktext: [`${minResult}`, `${maxResult}`]
},
},
text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
type: 'scatter3d',
showlegend: false
};
let subDiv = document.createElement("div");
try {
plotDiv.replaceChild(subDiv, spinnerContainer);
} catch (err) {
//
}
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
}
}
$("#plotScatter3d").data("loaded", "true");
}
async function plot_worker_cpu_ram() {
if($("#worker_cpu_ram_pre").data("loaded") == "true") {
return;
}
const logData = $("#worker_cpu_ram_pre").text();
const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
const hostData = {};
logData.split("\n").forEach(line => {
line = line.trim();
const match = line.match(regex);
if (match) {
const timestamp = new Date(parseInt(match[1]) * 1000);
const hostname = match[2];
const cpu = parseFloat(match[3]);
const ram = parseFloat(match[4]);
if (!hostData[hostname]) {
hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
}
hostData[hostname].timestamps.push(timestamp);
hostData[hostname].cpuUsage.push(cpu);
hostData[hostname].ramUsage.push(ram);
}
});
if (!Object.keys(hostData).length) {
console.log("No valid data found");
return;
}
const container = document.getElementById("cpuRamWorkerChartContainer");
container.innerHTML = "";
var i = 1;
Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
const chartId = `workerChart_${index}`;
const chartDiv = document.createElement("div");
chartDiv.id = chartId;
chartDiv.style.marginBottom = "40px";
container.appendChild(chartDiv);
const cpuTrace = {
x: timestamps,
y: cpuUsage,
mode: "lines+markers",
name: "CPU Usage (%)",
yaxis: "y1",
line: {
color: "red"
}
};
const ramTrace = {
x: timestamps,
y: ramUsage,
mode: "lines+markers",
name: "RAM Usage (MB)",
yaxis: "y2",
line: {
color: "blue"
}
};
const layout = {
title: `Worker CPU and RAM Usage - ${hostname}`,
xaxis: {
title: get_axis_title_data("Timestamp", "date")
},
yaxis: {
title: get_axis_title_data("CPU Usage (%)"),
side: "left",
color: "red"
},
yaxis2: {
title: get_axis_title_data("RAM Usage (MB)"),
side: "right",
overlaying: "y",
color: "blue"
},
showlegend: true
};
Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
i++;
});
$("#plot_worker_cpu_ram_button").remove();
$("#worker_cpu_ram_pre").data("loaded", "true");
}
function load_log_file(log_nr, filename) {
var pre_id = `single_run_${log_nr}_pre`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
fetch(url)
.then(response => response.json())
.then(data => {
if (data.data) {
$("#" + pre_id).html(data.data);
$("#" + pre_id).data("loaded", true);
} else {
log(`No 'data' key found in response.`);
}
$("#spinner_log_" + log_nr).remove();
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#spinner_log_" + log_nr).remove();
});
}
}
function load_debug_log () {
var pre_id = `here_debuglogs_go`;
if (!$("#" + pre_id).data("loaded")) {
const params = new URLSearchParams(window.location.search);
const user_id = params.get('user_id');
const experiment_name = params.get('experiment_name');
const run_nr = params.get('run_nr');
var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
fetch(url)
.then(response => response.json())
.then(data => {
$("#debug_log_spinner").remove();
if (data.data) {
try {
$("#" + pre_id).html(data.data);
} catch (err) {
$("#" + pre_id).text(`Error loading data: ${err}`);
}
$("#" + pre_id).data("loaded", true);
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
} else {
log(`No 'data' key found in response.`);
}
})
.catch(error => {
log(`Error loading log: ${error}`);
$("#debug_log_spinner").remove();
});
}
}
function plotBoxplot() {
if ($("#plotBoxplot").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough numeric columns for Boxplot");
return;
}
var resultIndex = tab_results_headers_json.findIndex(function(header) {
return result_names.includes(header.toLowerCase());
});
var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
var plotDiv = document.getElementById("plotBoxplot");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'box',
name: col,
boxmean: 'sd',
marker: {
color: 'rgb(0, 255, 0)'
},
};
});
let layout = {
title: 'Boxplot of Numerical Columns',
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Value")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotBoxplot").data("loaded", "true");
}
function plotHeatmap() {
if ($("#plotHeatmap").data("loaded") === "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col => {
if (special_col_names.includes(col) || result_names.includes(col)) {
return false;
}
if (!col.startsWith("OO_Info")) {
return true;
}
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.every(row => {
let value = parseFloat(row[index]);
return !isNaN(value) && isFinite(value);
});
});
if (numericColumns.length < 2) {
console.error("Not enough valid numeric columns for Heatmap");
return;
}
var columnData = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
return tab_results_csv_json.map(row => parseFloat(row[index]));
});
var dataMatrix = numericColumns.map((_, i) =>
numericColumns.map((_, j) => {
let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
return values.reduce((a, b) => a + b, 0) / values.length;
})
);
var trace = {
z: dataMatrix,
x: numericColumns,
y: numericColumns,
colorscale: 'Viridis',
type: 'heatmap'
};
var layout = {
xaxis: {
title: get_axis_title_data("Columns")
},
yaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
var plotDiv = document.getElementById("plotHeatmap");
plotDiv.innerHTML = "";
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotHeatmap").data("loaded", "true");
}
function plotHistogram() {
if ($("#plotHistogram").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Histogram");
return;
}
var plotDiv = document.getElementById("plotHistogram");
plotDiv.innerHTML = "";
const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
let traces = numericColumns.map((col, index) => {
let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
return {
x: data,
type: 'histogram',
name: col,
opacity: 0.7,
marker: {
color: colorPalette[index % colorPalette.length]
},
autobinx: true
};
});
let layout = {
title: 'Histogram of Numerical Columns',
xaxis: {
title: get_axis_title_data("Value")
},
yaxis: {
title: get_axis_title_data("Frequency")
},
showlegend: true,
barmode: 'overlay'
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotHistogram").data("loaded", "true");
}
function plotViolin() {
if ($("#plotViolin").data("loaded") == "true") {
return;
}
var numericColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !result_names.includes(col) &&
!col.startsWith("OO_Info") &&
tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
);
if (numericColumns.length < 1) {
console.error("Not enough columns for Violin Plot");
return;
}
var plotDiv = document.getElementById("plotViolin");
plotDiv.innerHTML = "";
let traces = numericColumns.map(col => {
let index = tab_results_headers_json.indexOf(col);
let data = tab_results_csv_json.map(row => parseFloat(row[index]));
return {
y: data,
type: 'violin',
name: col,
box: {
visible: true
},
line: {
color: 'rgb(0, 255, 0)'
},
marker: {
color: 'rgb(0, 255, 0)'
},
meanline: {
visible: true
},
};
});
let layout = {
title: 'Violin Plot of Numerical Columns',
yaxis: {
title: get_axis_title_data("Value")
},
xaxis: {
title: get_axis_title_data("Columns")
},
showlegend: false
};
Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
$("#plotViolin").data("loaded", "true");
}
function plotExitCodesPieChart() {
if ($("#plotExitCodesPieChart").data("loaded") == "true") {
return;
}
var exitCodes = tab_results_csv_json.map(row => row[tab_results_headers_json.indexOf("exit_code")]);
var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
counts[exitCode] = (counts[exitCode] || 0) + 1;
return counts;
}, {});
var labels = Object.keys(exitCodeCounts);
var values = Object.values(exitCodeCounts);
var plotDiv = document.getElementById("plotExitCodesPieChart");
plotDiv.innerHTML = "";
var trace = {
labels: labels,
values: values,
type: 'pie',
hoverinfo: 'label+percent',
textinfo: 'label+value',
marker: {
colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
}
};
var layout = {
title: 'Exit Code Distribution',
showlegend: true
};
Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
$("#plotExitCodesPieChart").data("loaded", "true");
}
function plotResultEvolution() {
if ($("#plotResultEvolution").data("loaded") == "true") {
return;
}
result_names.forEach(resultName => {
var relevantColumns = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
);
var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
var resultIndex = tab_results_headers_json.indexOf(resultName);
let data = tab_results_csv_json.map(row => ({
x: row[xColumnIndex],
y: parseFloat(row[resultIndex])
}));
data.sort((a, b) => a.x - b.x);
let xData = data.map(item => item.x);
let yData = data.map(item => item.y);
let trace = {
x: xData,
y: yData,
mode: 'lines+markers',
name: resultName,
line: {
shape: 'linear'
},
marker: {
size: get_marker_size()
}
};
let layout = {
title: `Evolution of ${resultName} over time`,
xaxis: {
title: get_axis_title_data("Trial-Index")
},
yaxis: {
title: get_axis_title_data(resultName)
},
showlegend: true
};
let subDiv = document.createElement("div");
document.getElementById("plotResultEvolution").appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
});
$("#plotResultEvolution").data("loaded", "true");
}
function plotResultPairs() {
if ($("#plotResultPairs").data("loaded") == "true") {
return;
}
var plotDiv = document.getElementById("plotResultPairs");
plotDiv.innerHTML = "";
for (let i = 0; i < result_names.length; i++) {
for (let j = i + 1; j < result_names.length; j++) {
let xName = result_names[i];
let yName = result_names[j];
let xIndex = tab_results_headers_json.indexOf(xName);
let yIndex = tab_results_headers_json.indexOf(yName);
let data = tab_results_csv_json
.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
.map(row => ({
x: parseFloat(row[xIndex]),
y: parseFloat(row[yIndex]),
status: row[tab_results_headers_json.indexOf("trial_status")]
}));
let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
let trace = {
x: data.map(d => d.x),
y: data.map(d => d.y),
mode: 'markers',
marker: {
size: get_marker_size(),
color: colors
},
text: data.map(d => `Status: ${d.status}`),
type: 'scatter',
showlegend: false
};
let layout = {
xaxis: {
title: get_axis_title_data(xName)
},
yaxis: {
title: get_axis_title_data(yName)
},
showlegend: false
};
let subDiv = document.createElement("div");
plotDiv.appendChild(subDiv);
Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
}
}
$("#plotResultPairs").data("loaded", "true");
}
function add_up_down_arrows_for_scrolling () {
const upArrow = document.createElement('div');
const downArrow = document.createElement('div');
const style = document.createElement('style');
style.innerHTML = `
.scroll-arrow {
position: fixed;
right: 10px;
z-index: 100;
cursor: pointer;
font-size: 25px;
display: none;
background-color: green;
color: white;
padding: 5px;
outline: 2px solid white;
box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
transition: background-color 0.3s, transform 0.3s;
}
.scroll-arrow:hover {
background-color: darkgreen;
transform: scale(1.1);
}
#up-arrow {
top: 10px;
}
#down-arrow {
bottom: 10px;
}
`;
document.head.appendChild(style);
upArrow.id = "up-arrow";
upArrow.classList.add("scroll-arrow");
upArrow.classList.add("invert_in_dark_mode");
upArrow.innerHTML = "↑";
downArrow.id = "down-arrow";
downArrow.classList.add("scroll-arrow");
downArrow.classList.add("invert_in_dark_mode");
downArrow.innerHTML = "↓";
document.body.appendChild(upArrow);
document.body.appendChild(downArrow);
function checkScrollPosition() {
const scrollPosition = window.scrollY;
const pageHeight = document.documentElement.scrollHeight;
const windowHeight = window.innerHeight;
if (scrollPosition > 0) {
upArrow.style.display = "block";
} else {
upArrow.style.display = "none";
}
if (scrollPosition + windowHeight < pageHeight) {
downArrow.style.display = "block";
} else {
downArrow.style.display = "none";
}
}
window.addEventListener("scroll", checkScrollPosition);
upArrow.addEventListener("click", function () {
window.scrollTo({ top: 0, behavior: 'smooth' });
});
downArrow.addEventListener("click", function () {
window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
});
checkScrollPosition();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
function plotGPUUsage() {
if ($("#tab_gpu_usage").data("loaded") === "true") {
return;
}
Object.keys(gpu_usage).forEach(node => {
const nodeData = gpu_usage[node];
var timestamps = [];
var gpuUtilizations = [];
var temperatures = [];
nodeData.forEach(entry => {
try {
var timestamp = new Date(entry[0]* 1000);
var utilization = parseFloat(entry[1]);
var temperature = parseFloat(entry[2]);
if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
timestamps.push(timestamp);
gpuUtilizations.push(utilization);
temperatures.push(temperature);
} else {
console.warn("Invalid data point:", entry);
}
} catch (error) {
console.error("Error processing GPU data entry:", error, entry);
}
});
var trace1 = {
x: timestamps,
y: gpuUtilizations,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'GPU Utilization (%)',
type: 'scatter',
yaxis: 'y1'
};
var trace2 = {
x: timestamps,
y: temperatures,
mode: 'lines+markers',
marker: {
size: get_marker_size(),
},
name: 'GPU Temperature (°C)',
type: 'scatter',
yaxis: 'y2'
};
var layout = {
title: 'GPU Usage Over Time - ' + node,
xaxis: {
title: get_axis_title_data("Timestamp", "date"),
tickmode: 'array',
tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
tickangle: -45
},
yaxis: {
title: get_axis_title_data("GPU Utilization (%)"),
overlaying: 'y',
rangemode: 'tozero'
},
yaxis2: {
title: get_axis_title_data("GPU Temperature (°C)"),
overlaying: 'y',
side: 'right',
position: 0.85,
rangemode: 'tozero'
},
legend: {
x: 0.1,
y: 0.9
}
};
var divId = 'gpu_usage_plot_' + node;
if (!document.getElementById(divId)) {
var div = document.createElement('div');
div.id = divId;
div.className = 'gpu-usage-plot';
document.getElementById('tab_gpu_usage').appendChild(div);
}
var plotData = [trace1, trace2];
Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
});
$("#tab_gpu_usage").data("loaded", "true");
}
function plotResultsDistributionByGenerationMethod() {
if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
return;
}
var res_col = result_names[0];
var gen_method_col = "generation_node";
var data = {};
tab_results_csv_json.forEach(row => {
var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
var result = row[tab_results_headers_json.indexOf(res_col)];
if (!data[gen_method]) {
data[gen_method] = [];
}
data[gen_method].push(result);
});
var traces = Object.keys(data).map(method => {
return {
y: data[method],
type: 'box',
name: method,
boxpoints: 'outliers',
jitter: 0.5,
pointpos: 0
};
});
var layout = {
title: 'Distribution of Results by Generation Method',
yaxis: {
title: get_axis_title_data(res_col)
},
xaxis: {
title: get_axis_title_data("Generation Method")
},
boxmode: 'group'
};
Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
}
function plotJobStatusDistribution() {
if ($("#plotJobStatusDistribution").data("loaded") === "true") {
return;
}
var status_col = "trial_status";
var status_counts = {};
tab_results_csv_json.forEach(row => {
var status = row[tab_results_headers_json.indexOf(status_col)];
if (status) {
status_counts[status] = (status_counts[status] || 0) + 1;
}
});
var statuses = Object.keys(status_counts);
var counts = Object.values(status_counts);
var colors = statuses.map((status, i) =>
status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
);
var trace = {
x: statuses,
y: counts,
type: 'bar',
marker: { color: colors }
};
var layout = {
title: 'Distribution of Job Status',
xaxis: { title: 'Trial Status' },
yaxis: { title: 'Nr. of jobs' }
};
Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
$("#plotJobStatusDistribution").data("loaded", "true");
}
function _colorize_table_entries_by_generation_method () {
document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
let text = el.textContent.toLowerCase();
let color = text.includes("manual") ? "green" :
text.includes("sobol") ? "orange" :
text.includes("saasbo") ? "pink" :
text.includes("uniform") ? "lightblue" :
text.includes("legacy_gpei") ? "sienna" :
text.includes("bo_mixed") ? "aqua" :
text.includes("randomforest") ? "darkseagreen" :
text.includes("external_generator") ? "purple" :
text.includes("botorch") ? "yellow" : "";
if (color !== "") {
el.style.backgroundColor = color;
}
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_trial_status () {
document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
el.textContent.includes("RUNNING") ? "orange" :
el.textContent.includes("FAILED") ? "red" :
el.textContent.includes("CANDIDATE") ? "lightblue" :
el.textContent.includes("ABANDONED") ? "yellow" : "";
if (color) el.style.backgroundColor = color;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_queue_time() {
let cells = [...document.querySelectorAll('[data-column-id="queue_time"]')];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
if (values.length === 0) return;
let min = Math.min(...values);
let max = Math.max(...values);
let range = max - min || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value)) return;
let ratio = (value - min) / range;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_run_time() {
let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
if (values.length === 0) return;
let min = Math.min(...values);
let max = Math.max(...values);
let range = max - min || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value)) return;
let ratio = (value - min) / range;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
}
function _colorize_table_entries_by_results() {
result_names.forEach((name, index) => {
let minMax = result_min_max[index];
let selector_query = `[data-column-id="${name}"]`;
let cells = [...document.querySelectorAll(selector_query)];
if (cells.length === 0) return;
let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
if (values.length === 0) return;
let logValues = values.map(v => Math.log(v));
let logMin = Math.min(...logValues);
let logMax = Math.max(...logValues);
let logRange = logMax - logMin || 1;
cells.forEach(el => {
let value = parseFloat(el.textContent);
if (isNaN(value) || value <= 0) return;
let logValue = Math.log(value);
let ratio = (logValue - logMin) / logRange;
if (minMax === "max") ratio = 1 - ratio;
let red = Math.round(255 * ratio);
let green = Math.round(255 * (1 - ratio));
el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
el.classList.add("invert_in_dark_mode");
});
});
}
function _colorize_table_entries_by_generation_node_or_hostname() {
["hostname", "generation_node"].forEach(element => {
let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
let cells = [...document.querySelectorAll(selector_query)];
if (cells.length === 0) return;
let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
let colorMap = {};
uniqueValues.forEach((value, index) => {
let hue = Math.round((360 / uniqueValues.length) * index);
colorMap[value] = `hsl(${hue}, 70%, 60%)`;
});
cells.forEach(el => {
let value = el.textContent.trim();
if (colorMap[value]) {
el.style.backgroundColor = colorMap[value];
el.classList.add("invert_in_dark_mode");
}
});
});
}
function colorize_table_entries () {
setTimeout(() => {
if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
_colorize_table_entries_by_trial_status();
_colorize_table_entries_by_results();
_colorize_table_entries_by_run_time();
_colorize_table_entries_by_queue_time();
_colorize_table_entries_by_generation_method();
_colorize_table_entries_by_generation_node_or_hostname();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
}, 300);
}
function add_colorize_to_gridjs_table () {
let searchInput = document.querySelector(".gridjs-search-input");
if (searchInput) {
searchInput.addEventListener("input", colorize_table_entries);
}
}
function updatePreWidths() {
var width = window.innerWidth * 0.95;
var pres = document.getElementsByTagName('pre');
for (var i = 0; i < pres.length; i++) {
pres[i].style.width = width + 'px';
}
}
function demo_mode(nr_sec = 3) {
let i = 0;
let tabs = $('menu[role="tablist"] > button');
setInterval(() => {
tabs.attr('aria-selected', 'false').removeClass('active');
let tab = tabs.eq(i % tabs.length);
tab.attr('aria-selected', 'true').addClass('active');
tab.trigger('click');
i++;
}, nr_sec * 1000);
}
function resizePlotlyCharts() {
const plotlyElements = document.querySelectorAll('.js-plotly-plot');
if (plotlyElements.length) {
const windowWidth = window.innerWidth;
const windowHeight = window.innerHeight;
const newWidth = windowWidth * 0.9;
const newHeight = windowHeight * 0.9;
plotlyElements.forEach(function(element, index) {
const layout = {
width: newWidth,
height: newHeight,
plot_bgcolor: 'rgba(0, 0, 0, 0)',
paper_bgcolor: 'rgba(0, 0, 0, 0)',
};
Plotly.relayout(element, layout)
});
}
make_text_in_parallel_plot_nicer();
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
function plotTimelineFromGlobals() {
if (
typeof tab_results_headers_json === "undefined" ||
typeof tab_results_csv_json === "undefined" ||
!Array.isArray(tab_results_headers_json) ||
!Array.isArray(tab_results_csv_json)
) {
console.warn("Global variables 'tab_results_headers_json' or 'tab_results_csv_json' missing or invalid.");
return null;
}
const headers = tab_results_headers_json;
const data = tab_results_csv_json;
const col = name => headers.indexOf(name);
const ix_trial_index = col("trial_index");
const ix_start_time = col("start_time");
const ix_end_time = col("end_time");
const ix_status = col("trial_status");
if ([ix_trial_index, ix_start_time, ix_end_time, ix_status].some(ix => ix === -1)) {
console.warn("One or more needed columns missing");
return null;
}
const traces = [];
// Add dummy traces for legend
traces.push({
type: "scatter",
mode: "lines",
x: [null, null],
y: [null, null],
line: { color: "green", width: 4 },
name: "COMPLETED",
showlegend: true,
hoverinfo: "none"
});
traces.push({
type: "scatter",
mode: "lines",
x: [null, null],
y: [null, null],
line: { color: "yellow", width: 4 },
name: "RUNNING",
showlegend: true,
hoverinfo: "none"
});
traces.push({
type: "scatter",
mode: "lines",
x: [null, null],
y: [null, null],
line: { color: "red", width: 4 },
name: "FAILED/OTHER",
showlegend: true,
hoverinfo: "none"
});
for (const row of data) {
const trial_index = row[ix_trial_index];
const start = row[ix_start_time];
const end = row[ix_end_time];
const status = row[ix_status];
if (
trial_index === "" || start === "" || end === "" ||
isNaN(start) || isNaN(end)
) continue;
let color = "red"; // default
if (status === "COMPLETED") color = "green";
else if (status === "RUNNING") color = "yellow";
traces.push({
type: "scatter",
mode: "lines",
x: [new Date(start * 1000), new Date(end * 1000)],
y: [trial_index, trial_index],
line: { color: color, width: 4 },
name: `Trial ${trial_index} (${status})`,
showlegend: false,
hoverinfo: "x+y+name"
});
}
if (traces.length <= 3) { // only dummy traces added
console.warn("No valid data for plotting found.");
return null;
}
const layout = {
title: "Trial Timeline",
xaxis: {
title: "Time",
type: "date"
},
yaxis: {
title: "Trial Index",
autorange: "reversed"
},
margin: { t: 50 }
};
Plotly.newPlot('plot_timeline', traces, add_default_layout_data(layout));
return true;
}
function createResultParameterCanvases(this_res_name) {
if (
typeof special_col_names === "undefined" ||
typeof result_names === "undefined" ||
typeof result_min_max === "undefined" ||
typeof tab_results_headers_json === "undefined" ||
typeof tab_results_csv_json === "undefined"
) {
console.error("Missing one or more required global variables.");
return null;
}
if (
!Array.isArray(special_col_names) ||
!Array.isArray(result_names) ||
!Array.isArray(result_min_max) ||
!Array.isArray(tab_results_headers_json) ||
!Array.isArray(tab_results_csv_json)
) {
console.error("All inputs must be arrays.");
return null;
}
function getColumnIndexMap(headers) {
var map = {};
for (var i = 0; i < headers.length; i++) {
map[headers[i]] = i;
}
return map;
}
function getColumnData(data, index) {
var result = [];
for (var i = 0; i < data.length; i++) {
result.push(data[i][index]);
}
return result;
}
function normalize(value, min, max) {
if (max === min) {
return 0.5;
}
return (value - min) / (max - min);
}
function interpolateColor(ratio, reverse) {
var r = reverse ? ratio : 1 - ratio;
var g = reverse ? 1 - ratio : ratio;
var b = 0;
r = Math.floor(r * 255);
g = Math.floor(g * 255);
return "rgb(" + r + "," + g + "," + b + ")";
}
function createCanvas(width, height) {
var canvas = document.createElement("canvas");
canvas.width = width;
canvas.height = height;
return canvas;
}
function isNumericArray(arr) {
for (var i = 0; i < arr.length; i++) {
var val = arr[i];
if (typeof val !== "number" || isNaN(val)) {
return false;
}
}
return true;
}
function findBestRowIndex() {
var bestIndex = 0;
for (var i = 1; i < tab_results_csv_json.length; i++) {
var better = false;
for (var r = 0; r < result_names.length; r++) {
var col = result_names[r];
var colIdx = header_map[col];
var goal = result_min_max[r]; // "min" or "max"
var valCurrent = tab_results_csv_json[i][colIdx];
var valBest = tab_results_csv_json[bestIndex][colIdx];
if (goal === "min" && valCurrent < valBest) {
better = true;
break;
}
if (goal === "max" && valCurrent > valBest) {
better = true;
break;
}
}
if (better) {
bestIndex = i;
}
}
return bestIndex;
}
var canvas_width = 1000;
var canvas_height = 100;
var header_map = getColumnIndexMap(tab_results_headers_json);
var parameter_columns = tab_results_headers_json.filter(function (name) {
return (
!special_col_names.includes(name) &&
!result_names.includes(name) &&
!name.startsWith("OO_Info_")
);
});
var container = document.createElement("div");
for (var r = 0; r < result_names.length; r++) {
var result_name = result_names[r];
if (this_res_name == result_name) {
var result_index = header_map[result_name];
var result_goal = result_min_max[r]; // "min" or "max"
var result_values = getColumnData(tab_results_csv_json, result_index);
var result_min = Math.min.apply(null, result_values);
var result_max = Math.max.apply(null, result_values);
var heading = document.createElement("h2");
heading.textContent = "Interpretation for result: " + result_name + " (goal: " + result_goal + ")";
heading.style.fontFamily = "sans-serif";
heading.style.marginTop = "24px";
heading.style.marginBottom = "12px";
container.appendChild(heading);
var table = document.createElement("table");
table.style.borderCollapse = "collapse";
table.style.marginBottom = "32px";
var thead = document.createElement("thead");
var headRow = document.createElement("tr");
var th1 = document.createElement("th");
th1.textContent = "Parameter";
th1.style.textAlign = "left";
th1.style.padding = "6px 12px";
var th2 = document.createElement("th");
th2.textContent = "Distribution of result";
th2.style.textAlign = "left";
th2.style.padding = "6px 12px";
headRow.appendChild(th1);
headRow.appendChild(th2);
thead.appendChild(headRow);
table.appendChild(thead);
var tbody = document.createElement("tbody");
for (var p = 0; p < parameter_columns.length; p++) {
var param_name = parameter_columns[p];
var param_index = header_map[param_name];
var param_values = getColumnData(tab_results_csv_json, param_index);
if (!isNumericArray(param_values)) {
continue;
}
var param_min = Math.min.apply(null, param_values);
var param_max = Math.max.apply(null, param_values);
var canvas = createCanvas(canvas_width, canvas_height);
canvas.classList.add("invert_in_dark_mode");
var ctx = canvas.getContext("2d");
ctx.fillStyle = "white";
ctx.fillRect(0, 0, canvas.width, canvas.height);
var x_groups = {};
for (var i = 0; i < tab_results_csv_json.length; i++) {
var raw_param = tab_results_csv_json[i][param_index];
var raw_result = tab_results_csv_json[i][result_index];
var x_ratio = normalize(raw_param, param_min, param_max);
var x = Math.floor(x_ratio * (canvas_width - 1));
if (!x_groups[x]) {
x_groups[x] = [];
}
x_groups[x].push(raw_result);
}
for (var x in x_groups) {
var values = x_groups[x];
values.sort(function (a, b) {
return a - b;
});
var stripe_height = canvas_height / values.length;
for (var i = 0; i < values.length; i++) {
var y_start = i * stripe_height;
var y_end = (i + 1) * stripe_height;
var value = values[i];
var result_ratio = normalize(value, result_min, result_max);
var color = interpolateColor(result_ratio, result_goal === "min");
ctx.beginPath();
ctx.strokeStyle = color;
ctx.lineWidth = 1;
ctx.moveTo(Number(x) + 0.5, y_start);
ctx.lineTo(Number(x) + 0.5, y_end);
ctx.stroke();
}
}
var row = document.createElement("tr");
var cell_param = document.createElement("td");
cell_param.textContent = param_name;
cell_param.style.padding = "4px 12px";
cell_param.style.verticalAlign = "top";
cell_param.style.fontFamily = "monospace";
cell_param.style.whiteSpace = "nowrap";
var cell_canvas = document.createElement("td");
cell_canvas.appendChild(canvas);
cell_canvas.style.padding = "4px 12px";
row.appendChild(cell_param);
row.appendChild(cell_canvas);
tbody.appendChild(row);
}
table.appendChild(tbody);
container.appendChild(table);
}
}
// === Summary: Best result ===
var bestIndex = findBestRowIndex();
var bestRow = tab_results_csv_json[bestIndex];
var ul = document.createElement("ul");
ul.style.margin = "0";
ul.style.paddingLeft = "24px";
// Alle Result-Spalten
for (var i = 0; i < result_names.length; i++) {
var name = result_names[i];
var val = bestRow[header_map[name]];
var li = document.createElement("li");
li.textContent = name + " = " + val;
ul.appendChild(li);
}
// Alle Parameter-Spalten (außer special_col_names)
for (var i = 0; i < tab_results_headers_json.length; i++) {
var name = tab_results_headers_json[i];
if (special_col_names.includes(name) || name.startsWith("OO_Info_") || result_names.includes(name)) {
continue;
}
var val = bestRow[header_map[name]];
var li = document.createElement("li");
li.textContent = name + " = " + val;
ul.appendChild(li);
}
return container;
}
function initializeResultParameterVisualizations() {
try {
var elements = $('.result_parameter_visualization');
if (!elements || elements.length === 0) {
console.warn('No .result_parameter_visualization elements found.');
return;
}
elements.each(function () {
var element = $(this);
if (element.data('initialized')) {
return; // Already initialized, skip
}
var resname = element.attr('data-resname');
if (!resname) {
console.error('Missing data-resname attribute for element:', this);
return;
}
try {
var html = createResultParameterCanvases(resname);
element.html(html);
element.data('initialized', true);
} catch (err) {
console.error('Error while calling createResultParameterCanvases for resname:', resname, err);
}
});
} catch (outerErr) {
console.error('Failed to initialize result parameter visualizations:', outerErr);
}
}
function plotParameterDistributionsByStatus() {
const container = document.getElementById('parameter_by_status_distribution');
if (!container) {
console.error("Kein Container mit id 'parameter_by_status_distribution' gefunden.");
return null;
}
if ($(container).data("loaded") === "true") {
return;
}
if (
typeof special_col_names === "undefined" ||
typeof result_names === "undefined" ||
typeof result_min_max === "undefined" ||
typeof tab_results_headers_json === "undefined" ||
typeof tab_results_csv_json === "undefined"
) {
console.error("Missing one or more required global variables.");
return null;
}
if (
!Array.isArray(special_col_names) ||
!Array.isArray(result_names) ||
!Array.isArray(result_min_max) ||
!Array.isArray(tab_results_headers_json) ||
!Array.isArray(tab_results_csv_json)
) {
console.error("All inputs must be arrays.");
return null;
}
container.innerHTML = "";
const statusIndex = tab_results_headers_json.indexOf("trial_status");
if (statusIndex < 0) {
container.textContent = "Kein 'trial_status' in den Daten gefunden.";
return null;
}
const trialStatuses = [...new Set(tab_results_csv_json.map(row => row[statusIndex]))].filter(s => s != null);
const paramCols = tab_results_headers_json.filter(col =>
!special_col_names.includes(col) &&
!result_names.includes(col)
);
for (const param of paramCols) {
const paramIndex = tab_results_headers_json.indexOf(param);
if (paramIndex < 0) continue;
const traces = [];
trialStatuses.forEach((status) => {
const filteredValues = tab_results_csv_json
.filter(row => row[statusIndex] === status)
.map(row => row[paramIndex])
.filter(val => val !== "" && val != null && !isNaN(val))
.map(Number);
if (filteredValues.length > 1) {
// Histogramm-Bins automatisch mit Plotly bestimmen lassen oder eigene
// Hier: bins in 20 Stück
const nbins = 20;
traces.push({
type: 'histogram',
x: filteredValues,
name: status,
opacity: 0.6,
xbingroup: 0,
marker: {color: getColorForStatus(status)},
nbinsx: nbins,
// für Overlay-Stil:
// histfunc: 'count', // default
// autobinx: false,
// xbins: {start: Math.min(...filteredValues), end: Math.max(...filteredValues), size: (Math.max(...filteredValues) - Math.min(...filteredValues)) / nbins}
});
}
});
if (traces.length > 0) {
const h2 = document.createElement('h2');
if(!param.startsWith("OO_Info_")) {
h2.textContent = `Histogram: ${param}`;
container.appendChild(h2);
const plotDiv = document.createElement('div');
plotDiv.style.marginBottom = '30px';
container.appendChild(plotDiv);
Plotly.newPlot(plotDiv, traces, {
barmode: 'overlay', // 'stack' oder 'overlay'
xaxis: {
title: { text: String(param) }, // Sicherstellen, dass es ein Textobjekt ist
automargin: true,
tickangle: -45, // Optional: bessere Lesbarkeit
titlefont: { size: 16 } // Optional: größerer Titel
},
yaxis: {
title: { text: 'Count' }, // Titel explizit als Objekt angeben
automargin: true,
titlefont: { size: 16 } // Optional: größerer Titel
},
margin: {
l: 60,
r: 30,
t: 30,
b: 80 // genug Platz für x-Achsentitel
},
legend: {
orientation: "h"
}
}, {
responsive: true
});
}
}
}
$(container).data("loaded", "true");
// Color mapping (falls nicht global)
function getColorForStatus(status) {
const baseAlpha = 0.5;
switch(status.toUpperCase()) {
case 'FAILED': return `rgba(214, 39, 40, ${baseAlpha})`;
case 'COMPLETED': return `rgba(44, 160, 44, ${baseAlpha})`;
case 'ABANDONED': return `rgba(255, 215, 0, ${baseAlpha})`;
case 'RUNNING': return `rgba(50, 50, 44, ${baseAlpha})`;
default:
const otherColors = [
`rgba(31, 119, 180, ${baseAlpha})`,
`rgba(255, 127, 14, ${baseAlpha})`,
`rgba(148, 103, 189, ${baseAlpha})`,
`rgba(140, 86, 75, ${baseAlpha})`,
`rgba(227, 119, 194, ${baseAlpha})`,
`rgba(127, 127, 127, ${baseAlpha})`,
`rgba(188, 189, 34, ${baseAlpha})`,
`rgba(23, 190, 207, ${baseAlpha})`
];
let hash = 0;
for (let i = 0; i < status.length; i++) {
hash = status.charCodeAt(i) + ((hash << 5) - hash);
}
const index = Math.abs(hash) % otherColors.length;
return otherColors[index];
}
}
resizePlotlyCharts();
}
window.addEventListener('load', updatePreWidths);
window.addEventListener('resize', updatePreWidths);
$(document).ready(function() {
colorize_table_entries();
add_up_down_arrows_for_scrolling();
add_colorize_to_gridjs_table();
});
window.addEventListener('resize', function() {
resizePlotlyCharts();
});
"use strict";
function get_row_by_index(idx) {
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
if(trial_index_col_idx == -1) {
error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
return null;
}
for (var i = 0; i < tab_results_csv_json.length; i++) {
var row = tab_results_csv_json[i];
var trial_index = row[trial_index_col_idx];
if (trial_index == idx) {
return row;
}
}
return null;
}
function load_pareto_graph_from_idxs () {
if (!Object.keys(window).includes("pareto_idxs")) {
error("pareto_idxs is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
if(pareto_idxs === null) {
var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
return;
}
var table = get_pareto_table_data_from_idx();
var html_tables = createParetoTablesFromData(table);
$("#pareto_from_idxs_table").html(html_tables);
renderParetoFrontPlots(table);
if (typeof apply_theme_based_on_system_preferences === 'function') {
apply_theme_based_on_system_preferences();
}
}
function renderParetoFrontPlots(data) {
try {
let container = document.getElementById("pareto_front_idxs_plot_container");
if (!container) {
console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
return;
}
container.innerHTML = "";
if(data === undefined || data === null) {
var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
return;
}
Object.keys(data).forEach((key, idx) => {
if (!key.startsWith("Pareto front for ")) return;
let label = key.replace("Pareto front for ", "");
let [xKey, yKey] = label.split("/");
if (!xKey || !yKey) {
console.warn("Could not extract two objectives from key:", key);
return;
}
let entries = data[key];
let x = [];
let y = [];
let hoverTexts = [];
entries.forEach((entry) => {
let results = entry.results || {};
let values = entry.values || {};
let xVal = (results[xKey] || [])[0];
let yVal = (results[yKey] || [])[0];
if (xVal === undefined || yVal === undefined) {
console.warn("Missing values for", xKey, yKey, "in", entry);
return;
}
x.push(xVal);
y.push(yVal);
let hoverInfo = [];
if ("trial_index" in values) {
hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
}
Object.keys(values)
.filter(k => k !== "trial_index")
.sort()
.forEach(k => {
hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
});
Object.keys(results)
.sort()
.forEach(k => {
hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
});
hoverTexts.push(hoverInfo.join("<br>"));
});
let wrapper = document.createElement("div");
wrapper.style.marginBottom = "30px";
let titleEl = document.createElement("h3");
titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
wrapper.appendChild(titleEl);
let divId = `pareto_plot_${idx}`;
let plotDiv = document.createElement("div");
plotDiv.id = divId;
plotDiv.style.width = "100%";
plotDiv.style.height = "400px";
wrapper.appendChild(plotDiv);
container.appendChild(wrapper);
let trace = {
x: x,
y: y,
text: hoverTexts,
hoverinfo: "text",
mode: "markers",
type: "scatter",
marker: {
size: 8,
color: 'rgb(31, 119, 180)',
line: {
width: 1,
color: 'black'
}
},
name: label
};
let layout = {
xaxis: { title: { text: xKey } },
yaxis: { title: { text: yKey } },
margin: { t: 10, l: 60, r: 20, b: 50 },
hovermode: "closest",
showlegend: false
};
Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
});
} catch (e) {
console.error("Error while rendering Pareto front plots:", e);
}
}
function createParetoTablesFromData(data) {
try {
var container = document.createElement("div");
var parsedData;
try {
parsedData = typeof data === "string" ? JSON.parse(data) : data;
} catch (e) {
console.error("JSON parsing failed:", e);
return container;
}
for (var sectionTitle in parsedData) {
if (!parsedData.hasOwnProperty(sectionTitle)) {
continue;
}
var sectionData = parsedData[sectionTitle];
var heading = document.createElement("h2");
heading.textContent = sectionTitle;
container.appendChild(heading);
var table = document.createElement("table");
table.style.borderCollapse = "collapse";
table.style.marginBottom = "2em";
table.style.width = "100%";
var thead = document.createElement("thead");
var headerRow = document.createElement("tr");
var allValueKeys = new Set();
var allResultKeys = new Set();
sectionData.forEach(entry => {
var values = entry.values || {};
var results = entry.results || {};
Object.keys(values).forEach(key => {
allValueKeys.add(key);
});
Object.keys(results).forEach(key => {
allResultKeys.add(key);
});
});
var sortedValueKeys = Array.from(allValueKeys).sort();
var sortedResultKeys = Array.from(allResultKeys).sort();
if (sortedValueKeys.includes("trial_index")) {
sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
sortedValueKeys.unshift("trial_index");
}
var allColumns = [...sortedValueKeys, ...sortedResultKeys];
allColumns.forEach(col => {
var th = document.createElement("th");
th.textContent = col;
th.style.border = "1px solid black";
th.style.padding = "4px";
headerRow.appendChild(th);
});
thead.appendChild(headerRow);
table.appendChild(thead);
var tbody = document.createElement("tbody");
sectionData.forEach(entry => {
var tr = document.createElement("tr");
allColumns.forEach(col => {
var td = document.createElement("td");
td.style.border = "1px solid black";
td.style.padding = "4px";
var value = null;
if (col in entry.values) {
value = entry.values[col];
} else if (col in entry.results) {
value = entry.results[col];
}
if (Array.isArray(value)) {
td.textContent = value.join(", ");
} else {
td.textContent = value !== null && value !== undefined ? value : "";
}
tr.appendChild(td);
});
tbody.appendChild(tr);
});
table.appendChild(tbody);
container.appendChild(table);
}
return container;
} catch (err) {
console.error("Unexpected error:", err);
var errorDiv = document.createElement("div");
errorDiv.textContent = "Error generating tables.";
return errorDiv;
}
}
function get_pareto_table_data_from_idx () {
if (!Object.keys(window).includes("pareto_idxs")) {
error("pareto_idxs is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_csv_json")) {
error("tab_results_csv_json is not defined");
return;
}
if (!Object.keys(window).includes("tab_results_headers_json")) {
error("tab_results_headers_json is not defined");
return;
}
var x_keys = Object.keys(pareto_idxs);
var tables = {};
for (var i = 0; i < x_keys.length; i++) {
var x_key = x_keys[i];
var y_keys = Object.keys(pareto_idxs[x_key]);
for (var j = 0; j < y_keys.length; j++) {
var y_key = y_keys[j];
var indices = pareto_idxs[x_key][y_key];
for (var k = 0; k < indices.length; k++) {
var idx = indices[k];
var row = get_row_by_index(idx);
if(row === null) {
error(`Error getting the row for index ${idx}`);
return;
}
var row_dict = {
"results": {},
"values": {},
};
for (var l = 0; l < tab_results_headers_json.length; l++) {
var header = tab_results_headers_json[l];
if (!special_col_names.includes(header) || header == "trial_index") {
var val = row[l];
if (result_names.includes(header)) {
if (!Object.keys(row_dict["results"]).includes(header)) {
row_dict["results"][header] = [];
}
row_dict["results"][header].push(val);
} else {
if (!Object.keys(row_dict["values"]).includes(header)) {
row_dict["values"][header] = [];
}
row_dict["values"][header].push(val);
}
}
}
var table_key = `Pareto front for ${x_key}/${y_key}`;
if(!Object.keys(tables).includes(table_key)) {
tables[table_key] = [];
}
tables[table_key].push(row_dict);
}
}
}
return tables;
}
function getMinMaxByResultName(resultName) {
try {
if (typeof resultName !== "string") {
error("Parameter resultName must be a string");
return;
}
if (!Array.isArray(result_names)) {
error("Global variable result_names is not an array or undefined");
return;
}
if (!Array.isArray(result_min_max)) {
error("Global variable result_min_max is not an array or undefined");
return;
}
if (result_names.length !== result_min_max.length) {
error("Global arrays result_names and result_min_max must have the same length");
return;
}
var index = result_names.indexOf(resultName);
if (index === -1) {
error("Result name '" + resultName + "' not found in result_names");
return;
}
var minMaxValue = result_min_max[index];
if (minMaxValue !== "min" && minMaxValue !== "max") {
error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
return;
}
return minMaxValue;
} catch (e) {
error("Unexpected error: " + e.message);
}
}
$(document).ready(function() {
colorize_table_entries();;
plotWorkerUsage();;
plotCPUAndRAMUsage();;
plotParameterDistributionsByStatus();;
plotTimelineFromGlobals();
colorize_table_entries();
});
</script>
<h1><img class='invert_icon' src='i/overview.svg' style='height: 1em' /> Overview</h1>
<button onclick="window.open('https://imageseg.scads.de/omniax/gui?partition=barnard&experiment_name=mnist_cpu&reservation=&account=&mem_gb=5&time=2400&worker_timeout=60&max_eval=500&num_parallel_jobs=50&gpus=0&num_random_steps=20&follow=1&live_share=1&send_anonymized_usage_stats=1&constraints=&result_names=VAL_ACC%3Dmax&run_program=python3%20.tests%2Fmnist%2Ftrain%20--epochs%20%25epochs%20--learning_rate%20%25lr%20--batch_size%20%25batch_size%20--hidden_size%20%25hidden_size%20--dropout%20%25dropout%20--activation%20%25activation%20--num_dense_layers%20%25num_dense_layers%20--init%20%25init%20--weight_decay%20%25weight_decay&cpus_per_task=1&nodes_per_job=1&seed=&dryrun=0&debug=0&revert_to_random_when_seemingly_exhausted=1&gridsearch=0&model=BOTORCH_MODULAR&external_generator=&n_estimators_randomforest=100&installation_method=clone&run_mode=local&disable_tqdm=0&verbose_tqdm=0&force_local_execution=0&auto_exclude_defective_hosts=0&show_sixel_general=0&show_sixel_trial_index_result=0&show_sixel_scatter=0&show_worker_percentage_table_at_end=0&occ=0&occ_type=euclid&no_sleep=0&slurm_use_srun=0&verbose_break_run_search_table=0&abbreviate_job_names=0&main_process_gb=8&max_nr_of_zero_results=50&slurm_signal_delay_s=0&max_failed_jobs=0&exclude=&username=&generation_strategy=&root_venv_dir=&workdir=&dont_jit_compile=0&fit_out_of_design=0&refit_on_cv=0&show_generate_time_table=0&dont_warm_start_refitting=0&max_attempts_for_generation=20&num_restarts=20&raw_samples=1024&max_abandoned_retrial=20&max_num_of_parallel_sruns=16&force_choice_for_ranges=0&no_transform_inputs=0&fit_abandoned=0&no_normalize_y=0&verbose=0&generate_all_jobs_at_once=1&flame_graph=0&checkout_to_latest_tested_version=0&parameter_0_name=epochs&parameter_0_type=range&parameter_0_min=10&parameter_0_max=200&parameter_0_number_type=int&parameter_0_log_scale=false&parameter_1_name=lr&parameter_1_type=range&parameter_1_min=0.0001&parameter_1_max=0.1&parameter_1_number_type=float&parameter_1_log_scale=false&parameter_2_name=batch_size&parameter_2_type=range&parameter_2_min=8&parameter_2_max=4096&parameter_2_number_type=int&parameter_2_log_scale=false&parameter_3_name=hidden_size&parameter_3_type=range&parameter_3_min=8&parameter_3_max=8192&parameter_3_number_type=int&parameter_3_log_scale=false&parameter_4_name=dropout&parameter_4_type=range&parameter_4_min=0&parameter_4_max=0.5&parameter_4_number_type=float&parameter_4_log_scale=false&parameter_5_name=activation&parameter_5_type=fixed&parameter_5_value=leaky_relu&parameter_6_name=num_dense_layers&parameter_6_type=range&parameter_6_min=1&parameter_6_max=4&parameter_6_number_type=int&parameter_6_log_scale=false&parameter_7_name=init&parameter_7_type=fixed&parameter_7_value=normal&parameter_8_name=weight_decay&parameter_8_type=range&parameter_8_min=0&parameter_8_max=1&parameter_8_number_type=float&parameter_8_log_scale=false&partition=barnard&num_parameters=9', '_blank')">GUI page with all the settings of this job</button><br><br><h2>Experiment overview </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Setting</th><th>Value </th></tr></thead><tbody><tr><td> Model for non-random steps</td><td>BOTORCH_MODULAR </td></tr><tr><td> Max. nr. evaluations</td><td>500 </td></tr><tr><td> Number random steps</td><td>20 </td></tr><tr><td> Nr. of workers (parameter)</td><td>50 </td></tr><tr><td> Main process memory (GB)</td><td>8 </td></tr><tr><td> Worker memory (GB)</td><td>5 </td></tr></tbody></table><h2>Job Summary per Generation Node</h2>
<table border='1' cellpadding='5' cellspacing='0'>
<thead><tr><th>Generation Node</th><th>Total</th><th>FAILED</th></tr></thead>
<tbody>
<tr><td>SOBOL</td><td>500</td><td>500</td></tr>
</tbody></table>
<h2>Experiment parameters </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Values</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> epochs</td><td>range</td><td>10</td><td>200</td><td></td><td>int</td><td>No </td></tr><tr><td> lr</td><td>range</td><td>0.0001</td><td>0.1</td><td></td><td>float</td><td>No </td></tr><tr><td> batch_size</td><td>range</td><td>8</td><td>4096</td><td></td><td>int</td><td>No </td></tr><tr><td> hidden_size</td><td>range</td><td>8</td><td>8192</td><td></td><td>int</td><td>No </td></tr><tr><td> dropout</td><td>range</td><td>0</td><td>0.5</td><td></td><td>float</td><td>No </td></tr><tr><td> activation</td><td>fixed</td><td></td><td></td><td>leaky_relu</td><td></td><td></td></tr><tr><td> num_dense_layers</td><td>range</td><td>1</td><td>4</td><td></td><td>int</td><td>No </td></tr><tr><td> init</td><td>fixed</td><td></td><td></td><td>normal</td><td></td><td></td></tr><tr><td> weight_decay</td><td>range</td><td>0</td><td>1</td><td></td><td>float</td><td>No </td></tr></tbody></table><h2>Number of evaluations</h2>
<table>
<tbody>
<tr>
<th>Failed</th>
<th>Succeeded</th>
<th>Running</th>
<th>Total</th>
</tr>
<tr>
<td>500</td>
<td>0</td>
<td>0</td>
<td>500</td>
</tr>
</tbody>
</table>
<h2>Result names and types</h2>
<table>
<tr><th>name</th><th>min/max</th></tr>
<tr>
<td>VAL_ACC</td>
<td>max</td>
</tr>
</table>
<h2>Last progressbar status</h2>
<tt>2025-07-23 07:16:16: Sobol, failed: 500 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs</tt><br>
<h2>Git-Version</h2>
<tt>Commit: 5c9229e7beea7e8d860579d9b9ce32bfeeae87df
</tt>
<h1><img class='invert_icon' src='i/csv.svg' style='height: 1em' /> Results</h1>
<div id='tab_results_csv_table'></div>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("tab_results_csv_table_pre")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'><img src='i/download.svg' style='height: 1em'> Download »results.csv« as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,submit_time,queue_time,start_time,end_time,run_time,program_string,VAL_ACC,exit_code,signal,hostname,OO_Info_SLURM_JOB_ID,arm_name,trial_status,generation_node,epochs,lr,batch_size,hidden_size,dropout,num_dense_layers,weight_decay,activation,init
0,1753190693,31,1753190724,1753190742,18,python3 .tests/mnist/train --epochs 119 --learning_rate 0.04547517540752887832 --batch_size 4096 --hidden_size 4774 --dropout 0.32788604497909545898 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.62162548303604125977,,1,,n1719,18578891,0_0,FAILED,SOBOL,119,0.04547517540752887832411488489,4096,4774,0.327886044979095458984375,4,0.621625483036041259765625,leaky_relu,normal
1,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 37 --learning_rate 0.08187936280146242141 --batch_size 263 --hidden_size 279 --dropout 0.01473537832498550415 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.16510647721588611603,,1,,n1720,18578887,1_0,FAILED,SOBOL,37,0.081879362801462421406206715346,263,279,0.014735378324985504150390625,1,0.16510647721588611602783203125,leaky_relu,normal
2,1753190693,31,1753190724,1753190730,6,python3 .tests/mnist/train --epochs 103 --learning_rate 0.01556215909915044902 --batch_size 3014 --hidden_size 6726 --dropout 0.21049671946093440056 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.81585886608809232712,,1,,n1719,18578892,2_0,FAILED,SOBOL,103,0.015562159099150449023674092075,3014,6726,0.210496719460934400558471679688,2,0.815858866088092327117919921875,leaky_relu,normal
3,1753190695,29,1753190724,1753190755,31,python3 .tests/mnist/train --epochs 162 --learning_rate 0.05094199270252138673 --batch_size 1225 --hidden_size 2543 --dropout 0.39781150175258517265 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39737818669527769089,,1,,n1719,18578893,3_0,FAILED,SOBOL,162,0.05094199270252138672665509489,1225,2543,0.397811501752585172653198242188,3,0.397378186695277690887451171875,leaky_relu,normal
4,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 200 --learning_rate 0.01155153194935992257 --batch_size 785 --hidden_size 3509 --dropout 0.48275432456284761429 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.94342354964464902878,,1,,n1720,18578888,4_0,FAILED,SOBOL,200,0.011551531949359922571418657355,785,3509,0.482754324562847614288330078125,4,0.943423549644649028778076171875,leaky_relu,normal
5,1753190694,50,1753190744,1753190751,7,python3 .tests/mnist/train --epochs 64 --learning_rate 0.07211981368083507371 --batch_size 3084 --hidden_size 7710 --dropout 0.1704127797856926918 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.26908155810087919235,,1,,n1720,18578895,5_0,FAILED,SOBOL,64,0.072119813680835073710362337351,3084,7710,0.170412779785692691802978515625,1,0.269081558100879192352294921875,leaky_relu,normal
6,1753190693,30,1753190723,1753190754,31,python3 .tests/mnist/train --epochs 22 --learning_rate 0.03073621091721579282 --batch_size 1850 --hidden_size 1372 --dropout 0.11533369356766343117 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.74406123347580432892,,1,,n1720,18578884,6_0,FAILED,SOBOL,22,0.030736210917215792820522679563,1850,1372,0.115333693567663431167602539062,2,0.74406123347580432891845703125,leaky_relu,normal
7,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 134 --learning_rate 0.09193863467276096324 --batch_size 2106 --hidden_size 5886 --dropout 0.30351876327767968178 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.04340361244976520538,,1,,n1720,18578889,7_0,FAILED,SOBOL,134,0.091938634672760963240101261817,2106,5886,0.303518763277679681777954101562,3,0.04340361244976520538330078125,leaky_relu,normal
8,1753190695,54,1753190749,1753190756,7,python3 .tests/mnist/train --epochs 146 --learning_rate 0.01951632173424586517 --batch_size 1674 --hidden_size 7387 --dropout 0.0547425542026758194 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.91777744051069021225,,1,,n1720,18578900,8_0,FAILED,SOBOL,146,0.019516321734245865165968680799,1674,7387,0.05474255420267581939697265625,3,0.917777440510690212249755859375,leaky_relu,normal
9,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 10 --learning_rate 0.057890026364848024 --batch_size 2440 --hidden_size 3960 --dropout 0.36801899783313274384 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.37337908800691366196,,1,,n1720,18578890,9_0,FAILED,SOBOL,10,0.05789002636484802399863269784,2440,3960,0.36801899783313274383544921875,2,0.373379088006913661956787109375,leaky_relu,normal
10,1753190695,56,1753190751,1753190758,7,python3 .tests/mnist/train --epochs 76 --learning_rate 0.03838079315507784972 --batch_size 703 --hidden_size 5186 --dropout 0.40650656586512923241 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.64473813585937023163,,1,,n1720,18578897,10_0,FAILED,SOBOL,76,0.038380793155077849720946403522,703,5186,0.406506565865129232406616210938,1,0.64473813585937023162841796875,leaky_relu,normal
11,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 188 --learning_rate 0.07807154996600002006 --batch_size 3515 --hidden_size 1944 --dropout 0.21931778779253363609 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.06413633935153484344,,1,,n1720,18578885,11_0,FAILED,SOBOL,188,0.078071549966000020059908592884,3515,1944,0.219317787792533636093139648438,4,0.06413633935153484344482421875,leaky_relu,normal
12,1753190693,30,1753190723,1753190729,6,python3 .tests/mnist/train --epochs 174 --learning_rate 0.03478188869664446126 --batch_size 2676 --hidden_size 979 --dropout 0.1499941973015666008 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.51693118922412395477,,1,,n1720,18578886,12_0,FAILED,SOBOL,174,0.034781888696644461256290981055,2676,979,0.149994197301566600799560546875,3,0.51693118922412395477294921875,leaky_relu,normal
13,1753190695,49,1753190744,1753190751,7,python3 .tests/mnist/train --epochs 91 --learning_rate 0.09884393323194236303 --batch_size 1398 --hidden_size 4203 --dropout 0.4622173672541975975 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.19218694977462291718,,1,,n1720,18578898,13_0,FAILED,SOBOL,91,0.098843933231942363026867326425,1398,4203,0.462217367254197597503662109375,2,0.19218694977462291717529296875,leaky_relu,normal
14,1753190695,49,1753190744,1753190757,13,python3 .tests/mnist/train --epochs 49 --learning_rate 0.00440232499679550551 --batch_size 3662 --hidden_size 2867 --dropout 0.25178997637704014778 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.79558388050645589828,,1,,n1720,18578896,14_0,FAILED,SOBOL,49,0.004402324996795505505919887668,3662,2867,0.251789976377040147781372070312,1,0.795583880506455898284912109375,leaky_relu,normal
15,1753190695,49,1753190744,1753190751,7,python3 .tests/mnist/train --epochs 107 --learning_rate 0.0683180442947894373 --batch_size 340 --hidden_size 6275 --dropout 0.06348677026107907295 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.4953280305489897728,,1,,n1720,18578894,15_0,FAILED,SOBOL,107,0.068318044294789437298476286742,340,6275,0.063486770261079072952270507812,4,0.495328030548989772796630859375,leaky_relu,normal
16,1753190812,24,1753190836,1753190842,6,python3 .tests/mnist/train --epochs 113 --learning_rate 0.00124535889513790608 --batch_size 2386 --hidden_size 1095 --dropout 0.38922261074185371399 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14561120886355638504,,1,,n1720,18578913,16_0,FAILED,SOBOL,113,0.001245358895137906084585321942,2386,1095,0.3892226107418537139892578125,2,0.145611208863556385040283203125,leaky_relu,normal
17,1753190835,31,1753190866,1753190872,6,python3 .tests/mnist/train --epochs 55 --learning_rate 0.06535618589064107198 --batch_size 1620 --hidden_size 6128 --dropout 0.20144571363925933838 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.56299528200179338455,,1,,n1720,18578949,17_0,FAILED,SOBOL,55,0.065356185890641071978279796895,1620,6128,0.20144571363925933837890625,3,0.562995282001793384552001953125,leaky_relu,normal
18,1753190864,32,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 85 --learning_rate 0.03179266022872179881 --batch_size 3444 --hidden_size 3243 --dropout 0.02232909528538584709 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.41687381640076637268,,1,,n1719,18579001,18_0,FAILED,SOBOL,85,0.031792660228721798809647935968,3444,3243,0.022329095285385847091674804688,4,0.4168738164007663726806640625,leaky_relu,normal
19,1753190877,19,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.09565960339317099159 --batch_size 633 --hidden_size 7948 --dropout 0.33402595622465014458 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.87448965385556221008,,1,,n1719,18579049,19_0,FAILED,SOBOL,168,0.095659603393170991592064922315,633,7948,0.334025956224650144577026367188,1,0.8744896538555622100830078125,leaky_relu,normal
20,1753190890,6,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 182 --learning_rate 0.04222384893205017448 --batch_size 1472 --hidden_size 6996 --dropout 0.29592188913375139236 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29638927057385444641,,1,,n1719,18579056,20_0,FAILED,SOBOL,182,0.042223848932050174476149351221,1472,6996,0.295921889133751392364501953125,2,0.2963892705738544464111328125,leaky_relu,normal
21,1753190889,7,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 70 --learning_rate 0.0805487714746035699 --batch_size 2750 --hidden_size 2309 --dropout 0.10919838491827249527 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99424130097031593323,,1,,n1719,18579054,21_0,FAILED,SOBOL,70,0.08054877147460356989761010027,2750,2309,0.109198384918272495269775390625,3,0.9942413009703159332275390625,leaky_relu,normal
22,1753190888,8,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 16 --learning_rate 0.02201457734219729873 --batch_size 398 --hidden_size 5047 --dropout 0.17899719858542084694 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.01609530765563249588,,1,,n1719,18579050,22_0,FAILED,SOBOL,16,0.022014577342197298726045318062,398,5047,0.178997198585420846939086914062,4,0.016095307655632495880126953125,leaky_relu,normal
23,1753190889,7,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 152 --learning_rate 0.06175411065882072115 --batch_size 3721 --hidden_size 33 --dropout 0.49180836835876107216 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.69324312824755907059,,1,,n1719,18579055,23_0,FAILED,SOBOL,152,0.061754110658820721146966548076,3721,33,0.491808368358761072158813476562,1,0.693243128247559070587158203125,leaky_relu,normal
24,1753190889,7,1753190896,1753190902,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.02796652501225471363 --batch_size 60 --hidden_size 2625 --dropout 0.24352808482944965363 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31481028348207473755,,1,,n1719,18579053,24_0,FAILED,SOBOL,140,0.027966525012254713628001567827,60,2625,0.24352808482944965362548828125,1,0.314810283482074737548828125,leaky_relu,normal
25,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 28 --learning_rate 0.08858358920393512304 --batch_size 3893 --hidden_size 6552 --dropout 0.43118660710752010345 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89822172373533248901,,1,,n1720,18579057,25_0,FAILED,SOBOL,28,0.088583589203935123035371645983,3893,6552,0.43118660710752010345458984375,4,0.898221723735332489013671875,leaky_relu,normal
26,1753190892,33,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 58 --learning_rate 0.00817502328474074488 --batch_size 1038 --hidden_size 740 --dropout 0.34479621564969420433 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.12270453665405511856,,1,,n1720,18579061,26_0,FAILED,SOBOL,58,0.008175023284740744883292151712,1038,740,0.344796215649694204330444335938,3,0.122704536654055118560791015625,leaky_relu,normal
27,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 194 --learning_rate 0.06932867090674117716 --batch_size 2827 --hidden_size 4468 --dropout 0.03298121830448508263 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.66429348383098840714,,1,,n1720,18579060,27_0,FAILED,SOBOL,194,0.069328670906741177160093059229,2827,4468,0.032981218304485082626342773438,2,0.664293483830988407135009765625,leaky_relu,normal
28,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 156 --learning_rate 0.01823117797318845809 --batch_size 3268 --hidden_size 5421 --dropout 0.08670460712164640427 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24294306430965662003,,1,,n1720,18579059,28_0,FAILED,SOBOL,156,0.018231177973188458091291508367,3268,5421,0.086704607121646404266357421875,1,0.242943064309656620025634765625,leaky_relu,normal
29,1753190892,33,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 97 --learning_rate 0.05458658206956461256 --batch_size 968 --hidden_size 1675 --dropout 0.27355387713760137558 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.5442995736375451088,,1,,n1720,18579062,29_0,FAILED,SOBOL,97,0.054586582069564612562651007011,968,1675,0.273553877137601375579833984375,4,0.544299573637545108795166015625,leaky_relu,normal
30,1753190891,34,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 43 --learning_rate 0.04914746912792325451 --batch_size 2305 --hidden_size 7633 --dropout 0.43800438614562153816 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.4445722624659538269,,1,,n1720,18579058,30_0,FAILED,SOBOL,43,0.049147469127923254506029593358,2305,7633,0.438004386145621538162231445312,3,0.444572262465953826904296875,leaky_relu,normal
31,1753190892,33,1753190925,1753190932,7,python3 .tests/mnist/train --epochs 125 --learning_rate 0.08457607923699543562 --batch_size 2050 --hidden_size 3687 --dropout 0.12531922059133648872 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.76821608096361160278,,1,,n1720,18579063,31_0,FAILED,SOBOL,125,0.084576079236995435617352256941,2050,3687,0.125319220591336488723754882812,2,0.768216080963611602783203125,leaky_relu,normal
32,1753191005,16,1753191021,1753191027,6,python3 .tests/mnist/train --epochs 129 --learning_rate 0.01326881769858300614 --batch_size 743 --hidden_size 209 --dropout 0.30879422789439558983 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43125533033162355423,,1,,n1720,18579075,32_0,FAILED,SOBOL,129,0.013268817698583006137180717587,743,209,0.308794227894395589828491210938,2,0.431255330331623554229736328125,leaky_relu,normal
33,1753191005,11,1753191016,1753191022,6,python3 .tests/mnist/train --epochs 41 --learning_rate 0.05177052574371919513 --batch_size 3554 --hidden_size 4968 --dropout 0.12196009745821356773 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.85546946991235017776,,1,,n1720,18579074,33_0,FAILED,SOBOL,41,0.051770525743719195133074606474,3554,4968,0.121960097458213567733764648438,3,0.855469469912350177764892578125,leaky_relu,normal
34,1753191005,16,1753191021,1753191027,6,python3 .tests/mnist/train --epochs 93 --learning_rate 0.04474420142527670008 --batch_size 1761 --hidden_size 2102 --dropout 0.16062025167047977448 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.13122984394431114197,,1,,n1720,18579073,34_0,FAILED,SOBOL,93,0.044744201425276700079258773712,1761,2102,0.16062025167047977447509765625,4,0.1312298439443111419677734375,leaky_relu,normal
35,1753191052,24,1753191076,1753191082,6,python3 .tests/mnist/train --epochs 157 --learning_rate 0.08427026354009285736 --batch_size 2528 --hidden_size 7044 --dropout 0.47332079522311687469 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.58201531693339347839,,1,,n1720,18579079,35_0,FAILED,SOBOL,157,0.084270263540092857357244326977,2528,7044,0.47332079522311687469482421875,1,0.5820153169333934783935546875,leaky_relu,normal
36,1753191072,33,1753191105,1753191112,7,python3 .tests/mnist/train --epochs 190 --learning_rate 0.02844115424733608885 --batch_size 3607 --hidden_size 8156 --dropout 0.40394197823479771614 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.0029346756637096405,,1,,n1720,18579080,36_0,FAILED,SOBOL,190,0.028441154247336088850550694929,3607,8156,0.403941978234797716140747070312,2,0.0029346756637096405029296875,leaky_relu,normal
37,1753191080,25,1753191105,1753191112,7,python3 .tests/mnist/train --epochs 61 --learning_rate 0.09276545393327251254 --batch_size 285 --hidden_size 3195 --dropout 0.21626807795837521553 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.70957758650183677673,,1,,n1720,18579081,37_0,FAILED,SOBOL,61,0.092765453933272512543339871627,285,3195,0.216268077958375215530395507812,3,0.7095775865018367767333984375,leaky_relu,normal
38,1753191118,17,1753191135,1753191141,6,python3 .tests/mnist/train --epochs 31 --learning_rate 0.01082227202691137674 --batch_size 2605 --hidden_size 5952 --dropout 0.00579774659126996994 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.30954999197274446487,,1,,n1720,18579091,38_0,FAILED,SOBOL,31,0.01082227202691137674106514055,2605,5952,0.005797746591269969940185546875,4,0.309549991972744464874267578125,leaky_relu,normal
39,1753191117,18,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 137 --learning_rate 0.0745124282001517757 --batch_size 1327 --hidden_size 1175 --dropout 0.31759760435670614243 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.977906753309071064,,1,,n1720,18579087,39_0,FAILED,SOBOL,137,0.074512428200151775703474754664,1327,1175,0.317597604356706142425537109375,1,0.977906753309071063995361328125,leaky_relu,normal
40,1753191118,17,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 149 --learning_rate 0.03921075509116053737 --batch_size 2973 --hidden_size 3766 --dropout 0.07420253334566950798 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10826213657855987549,,1,,n1720,18579090,40_0,FAILED,SOBOL,149,0.039210755091160537366690164163,2973,3766,0.074202533345669507980346679688,1,0.10826213657855987548828125,leaky_relu,normal
41,1753191118,17,1753191135,1753191141,6,python3 .tests/mnist/train --epochs 19 --learning_rate 0.07577963783247396168 --batch_size 1184 --hidden_size 7456 --dropout 0.26091065956279635429 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68288627266883850098,,1,,n1720,18579089,41_0,FAILED,SOBOL,19,0.075779637832473961678303453482,1184,7456,0.260910659562796354293823242188,4,0.6828862726688385009765625,leaky_relu,normal
42,1753191118,17,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 73 --learning_rate 0.02190579320583492529 --batch_size 4008 --hidden_size 1626 --dropout 0.45675111934542655945 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.3292528325691819191,,1,,n1720,18579088,42_0,FAILED,SOBOL,73,0.021905793205834925285735437228,4008,1626,0.4567511193454265594482421875,3,0.329252832569181919097900390625,leaky_relu,normal
43,1753191117,18,1753191135,1753191142,7,python3 .tests/mnist/train --epochs 179 --learning_rate 0.05715762227820232744 --batch_size 174 --hidden_size 5628 --dropout 0.14392480999231338501 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.8796287858858704567,,1,,n1720,18579086,43_0,FAILED,SOBOL,179,0.057157622278202327437135465971,174,5628,0.143924809992313385009765625,2,0.879628785885870456695556640625,leaky_relu,normal
44,1753191118,17,1753191135,1753191141,6,python3 .tests/mnist/train --epochs 169 --learning_rate 0.00523400294650346043 --batch_size 1908 --hidden_size 4516 --dropout 0.22893436485901474953 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45730573777109384537,,1,,n1720,18579092,44_0,FAILED,SOBOL,169,0.005234002946503460429461540571,1908,4516,0.228934364859014749526977539062,1,0.457305737771093845367431640625,leaky_relu,normal
45,1753191135,33,1753191168,1753191174,6,python3 .tests/mnist/train --epochs 81 --learning_rate 0.06602784668626264508 --batch_size 2163 --hidden_size 533 --dropout 0.41672640154138207436 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75182049814611673355,,1,,n1720,18579095,45_0,FAILED,SOBOL,81,0.066027846686262645081733069219,2163,533,0.416726401541382074356079101562,4,0.751820498146116733551025390625,leaky_relu,normal
46,1753191135,31,1753191166,1753191172,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.0371696441546082515 --batch_size 857 --hidden_size 6473 --dropout 0.36145368684083223343 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.23020967841148376465,,1,,n1720,18579094,46_0,FAILED,SOBOL,52,0.037169644154608251496174631257,857,6473,0.361453686840832233428955078125,3,0.2302096784114837646484375,leaky_relu,normal
47,1753191135,31,1753191166,1753191172,6,python3 .tests/mnist/train --epochs 117 --learning_rate 0.09810981462029741418 --batch_size 3157 --hidden_size 2801 --dropout 0.04977220389991998672 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.56069506704807281494,,1,,n1720,18579096,47_0,FAILED,SOBOL,117,0.098109814620297414178295980491,3157,2801,0.049772203899919986724853515625,2,0.56069506704807281494140625,leaky_relu,normal
48,1753191253,33,1753191286,1753191299,13,python3 .tests/mnist/train --epochs 111 --learning_rate 0.0340861925455741635 --batch_size 1111 --hidden_size 5678 --dropout 0.49745771801099181175 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.82816515304148197174,,1,,n1720,18579101,48_0,FAILED,SOBOL,111,0.034086192545574163503818709842,1111,5678,0.497457718010991811752319335938,4,0.82816515304148197174072265625,leaky_relu,normal
49,1753191258,28,1753191286,1753191293,7,python3 .tests/mnist/train --epochs 47 --learning_rate 0.09483125977963209607 --batch_size 2900 --hidden_size 1421 --dropout 0.18524968763813376427 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.38043322600424289703,,1,,n1720,18579102,49_0,FAILED,SOBOL,47,0.094831259779632096074131197838,2900,1421,0.185249687638133764266967773438,1,0.38043322600424289703369140625,leaky_relu,normal
50,1753193953,37,1753193990,1753193996,6,python3 .tests/mnist/train --epochs 87 --learning_rate 0.00197614317061379531 --batch_size 116 --hidden_size 7887 --dropout 0.0987878013402223587 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60931927245110273361,,1,,n1720,18579857,50_0,FAILED,SOBOL,87,0.001976143170613795310708304953,116,7887,0.09878780134022235870361328125,2,0.609319272451102733612060546875,leaky_relu,normal
51,1753193953,36,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 175 --learning_rate 0.06296509572435170232 --batch_size 3950 --hidden_size 3429 --dropout 0.28710638545453548431 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.1820513484999537468,,1,,n1720,18579856,51_0,FAILED,SOBOL,175,0.062965095724351702322074686435,3950,3429,0.28710638545453548431396484375,3,0.182051348499953746795654296875,leaky_relu,normal
52,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 185 --learning_rate 0.02430944309579208609 --batch_size 2216 --hidden_size 2367 --dropout 0.34077436896041035652 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.72906957846134901047,,1,,n1720,18579853,52_0,FAILED,SOBOL,185,0.024309443095792086092510331241,2216,2367,0.340774368960410356521606445312,4,0.729069578461349010467529296875,leaky_relu,normal
53,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 79 --learning_rate 0.06092710197065025896 --batch_size 1961 --hidden_size 6806 --dropout 0.0274825473316013813 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.06156909745186567307,,1,,n1720,18579845,53_0,FAILED,SOBOL,79,0.06092710197065025895524215116,1961,6806,0.027482547331601381301879882812,1,0.061569097451865673065185546875,leaky_relu,normal
54,1753193954,35,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 13 --learning_rate 0.04295329977078363864 --batch_size 3227 --hidden_size 486 --dropout 0.19213431607931852341 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.95841535367071628571,,1,,n1720,18579858,54_0,FAILED,SOBOL,13,0.042953299770783638644733315459,3227,486,0.192134316079318523406982421875,2,0.95841535367071628570556640625,leaky_relu,normal
55,1753193950,13,1753193963,1753193969,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.07815634638294578773 --batch_size 927 --hidden_size 4726 --dropout 0.3793079545721411705 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25091592408716678619,,1,,n1720,18579847,55_0,FAILED,SOBOL,143,0.078156346382945787731877373972,927,4726,0.379307954572141170501708984375,3,0.25091592408716678619384765625,leaky_relu,normal
56,1753193950,39,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 131 --learning_rate 0.00734486968806013531 --batch_size 3373 --hidden_size 6226 --dropout 0.13541692821308970451 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.63212676253169775009,,1,,n1720,18579855,56_0,FAILED,SOBOL,131,0.007344869688060135307083875489,3373,6226,0.135416928213089704513549804688,3,0.632126762531697750091552734375,leaky_relu,normal
57,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 25 --learning_rate 0.07162039286829531559 --batch_size 562 --hidden_size 3074 --dropout 0.44774309499189257622 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.08089810516685247421,,1,,n1720,18579846,57_0,FAILED,SOBOL,25,0.071620392868295315591531391419,562,3074,0.447743094991892576217651367188,2,0.080898105166852474212646484375,leaky_relu,normal
58,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 67 --learning_rate 0.02557724520126357717 --batch_size 2331 --hidden_size 4282 --dropout 0.26846151426434516907 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93038890324532985687,,1,,n1720,18579844,58_0,FAILED,SOBOL,67,0.025577245201263577173422802957,2331,4282,0.2684615142643451690673828125,1,0.93038890324532985687255859375,leaky_relu,normal
59,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 196 --learning_rate 0.08931618346255272567 --batch_size 1564 --hidden_size 802 --dropout 0.08026130497455596924 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.3566172327846288681,,1,,n1720,18579852,59_0,FAILED,SOBOL,196,0.089316183462552725669247877249,1564,802,0.08026130497455596923828125,4,0.35661723278462886810302734375,leaky_relu,normal
60,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 163 --learning_rate 0.04831598283881322065 --batch_size 485 --hidden_size 1864 --dropout 0.0422240295447409153 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.81039257906377315521,,1,,n1720,18579851,60_0,FAILED,SOBOL,163,0.04831598283881322064559071805,485,1864,0.042224029544740915298461914062,3,0.81039257906377315521240234375,leaky_relu,normal
61,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 99 --learning_rate 0.08686646701749414778 --batch_size 3807 --hidden_size 5363 --dropout 0.35538984695449471474 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.47685722075402736664,,1,,n1720,18579848,61_0,FAILED,SOBOL,99,0.086866467017494147784262281675,3807,5363,0.355389846954494714736938476562,2,0.47685722075402736663818359375,leaky_relu,normal
62,1753193950,10,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 35 --learning_rate 0.01584323085462674419 --batch_size 1511 --hidden_size 4009 --dropout 0.42523923236876726151 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.50212263967841863632,,1,,n1720,18579849,62_0,FAILED,SOBOL,35,0.015843230854626744186219866606,1511,4009,0.425239232368767261505126953125,1,0.502122639678418636322021484375,leaky_relu,normal
63,1753193950,39,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 123 --learning_rate 0.0553205105092376484 --batch_size 2789 --hidden_size 7179 --dropout 0.23793982807546854019 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.21065761055797338486,,1,,n1720,18579854,63_0,FAILED,SOBOL,123,0.05532051050923764839994944964,2789,7179,0.237939828075468540191650390625,4,0.210657610557973384857177734375,leaky_relu,normal
64,1753193954,35,1753193989,1753193995,6,python3 .tests/mnist/train --epochs 121 --learning_rate 0.00982255834611132743 --batch_size 1352 --hidden_size 2955 --dropout 0.11837203986942768097 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02814712561666965485,,1,,n1720,18579859,64_0,FAILED,SOBOL,121,0.009822558346111327429173165626,1352,2955,0.11837203986942768096923828125,3,0.02814712561666965484619140625,leaky_relu,normal
65,1753193949,11,1753193960,1753193966,6,python3 .tests/mnist/train --epochs 36 --learning_rate 0.07394634587783366353 --batch_size 2630 --hidden_size 6187 --dropout 0.3065226580947637558 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.69656501151621341705,,1,,n1720,18579843,65_0,FAILED,SOBOL,36,0.073946345877833663529088426003,2630,6187,0.30652265809476375579833984375,2,0.69656501151621341705322265625,leaky_relu,normal
66,1753194165,33,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 101 --learning_rate 0.02944625098584219974 --batch_size 390 --hidden_size 875 --dropout 0.47019830858334898949 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.28433792572468519211,,1,,n1720,18579867,66_0,FAILED,SOBOL,101,0.029446250985842199743292013636,390,875,0.470198308583348989486694335938,1,0.284337925724685192108154296875,leaky_relu,normal
67,1753194169,29,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 162 --learning_rate 0.09332615319788456487 --batch_size 3712 --hidden_size 4307 --dropout 0.15788358589634299278 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.99091989081352949142,,1,,n1720,18579869,67_0,FAILED,SOBOL,162,0.093326153197884564871600332481,3712,4307,0.157883585896342992782592773438,4,0.990919890813529491424560546875,leaky_relu,normal
68,1753194164,6,1753194170,1753194176,6,python3 .tests/mnist/train --epochs 195 --learning_rate 0.04456930601252243052 --batch_size 2490 --hidden_size 5274 --dropout 0.21155166160315275192 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.41238844674080610275,,1,,n1720,18579866,68_0,FAILED,SOBOL,195,0.044569306012522430515687688057,2490,5274,0.211551661603152751922607421875,3,0.412388446740806102752685546875,leaky_relu,normal
69,1753194168,30,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 68 --learning_rate 0.08288279199972749256 --batch_size 1723 --hidden_size 1856 --dropout 0.39889302756637334824 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86311303358525037766,,1,,n1720,18579868,69_0,FAILED,SOBOL,68,0.082882791999727492560090524876,1723,1856,0.398893027566373348236083984375,2,0.863113033585250377655029296875,leaky_relu,normal
70,1753194169,29,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.01343680607276037317 --batch_size 3468 --hidden_size 7283 --dropout 0.31340719433501362801 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15009609796106815338,,1,,n1720,18579870,70_0,FAILED,SOBOL,27,0.01343680607276037317077133082,3468,7283,0.313407194335013628005981445312,1,0.15009609796106815338134765625,leaky_relu,normal
71,1753194175,23,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 130 --learning_rate 0.05316490432266146593 --batch_size 657 --hidden_size 4064 --dropout 0.00022230343893170357 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57437142170965671539,,1,,n1720,18579874,71_0,FAILED,SOBOL,130,0.053164904322661465929655832952,657,4064,0.000222303438931703567504882812,4,0.57437142170965671539306640625,leaky_relu,normal
72,1753194175,23,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 142 --learning_rate 0.03655887942025438236 --batch_size 3132 --hidden_size 1540 --dropout 0.26462446525692939758 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.4488072982057929039,,1,,n1720,18579875,72_0,FAILED,SOBOL,142,0.036558879420254382364152689888,3132,1540,0.2646244652569293975830078125,4,0.448807298205792903900146484375,leaky_relu,normal
73,1753194184,50,1753194234,1753194240,6,python3 .tests/mnist/train --epochs 15 --learning_rate 0.09716450110208244006 --batch_size 832 --hidden_size 5718 --dropout 0.07634784281253814697 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77935381140559911728,,1,,n1720,18579882,73_0,FAILED,SOBOL,15,0.097164501102082440064933166468,832,5718,0.07634784281253814697265625,1,0.779353811405599117279052734375,leaky_relu,normal
74,1753194183,45,1753194228,1753194235,7,python3 .tests/mnist/train --epochs 80 --learning_rate 0.00583786064228042963 --batch_size 2058 --hidden_size 3357 --dropout 0.147173288743942976 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.23870756290853023529,,1,,n1720,18579881,74_0,FAILED,SOBOL,80,0.005837860642280429633588223481,2058,3357,0.147173288743942975997924804688,2,0.23870756290853023529052734375,leaky_relu,normal
75,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 183 --learning_rate 0.06698006724305451132 --batch_size 1802 --hidden_size 7862 --dropout 0.45936224563047289848 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.53316137753427028656,,1,,n1720,18579877,75_0,FAILED,SOBOL,183,0.066980067243054511316735499804,1802,7862,0.459362245630472898483276367188,3,0.53316137753427028656005859375,leaky_relu,normal
76,1753194183,45,1753194228,1753194235,7,python3 .tests/mnist/train --epochs 174 --learning_rate 0.02056776805287226922 --batch_size 211 --hidden_size 6894 --dropout 0.42132493574172258377 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11041096411645412445,,1,,n1720,18579880,76_0,FAILED,SOBOL,174,0.02056776805287226922436261134,211,6894,0.421324935741722583770751953125,4,0.11041096411645412445068359375,leaky_relu,normal
77,1753194184,44,1753194228,1753194235,7,python3 .tests/mnist/train --epochs 89 --learning_rate 0.05693613863997162156 --batch_size 4045 --hidden_size 2375 --dropout 0.23410170618444681168 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.66072603128850460052,,1,,n1720,18579883,77_0,FAILED,SOBOL,89,0.056936138639971621555613268129,4045,2375,0.234101706184446811676025390625,1,0.66072603128850460052490234375,leaky_relu,normal
78,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 48 --learning_rate 0.04055416330182925327 --batch_size 1270 --hidden_size 4622 --dropout 0.05384401464834809303 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.32710434403270483017,,1,,n1720,18579876,78_0,FAILED,SOBOL,48,0.040554163301829253274188857858,1270,4622,0.053844014648348093032836914062,2,0.327104344032704830169677734375,leaky_relu,normal
79,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 109 --learning_rate 0.07599573841299862853 --batch_size 3058 --hidden_size 431 --dropout 0.36714728036895394325 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90178966429084539413,,1,,n1720,18579878,79_0,FAILED,SOBOL,109,0.075995738412998628530381495239,3058,431,0.367147280368953943252563476562,3,0.901789664290845394134521484375,leaky_relu,normal
80,1753194180,18,1753194198,1753194204,6,python3 .tests/mnist/train --epochs 115 --learning_rate 0.04312895736005157438 --batch_size 1016 --hidden_size 7529 --dropout 0.18008241988718509674 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.73951292503625154495,,1,,n1720,18579879,80_0,FAILED,SOBOL,115,0.043128957360051574376758054541,1016,7529,0.18008241988718509674072265625,1,0.739512925036251544952392578125,leaky_relu,normal
81,1753194280,9,1753194289,1753194295,6,python3 .tests/mnist/train --epochs 54 --learning_rate 0.07954610445285216491 --batch_size 3316 --hidden_size 3791 --dropout 0.49285913817584514618 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.03207467962056398392,,1,,n1720,18579893,81_0,FAILED,SOBOL,54,0.079546104452852164912179944167,3316,3791,0.49285913817584514617919921875,4,0.032074679620563983917236328125,leaky_relu,normal
82,1753194411,28,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 83 --learning_rate 0.02413916819207370321 --batch_size 2002 --hidden_size 5509 --dropout 0.28141274815425276756 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.94797138497233390808,,1,,n1720,18579901,82_0,FAILED,SOBOL,83,0.024139168192073703206323997961,2002,5509,0.281412748154252767562866210938,3,0.9479713849723339080810546875,leaky_relu,normal
83,1753194420,19,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.05953196121519432199 --batch_size 2258 --hidden_size 1587 --dropout 0.09471606602892279625 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.28041001781821250916,,1,,n1720,18579904,83_0,FAILED,SOBOL,168,0.059531961215194321990207271256,2258,1587,0.094716066028922796249389648438,2,0.2804100178182125091552734375,leaky_relu,normal
84,1753194420,19,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 177 --learning_rate 0.0029735703218728305 --batch_size 3849 --hidden_size 636 --dropout 0.02533716242760419846 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82797744497656822205,,1,,n1720,18579903,84_0,FAILED,SOBOL,177,0.002973570321872830504728035805,3849,636,0.025337162427604198455810546875,1,0.8279774449765682220458984375,leaky_relu,normal
85,1753194424,15,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 74 --learning_rate 0.06353041587015614833 --batch_size 15 --hidden_size 4572 --dropout 0.33706060703843832016 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.40064857527613639832,,1,,n1720,18579905,85_0,FAILED,SOBOL,74,0.06353041587015614832800736167,15,4572,0.337060607038438320159912109375,4,0.4006485752761363983154296875,leaky_relu,normal
86,1753194427,12,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 21 --learning_rate 0.03308185798358172225 --batch_size 2878 --hidden_size 2713 --dropout 0.37669687392190098763 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.60950737167149782181,,1,,n1720,18579906,86_0,FAILED,SOBOL,21,0.033081857983581722248977996514,2878,2713,0.376696873921900987625122070312,3,0.609507371671497821807861328125,leaky_relu,normal
87,1753194431,8,1753194439,1753194445,6,python3 .tests/mnist/train --epochs 148 --learning_rate 0.09427284704456107001 --batch_size 1090 --hidden_size 6464 --dropout 0.1888857637532055378 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.16183656919747591019,,1,,n1720,18579913,87_0,FAILED,SOBOL,148,0.094272847044561070006807312893,1090,6464,0.188885763753205537796020507812,2,0.161836569197475910186767578125,leaky_relu,normal
88,1753194437,32,1753194469,1753194475,6,python3 .tests/mnist/train --epochs 136 --learning_rate 0.01717896947804838439 --batch_size 2700 --hidden_size 4895 --dropout 0.45279200002551078796 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78321972489356994629,,1,,n1720,18579917,88_0,FAILED,SOBOL,136,0.017178969478048384394996972446,2700,4895,0.4527920000255107879638671875,2,0.7832197248935699462890625,leaky_relu,normal
89,1753194436,38,1753194474,1753194480,6,python3 .tests/mnist/train --epochs 33 --learning_rate 0.05554123197095468811 --batch_size 1422 --hidden_size 185 --dropout 0.14013341814279556274 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.4918158799409866333,,1,,n1720,18579916,89_0,FAILED,SOBOL,33,0.055541231970954688113017994056,1422,185,0.140133418142795562744140625,3,0.49181587994098663330078125,leaky_relu,normal
90,1753194438,36,1753194474,1753194480,6,python3 .tests/mnist/train --epochs 62 --learning_rate 0.04697333680465817785 --batch_size 3766 --hidden_size 7164 --dropout 0.08583682356402277946 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.52929581049829721451,,1,,n1720,18579918,90_0,FAILED,SOBOL,62,0.046973336804658177845439581688,3766,7164,0.085836823564022779464721679688,4,0.529295810498297214508056640625,leaky_relu,normal
91,1753194438,31,1753194469,1753194475,6,python3 .tests/mnist/train --epochs 189 --learning_rate 0.08665265296651050719 --batch_size 444 --hidden_size 2141 --dropout 0.27265188051387667656 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.19569956604391336441,,1,,n1720,18579920,91_0,FAILED,SOBOL,189,0.086652652966510507193120815828,444,2141,0.272651880513876676559448242188,1,0.195699566043913364410400390625,leaky_relu,normal
92,1753194439,30,1753194469,1753194475,6,python3 .tests/mnist/train --epochs 156 --learning_rate 0.02618877211213111941 --batch_size 1666 --hidden_size 3091 --dropout 0.35766146052628755569 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.64904754702001810074,,1,,n1720,18579921,92_0,FAILED,SOBOL,156,0.026188772112131119412792301659,1666,3091,0.357661460526287555694580078125,2,0.649047547020018100738525390625,leaky_relu,normal
93,1753194438,33,1753194471,1753194477,6,python3 .tests/mnist/train --epochs 95 --learning_rate 0.09026378351030871217 --batch_size 2433 --hidden_size 8100 --dropout 0.04581201169639825821 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07521493081003427505,,1,,n1720,18579919,93_0,FAILED,SOBOL,95,0.090263783510308712165759459367,2433,8100,0.045812011696398258209228515625,3,0.075214930810034275054931640625,leaky_relu,normal
94,1753194539,20,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 42 --learning_rate 0.00673872546274215025 --batch_size 584 --hidden_size 1263 --dropout 0.24067642027512192726 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.91346754133701324463,,1,,n1720,18579977,94_0,FAILED,SOBOL,42,0.00673872546274215025036147253,584,1263,0.240676420275121927261352539062,4,0.91346754133701324462890625,leaky_relu,normal
95,1753194546,13,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 127 --learning_rate 0.07066741013498976931 --batch_size 3395 --hidden_size 5960 --dropout 0.42836176464334130287 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.36230000853538513184,,1,,n1720,18579978,95_0,FAILED,SOBOL,127,0.070667410134989769310287499593,3395,5960,0.428361764643341302871704101562,1,0.3623000085353851318359375,leaky_relu,normal
96,1753194552,7,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 124 --learning_rate 0.03017551072221249381 --batch_size 2145 --hidden_size 6641 --dropout 0.01051074592396616936 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96265801507979631424,,1,,n1720,18579979,96_0,FAILED,SOBOL,124,0.030175510722212493808225275416,2145,6641,0.010510745923966169357299804688,1,0.962658015079796314239501953125,leaky_relu,normal
97,1753194554,5,1753194559,1753194565,6,python3 .tests/mnist/train --epochs 44 --learning_rate 0.09093353886464611291 --batch_size 1889 --hidden_size 2633 --dropout 0.32234481675550341606 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.26206128019839525223,,1,,n1720,18579980,97_0,FAILED,SOBOL,44,0.090933538864646112909184694217,1889,2633,0.322344816755503416061401367188,4,0.262061280198395252227783203125,leaky_relu,normal
98,1753194638,11,1753194649,1753194655,6,python3 .tests/mnist/train --epochs 99 --learning_rate 0.01211761482991278137 --batch_size 3171 --hidden_size 4364 --dropout 0.39312164857983589172 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.72482644394040107727,,1,,n1720,18580025,98_0,FAILED,SOBOL,99,0.012117614829912781368448371211,3171,4364,0.3931216485798358917236328125,3,0.7248264439404010772705078125,leaky_relu,normal
99,1753194639,10,1753194649,1753194655,6,python3 .tests/mnist/train --epochs 154 --learning_rate 0.07311952680340037813 --batch_size 871 --hidden_size 685 --dropout 0.20542116463184356689 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.05042326822876930237,,1,,n1720,18580026,99_0,FAILED,SOBOL,154,0.073119526803400378134334403057,871,685,0.20542116463184356689453125,2,0.0504232682287693023681640625,leaky_relu,normal
100,1753197683,30,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 193 --learning_rate 0.01416778107844293179 --batch_size 1199 --hidden_size 1794 --dropout 0.16731713199988007545 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.59701806679368019104,,1,,n1720,18580659,100_0,FAILED,SOBOL,193,0.014167781078442931788630154699,1199,1794,0.167317131999880075454711914062,1,0.5970180667936801910400390625,leaky_relu,normal
101,1753197686,27,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 60 --learning_rate 0.05077400377010927307 --batch_size 2988 --hidden_size 5460 --dropout 0.47999085346236824989 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.17847626283764839172,,1,,n1720,18580662,101_0,FAILED,SOBOL,60,0.050774003770109273070421096463,2988,5460,0.479990853462368249893188476562,4,0.1784762628376483917236328125,leaky_relu,normal
102,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 29 --learning_rate 0.04686264722701162511 --batch_size 157 --hidden_size 3615 --dropout 0.29989626724272966385 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.8404668392613530159,,1,,n1720,18580656,102_0,FAILED,SOBOL,29,0.046862647227011625106207759472,157,3615,0.299896267242729663848876953125,3,0.840466839261353015899658203125,leaky_relu,normal
103,1753197690,53,1753197743,1753197749,6,python3 .tests/mnist/train --epochs 138 --learning_rate 0.08205425914460794112 --batch_size 3990 --hidden_size 7608 --dropout 0.11309658829122781754 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38400879222899675369,,1,,n1720,18580668,103_0,FAILED,SOBOL,138,0.082054259144607941123261696248,3990,7608,0.113096588291227817535400390625,2,0.384008792228996753692626953125,leaky_relu,normal
104,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 150 --learning_rate 0.00345010499823838459 --batch_size 301 --hidden_size 6040 --dropout 0.37211761390790343285 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.51418208330869674683,,1,,n1720,18580654,104_0,FAILED,SOBOL,150,0.003450104998238384592518235294,301,6040,0.372117613907903432846069335938,2,0.514182083308696746826171875,leaky_relu,normal
105,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 17 --learning_rate 0.06771418604077772407 --batch_size 3624 --hidden_size 1087 --dropout 0.06040930887684226036 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21398711949586868286,,1,,n1720,18580653,105_0,FAILED,SOBOL,17,0.067714186040777724073791432602,3624,1087,0.060409308876842260360717773438,3,0.213987119495868682861328125,leaky_relu,normal
106,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 72 --learning_rate 0.03572720128446817828 --batch_size 1312 --hidden_size 8052 --dropout 0.22388185746967792511 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.79833360109478235245,,1,,n1720,18580664,106_0,FAILED,SOBOL,72,0.035727201284468178277275995924,1312,8052,0.22388185746967792510986328125,4,0.798333601094782352447509765625,leaky_relu,normal
107,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 181 --learning_rate 0.09945469889668748231 --batch_size 2589 --hidden_size 3299 --dropout 0.41170834563672542572 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.47352817747741937637,,1,,n1720,18580665,107_0,FAILED,SOBOL,181,0.09945469889668748231237316304,2589,3299,0.41170834563672542572021484375,1,0.473528177477419376373291015625,leaky_relu,normal
108,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 165 --learning_rate 0.03816469164416194659 --batch_size 3541 --hidden_size 2190 --dropout 0.46543164225295186043 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92589590046554803848,,1,,n1720,18580655,108_0,FAILED,SOBOL,165,0.038164691644161946593172274333,3541,2190,0.465431642252951860427856445312,2,0.925895900465548038482666015625,leaky_relu,normal
109,1753197690,23,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 87 --learning_rate 0.07672814268572256124 --batch_size 730 --hidden_size 6956 --dropout 0.15263954596593976021 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.34523297939449548721,,1,,n1720,18580663,109_0,FAILED,SOBOL,87,0.076728142685722561244787698342,730,6956,0.152639545965939760208129882812,3,0.345232979394495487213134765625,leaky_relu,normal
110,1753197681,32,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 56 --learning_rate 0.01973780593071132808 --batch_size 2547 --hidden_size 105 --dropout 0.067227180115878582 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63661927729845046997,,1,,n1720,18580652,110_0,FAILED,SOBOL,56,0.019737805930711328078475119696,2547,105,0.067227180115878582000732421875,4,0.636619277298450469970703125,leaky_relu,normal
111,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 112 --learning_rate 0.05922805095957592303 --batch_size 1780 --hidden_size 5072 --dropout 0.2539087226614356041 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.09228187054395675659,,1,,n1720,18580669,111_0,FAILED,SOBOL,112,0.059228050959575923029021282673,1780,5072,0.253908722661435604095458984375,1,0.092281870543956756591796875,leaky_relu,normal
112,1753197690,53,1753197743,1753197749,6,python3 .tests/mnist/train --epochs 106 --learning_rate 0.02340971753941848907 --batch_size 3823 --hidden_size 3857 --dropout 0.19880044041201472282 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.29719346947968006134,,1,,n1720,18580666,112_0,FAILED,SOBOL,106,0.023409717539418489068436812772,3823,3857,0.198800440412014722824096679688,3,0.29719346947968006134033203125,leaky_relu,normal
113,1753197690,52,1753197742,1753197748,6,python3 .tests/mnist/train --epochs 50 --learning_rate 0.06192438612077385413 --batch_size 500 --hidden_size 7331 --dropout 0.38600829197093844414 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.97440223582088947296,,1,,n1720,18580667,113_0,FAILED,SOBOL,50,0.061924386120773854125243218505,500,7331,0.386008291970938444137573242188,2,0.97440223582088947296142578125,leaky_relu,normal
114,1753197681,32,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 93 --learning_rate 0.04083409179253504051 --batch_size 2772 --hidden_size 2032 --dropout 0.3319071643054485321 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.0152916712686419487,,1,,n1720,18580651,114_0,FAILED,SOBOL,93,0.040834091792535040510436772365,2772,2032,0.3319071643054485321044921875,1,0.015291671268641948699951171875,leaky_relu,normal
115,1753197682,31,1753197713,1753197719,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.08037311295494438401 --batch_size 1495 --hidden_size 5195 --dropout 0.01858875900506973267 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71308257710188627243,,1,,n1720,18580657,115_0,FAILED,SOBOL,171,0.080373112954944384012101465942,1495,5195,0.018588759005069732666015625,4,0.713082577101886272430419921875,leaky_relu,normal
116,1753197987,26,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 187 --learning_rate 0.03235107389418408891 --batch_size 543 --hidden_size 4130 --dropout 0.10353155666962265968 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.13553162943571805954,,1,,n1720,18580737,116_0,FAILED,SOBOL,187,0.032351073894184088908243523974,543,4130,0.103531556669622659683227539062,3,0.135531629435718059539794921875,leaky_relu,normal
117,1753197991,22,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 78 --learning_rate 0.09666393702477217575 --batch_size 3354 --hidden_size 954 --dropout 0.29182331869378685951 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.59308628272265195847,,1,,n1720,18580739,117_0,FAILED,SOBOL,78,0.096663937024772175754527836489,3354,954,0.291823318693786859512329101562,2,0.593086282722651958465576171875,leaky_relu,normal
118,1753197992,21,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 11 --learning_rate 0.00068003819109871985 --batch_size 1577 --hidden_size 6394 --dropout 0.48660663235932588577 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.42695306427776813507,,1,,n1720,18580740,118_0,FAILED,SOBOL,11,0.000680038191098719852802079178,1577,6394,0.486606632359325885772705078125,1,0.42695306427776813507080078125,leaky_relu,normal
119,1753197993,20,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 144 --learning_rate 0.06435875929761677994 --batch_size 2344 --hidden_size 2906 --dropout 0.17443305347114801407 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.84439802356064319611,,1,,n1720,18580741,119_0,FAILED,SOBOL,144,0.064358759297616779937456499283,2344,2906,0.174433053471148014068603515625,4,0.84439802356064319610595703125,leaky_relu,normal
120,1753197990,23,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 132 --learning_rate 0.04936128410929814525 --batch_size 1947 --hidden_size 382 --dropout 0.43395003443583846092 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.22566900309175252914,,1,,n1720,18580738,120_0,FAILED,SOBOL,132,0.049361284109298145250654954452,1947,382,0.433950034435838460922241210938,4,0.225669003091752529144287109375,leaky_relu,normal
121,1753197996,17,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 23 --learning_rate 0.08591872434075922826 --batch_size 2203 --hidden_size 4830 --dropout 0.24662380805239081383 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.54937376733869314194,,1,,n1720,18580742,121_0,FAILED,SOBOL,23,0.085918724340759228264019498056,2203,4830,0.246623808052390813827514648438,1,0.549373767338693141937255859375,leaky_relu,normal
122,1753197999,14,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 66 --learning_rate 0.01801045595323666829 --batch_size 945 --hidden_size 2455 --dropout 0.03521839715540409088 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.46184594742953777313,,1,,n1720,18580743,122_0,FAILED,SOBOL,66,0.018010455953236668286132626804,945,2455,0.03521839715540409088134765625,2,0.46184594742953777313232421875,leaky_relu,normal
123,1753198002,11,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 199 --learning_rate 0.05325084400437772592 --batch_size 3245 --hidden_size 6718 --dropout 0.3484186660498380661 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.76314133219420909882,,1,,n1720,18580744,123_0,FAILED,SOBOL,199,0.053250844004377725915411190272,3245,6718,0.34841866604983806610107421875,3,0.76314133219420909881591796875,leaky_relu,normal
124,1753198002,11,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 160 --learning_rate 0.0091280054598115376 --batch_size 2917 --hidden_size 7783 --dropout 0.27909516217187047005 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.34136378578841686249,,1,,n1720,18580746,124_0,FAILED,SOBOL,160,0.009128005459811537602998754437,2917,7783,0.279095162171870470046997070312,4,0.34136378578841686248779296875,leaky_relu,normal
125,1753198003,10,1753198013,1753198019,6,python3 .tests/mnist/train --epochs 104 --learning_rate 0.06993481569029391665 --batch_size 1128 --hidden_size 3533 --dropout 0.09092916594818234444 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.88289154879748821259,,1,,n1720,18580747,125_0,FAILED,SOBOL,104,0.069934815690293916645714489277,1128,3533,0.090929165948182344436645507812,1,0.88289154879748821258544921875,leaky_relu,normal
126,1753198003,40,1753198043,1753198049,6,python3 .tests/mnist/train --epochs 38 --learning_rate 0.02701892589488998075 --batch_size 3935 --hidden_size 5766 --dropout 0.13039469998329877853 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.09615167137235403061,,1,,n1720,18580748,126_0,FAILED,SOBOL,38,0.027018925894889980754420832909,3935,5766,0.130394699983298778533935546875,2,0.096151671372354030609130859375,leaky_relu,normal
127,1753198097,37,1753198134,1753198140,6,python3 .tests/mnist/train --epochs 118 --learning_rate 0.0879720613626763237 --batch_size 102 --hidden_size 1333 --dropout 0.44269428309053182602 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.6796239977702498436,,1,,n1720,18580762,127_0,FAILED,SOBOL,118,0.087972061362676323703624348127,102,1333,0.442694283090531826019287109375,3,0.679623997770249843597412109375,leaky_relu,normal
128,1753198136,32,1753198168,1753198174,6,python3 .tests/mnist/train --epochs 118 --learning_rate 0.021333446187060328 --batch_size 2851 --hidden_size 5134 --dropout 0.15841000806540250778 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45364432875066995621,,1,,n1720,18580770,128_0,FAILED,SOBOL,118,0.021333446187060327997597752869,2851,5134,0.158410008065402507781982421875,1,0.453644328750669956207275390625,leaky_relu,normal
129,1753198153,10,1753198163,1753198169,6,python3 .tests/mnist/train --epochs 39 --learning_rate 0.05775597819834948216 --batch_size 1062 --hidden_size 1965 --dropout 0.47156402375549077988 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75495500210672616959,,1,,n1720,18580789,129_0,FAILED,SOBOL,39,0.05775597819834948215556025275,1062,1965,0.471564023755490779876708984375,4,0.754955002106726169586181640625,leaky_relu,normal
130,1753198160,38,1753198198,1753198204,6,python3 .tests/mnist/train --epochs 104 --learning_rate 0.03978310229601338815 --batch_size 3869 --hidden_size 7405 --dropout 0.30711014242842793465 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.2338400036096572876,,1,,n1720,18580791,130_0,FAILED,SOBOL,104,0.039783102296013388154971579524,3869,7405,0.307110142428427934646606445312,3,0.23384000360965728759765625,leaky_relu,normal
131,1753198159,34,1753198193,1753198199,6,python3 .tests/mnist/train --epochs 159 --learning_rate 0.07518128172624856387 --batch_size 36 --hidden_size 3909 --dropout 0.11979869799688458443 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.55752965807914733887,,1,,n1720,18580790,131_0,FAILED,SOBOL,159,0.075181281726248563868075791561,36,3909,0.119798697996884584426879882812,2,0.5575296580791473388671875,leaky_relu,normal
132,1753198322,21,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 198 --learning_rate 0.03735490096257999826 --batch_size 2010 --hidden_size 2846 --dropout 0.00354100950062274933 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10359027981758117676,,1,,n1720,18580888,132_0,FAILED,SOBOL,198,0.037354900962579998258128455291,2010,2846,0.00354100950062274932861328125,1,0.1035902798175811767578125,leaky_relu,normal
133,1753198320,28,1753198348,1753198354,6,python3 .tests/mnist/train --epochs 65 --learning_rate 0.09790483686719089751 --batch_size 2265 --hidden_size 6328 --dropout 0.31588684581220149994 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68704743683338165283,,1,,n1720,18580887,133_0,FAILED,SOBOL,65,0.097904836867190897509161118251,2265,6328,0.31588684581220149993896484375,4,0.68704743683338165283203125,leaky_relu,normal
134,1753198333,10,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 24 --learning_rate 0.00504874632460996543 --batch_size 1007 --hidden_size 1029 --dropout 0.40227291500195860863 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.33389449957758188248,,1,,n1720,18580890,134_0,FAILED,SOBOL,24,0.005048746324609965432927971563,1007,1029,0.402272915001958608627319335938,3,0.333894499577581882476806640625,leaky_relu,normal
135,1753198334,9,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 133 --learning_rate 0.06623282425329089784 --batch_size 3308 --hidden_size 4184 --dropout 0.21409213682636618614 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.87543772999197244644,,1,,n1720,18580892,135_0,FAILED,SOBOL,133,0.066232824253290897842383344596,3308,4184,0.214092136826366186141967773438,2,0.875437729991972446441650390625,leaky_relu,normal
136,1753198331,12,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 145 --learning_rate 0.04534093790641054861 --batch_size 609 --hidden_size 6772 --dropout 0.45895781833678483963 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.00762405619025230408,,1,,n1720,18580889,136_0,FAILED,SOBOL,145,0.045340937906410548607905042218,609,6772,0.458957818336784839630126953125,2,0.0076240561902523040771484375,leaky_relu,normal
137,1753198336,7,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 12 --learning_rate 0.08369629671014845729 --batch_size 3420 --hidden_size 2530 --dropout 0.14568566624075174332 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.70539985224604606628,,1,,n1720,18580894,137_0,FAILED,SOBOL,12,0.083696296710148457287381518199,3420,2530,0.145685666240751743316650390625,3,0.7053998522460460662841796875,leaky_relu,normal
138,1753198335,8,1753198343,1753198349,6,python3 .tests/mnist/train --epochs 77 --learning_rate 0.01267208140352740937 --batch_size 1643 --hidden_size 4763 --dropout 0.07588253403082489967 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.30489151645451784134,,1,,n1720,18580893,138_0,FAILED,SOBOL,77,0.012672081403527409373954704108,1643,4763,0.075882534030824899673461914062,4,0.304891516454517841339111328125,leaky_relu,normal
139,1753198337,11,1753198348,1753198354,6,python3 .tests/mnist/train --epochs 186 --learning_rate 0.05234449238758534517 --batch_size 2410 --hidden_size 322 --dropout 0.26307560363784432411 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.98211557138711214066,,1,,n1720,18580896,139_0,FAILED,SOBOL,186,0.052344492387585345172240636202,2410,322,0.263075603637844324111938476562,1,0.982115571387112140655517578125,leaky_relu,normal
140,1753198468,26,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.01061262612873688227 --batch_size 3760 --hidden_size 1386 --dropout 0.36370639875531196594 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43489516247063875198,,1,,n1720,18580966,140_0,FAILED,SOBOL,171,0.010612626128736882269443242421,3760,1386,0.3637063987553119659423828125,2,0.434895162470638751983642578125,leaky_relu,normal
141,1753198467,29,1753198496,1753198502,6,python3 .tests/mnist/train --epochs 92 --learning_rate 0.07469301649089903072 --batch_size 438 --hidden_size 5841 --dropout 0.05148656666278839111 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.85235558915883302689,,1,,n1720,18580965,141_0,FAILED,SOBOL,92,0.074693016490899030723760176897,438,5841,0.05148656666278839111328125,3,0.852355589158833026885986328125,leaky_relu,normal
142,1753198480,14,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 51 --learning_rate 0.02865080033158883335 --batch_size 2710 --hidden_size 3466 --dropout 0.23059982387349009514 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.12761990353465080261,,1,,n1720,18581000,142_0,FAILED,SOBOL,51,0.028650800331588833352869372106,2710,3466,0.230599823873490095138549804688,4,0.1276199035346508026123046875,leaky_relu,normal
143,1753198481,13,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 106 --learning_rate 0.09258486545644700749 --batch_size 1432 --hidden_size 7721 --dropout 0.41890636784955859184 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.58515938743948936462,,1,,n1720,18581001,143_0,FAILED,SOBOL,106,0.092584865456447007492357670344,1432,7721,0.418906367849558591842651367188,1,0.5851593874394893646240234375,leaky_relu,normal
144,1753198487,7,1753198494,1753198500,6,python3 .tests/mnist/train --epochs 112 --learning_rate 0.02536912309788167535 --batch_size 3475 --hidden_size 751 --dropout 0.09707343857735395432 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.80575696192681789398,,1,,n1720,18581002,144_0,FAILED,SOBOL,112,0.025369123097881675354958730395,3475,751,0.097073438577353954315185546875,3,0.80575696192681789398193359375,leaky_relu,normal
145,1753198500,22,1753198522,1753198529,7,python3 .tests/mnist/train --epochs 57 --learning_rate 0.08949829592024907687 --batch_size 664 --hidden_size 4425 --dropout 0.2848536735400557518 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.48096688650548458099,,1,,n1720,18581023,145_0,FAILED,SOBOL,57,0.089498295920249076873531635101,664,4425,0.284853673540055751800537109375,2,0.48096688650548458099365234375,leaky_relu,normal
146,1753198502,20,1753198522,1753198529,7,python3 .tests/mnist/train --epochs 86 --learning_rate 0.00755299160536378709 --batch_size 2481 --hidden_size 2579 --dropout 0.49527775170281529427 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.5067280670627951622,,1,,n1720,18581024,146_0,FAILED,SOBOL,86,0.007552991605363787094851169002,2481,2579,0.495277751702815294265747070312,1,0.506728067062795162200927734375,leaky_relu,normal
147,1753198606,8,1753198614,1753198620,6,python3 .tests/mnist/train --epochs 165 --learning_rate 0.07143828059667721442 --batch_size 1714 --hidden_size 6565 --dropout 0.18358422862365841866 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.2065180530771613121,,1,,n1719,18581073,147_0,FAILED,SOBOL,165,0.071438280596677214417944412617,1714,6565,0.183584228623658418655395507812,4,0.206518053077161312103271484375,leaky_relu,normal
148,1753198655,19,1753198674,1753198680,6,python3 .tests/mnist/train --epochs 180 --learning_rate 0.0164384431688115 --batch_size 364 --hidden_size 7676 --dropout 0.1903734598308801651 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.62843292858451604843,,1,,n1720,18581100,148_0,FAILED,SOBOL,180,0.016438443168811500000314751446,364,7676,0.19037345983088016510009765625,3,0.628432928584516048431396484375,leaky_relu,normal
149,1753198672,31,1753198703,1753198709,6,python3 .tests/mnist/train --epochs 71 --learning_rate 0.05474501988450065915 --batch_size 3686 --hidden_size 3676 --dropout 0.37710125558078289032 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.08408029284328222275,,1,,n1720,18581129,149_0,FAILED,SOBOL,71,0.05474501988450065914637576725,3686,3676,0.37710125558078289031982421875,2,0.084080292843282222747802734375,leaky_relu,normal
150,1753202113,44,1753202157,1753202170,13,python3 .tests/mnist/train --epochs 18 --learning_rate 0.04772077033855021133 --batch_size 1374 --hidden_size 5408 --dropout 0.3386094248853623867 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93405165337026119232,,1,,n1720,18582227,150_0,FAILED,SOBOL,18,0.047720770338550211331352102206,1374,5408,0.338609424885362386703491210938,1,0.93405165337026119232177734375,leaky_relu,normal
151,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 151 --learning_rate 0.08744195782830939401 --batch_size 2652 --hidden_size 1720 --dropout 0.02580254664644598961 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.35340414009988307953,,1,,n1720,18582229,151_0,FAILED,SOBOL,151,0.087441957828309394007426647022,2652,1720,0.025802546646445989608764648438,4,0.35340414009988307952880859375,leaky_relu,normal
152,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 139 --learning_rate 0.0021598750673234462 --batch_size 1265 --hidden_size 3225 --dropout 0.27017227280884981155 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.73278379719704389572,,1,,n1720,18582216,152_0,FAILED,SOBOL,139,0.002159875067323446199557546166,1265,3225,0.270172272808849811553955078125,4,0.732783797197043895721435546875,leaky_relu,normal
153,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 30 --learning_rate 0.06275859343213960329 --batch_size 3054 --hidden_size 8000 --dropout 0.08251804206520318985 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.05836557131260633469,,1,,n1720,18582225,153_0,FAILED,SOBOL,30,0.062758593432139603285335738292,3054,8000,0.082518042065203189849853515625,1,0.058365571312606334686279296875,leaky_relu,normal
154,1753202106,22,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 59 --learning_rate 0.03390246046278626302 --batch_size 223 --hidden_size 1148 --dropout 0.1375928693450987339 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.95473102666437625885,,1,,n1720,18582221,154_0,FAILED,SOBOL,59,0.033902460462786263017953558574,223,1148,0.137592869345098733901977539062,2,0.95473102666437625885009765625,leaky_relu,normal
155,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 192 --learning_rate 0.09503776225792244514 --batch_size 4056 --hidden_size 6107 --dropout 0.44941215822473168373 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25414963997900485992,,1,,n1720,18582215,155_0,FAILED,SOBOL,192,0.095037762257922445141566925031,4056,6107,0.449412158224731683731079101562,3,0.25414963997900485992431640625,leaky_relu,normal
156,1753202113,15,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 153 --learning_rate 0.04238247729111463413 --batch_size 2082 --hidden_size 4997 --dropout 0.42699600383639335632 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.83278396166861057281,,1,,n1720,18582224,156_0,FAILED,SOBOL,153,0.042382477291114634132540572864,2082,4997,0.4269960038363933563232421875,4,0.83278396166861057281494140625,leaky_relu,normal
157,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 98 --learning_rate 0.07875622721435503182 --batch_size 1827 --hidden_size 52 --dropout 0.24015007168054580688 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.37634132243692874908,,1,,n1720,18582218,157_0,FAILED,SOBOL,98,0.078756227214355031818193708659,1827,52,0.240150071680545806884765625,1,0.37634132243692874908447265625,leaky_relu,normal
158,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 45 --learning_rate 0.02488026538938284057 --batch_size 3109 --hidden_size 7017 --dropout 0.04438542900606989861 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60473136883229017258,,1,,n1720,18582230,158_0,FAILED,SOBOL,45,0.024880265389382840574006294787,3109,7017,0.044385429006069898605346679688,2,0.604731368832290172576904296875,leaky_relu,normal
159,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 124 --learning_rate 0.0603272213253192649 --batch_size 808 --hidden_size 2256 --dropout 0.35707393242046236992 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.18617433588951826096,,1,,n1720,18582219,159_0,FAILED,SOBOL,124,0.060327221325319264899622595522,808,2256,0.357073932420462369918823242188,3,0.186174335889518260955810546875,leaky_relu,normal
160,1753202113,15,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 127 --learning_rate 0.0389547594267874997 --batch_size 1605 --hidden_size 1639 --dropout 0.20484892511740326881 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.52109432034194469452,,1,,n1720,18582223,160_0,FAILED,SOBOL,127,0.038954759426787499698718875152,1605,1639,0.204848925117403268814086914062,3,0.52109432034194469451904296875,leaky_relu,normal
161,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 41 --learning_rate 0.07747481329878792844 --batch_size 2371 --hidden_size 5583 --dropout 0.39167971769347786903 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.18751312606036663055,,1,,n1720,18582217,161_0,FAILED,SOBOL,41,0.077474813298787928439459449237,2371,5583,0.391679717693477869033813476562,2,0.18751312606036663055419921875,leaky_relu,normal
162,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 96 --learning_rate 0.01894235527645796516 --batch_size 522 --hidden_size 3724 --dropout 0.32183369714766740799 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.79139085765928030014,,1,,n1720,18582226,162_0,FAILED,SOBOL,96,0.01894235527645796515749943012,522,3724,0.321833697147667407989501953125,1,0.791390857659280300140380859375,leaky_relu,normal
163,1753202106,22,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 157 --learning_rate 0.05848676321813837259 --batch_size 3334 --hidden_size 7468 --dropout 0.00912981573492288589 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.49997166451066732407,,1,,n1720,18582220,163_0,FAILED,SOBOL,157,0.058486763218138372588672524444,3334,7468,0.009129815734922885894775390625,4,0.499971664510667324066162109375,leaky_relu,normal
164,1753202113,44,1753202157,1753202164,7,python3 .tests/mnist/train --epochs 190 --learning_rate 0.00422173689212650138 --batch_size 2765 --hidden_size 6518 --dropout 0.10970139829441905022 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.92090628203004598618,,1,,n1720,18582228,164_0,FAILED,SOBOL,190,0.004221736892126501383692982472,2765,6518,0.109701398294419050216674804688,3,0.920906282030045986175537109375,leaky_relu,normal
165,1753202105,23,1753202128,1753202134,6,python3 .tests/mnist/train --epochs 63 --learning_rate 0.0685276907511986888 --batch_size 1487 --hidden_size 2788 --dropout 0.2973710070364177227 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.36972334142774343491,,1,,n1720,18582222,165_0,FAILED,SOBOL,63,0.068527690751198688801082425925,1487,2788,0.297371007036417722702026367188,2,0.369723341427743434906005859375,leaky_relu,normal
166,1753202486,1129,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 32 --learning_rate 0.03496247661523521622 --batch_size 3831 --hidden_size 4506 --dropout 0.47665690258145332336 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.64157838933169841766,,1,,n1720,18582388,166_0,FAILED,SOBOL,32,0.03496247661523521621518284519,3831,4506,0.4766569025814533233642578125,1,0.64157838933169841766357421875,leaky_relu,normal
167,1753202486,1129,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 135 --learning_rate 0.09863428696161136155 --batch_size 509 --hidden_size 576 --dropout 0.16485275328159332275 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.06776100210845470428,,1,,n1720,18582389,167_0,FAILED,SOBOL,135,0.098634286961611361554957966291,509,576,0.16485275328159332275390625,4,0.06776100210845470428466796875,leaky_relu,normal
168,1753202489,1126,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 147 --learning_rate 0.01496380262076854768 --batch_size 3910 --hidden_size 2080 --dropout 0.41215838165953755379 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.94030388724058866501,,1,,n1720,18582391,168_0,FAILED,SOBOL,147,0.014963802620768547682605920102,3910,2080,0.412158381659537553787231445312,4,0.940303887240588665008544921875,leaky_relu,normal
169,1753202487,1128,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 20 --learning_rate 0.05151433953521773745 --batch_size 77 --hidden_size 7097 --dropout 0.22544596390798687935 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.272727171890437603,,1,,n1720,18582390,169_0,FAILED,SOBOL,20,0.051514339535217737453542952153,77,7097,0.225445963907986879348754882812,1,0.272727171890437602996826171875,leaky_relu,normal
170,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 75 --learning_rate 0.0460735329093411583 --batch_size 2940 --hidden_size 260 --dropout 0.06079852115362882614 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.74721108563244342804,,1,,n1720,18582393,170_0,FAILED,SOBOL,75,0.046073532909341158303462293588,2940,260,0.060798521153628826141357421875,2,0.74721108563244342803955078125,leaky_relu,normal
171,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 178 --learning_rate 0.08130701615484431377 --batch_size 1151 --hidden_size 4949 --dropout 0.37362053897231817245 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.03978789038956165314,,1,,n1720,18582394,171_0,FAILED,SOBOL,178,0.081307016154844313771121733225,1151,4949,0.373620538972318172454833984375,3,0.03978789038956165313720703125,leaky_relu,normal
172,1753202485,1129,1753203614,1753203620,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.03094118885640054911 --batch_size 951 --hidden_size 5899 --dropout 0.25742581998929381371 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.61744958348572254181,,1,,n1720,18582386,172_0,FAILED,SOBOL,168,0.030941188856400549112013464992,951,5899,0.257425819989293813705444335938,4,0.61744958348572254180908203125,leaky_relu,normal
173,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 84 --learning_rate 0.09175337842302397351 --batch_size 3251 --hidden_size 1196 --dropout 0.069630445446819067 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.16979400999844074249,,1,,n1720,18582392,173_0,FAILED,SOBOL,84,0.091753378423023973509131678838,3251,1196,0.069630445446819067001342773438,1,0.16979400999844074249267578125,leaky_relu,normal
174,1753202486,1129,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 53 --learning_rate 0.01134655382409691798 --batch_size 1937 --hidden_size 8175 --dropout 0.15609570033848285675 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.82006583642214536667,,1,,n1720,18582387,174_0,FAILED,SOBOL,53,0.011346553824096917983954568854,1937,8175,0.15609570033848285675048828125,2,0.820065836422145366668701171875,leaky_relu,normal
175,1753202491,1124,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 115 --learning_rate 0.07230507011665031347 --batch_size 2193 --hidden_size 3144 --dropout 0.46777384541928768158 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39272155892103910446,,1,,n1720,18582395,175_0,FAILED,SOBOL,115,0.07230507011665031347202869938,2193,3144,0.46777384541928768157958984375,3,0.392721558921039104461669921875,leaky_relu,normal
176,1753202492,1123,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 109 --learning_rate 0.00838152539087459389 --batch_size 150 --hidden_size 4231 --dropout 0.01618542009964585304 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24613103363662958145,,1,,n1720,18582396,176_0,FAILED,SOBOL,109,0.008381525390874593889334320806,150,4231,0.016185420099645853042602539062,1,0.246131033636629581451416015625,leaky_relu,normal
177,1753202495,1120,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 47 --learning_rate 0.06914493845179676967 --batch_size 3983 --hidden_size 821 --dropout 0.32839011261239647865 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.54059995803982019424,,1,,n1720,18582401,177_0,FAILED,SOBOL,47,0.069144938451796769673940445955,3983,821,0.328390112612396478652954101562,4,0.540599958039820194244384765625,leaky_relu,normal
178,1753202493,1122,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 90 --learning_rate 0.02776002309219911812 --batch_size 1208 --hidden_size 6248 --dropout 0.38366613257676362991 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.44135338813066482544,,1,,n1720,18582397,178_0,FAILED,SOBOL,90,0.027760023092199118122103129735,1208,6248,0.383666132576763629913330078125,3,0.441353388130664825439453125,leaky_relu,normal
179,1753202494,1121,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 174 --learning_rate 0.08876732147280126661 --batch_size 2997 --hidden_size 3021 --dropout 0.19534421060234308243 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.77188461273908615112,,1,,n1720,18582399,179_0,FAILED,SOBOL,174,0.088767321472801266613039672393,2997,3021,0.195344210602343082427978515625,2,0.771884612739086151123046875,leaky_relu,normal
180,1753202495,1120,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 184 --learning_rate 0.04854758885474876051 --batch_size 3197 --hidden_size 3990 --dropout 0.17286902246996760368 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31891810148954391479,,1,,n1720,18582400,180_0,FAILED,SOBOL,184,0.048547588854748760511803595818,3197,3990,0.172869022469967603683471679688,1,0.318918101489543914794921875,leaky_relu,normal
181,1753202675,940,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 81 --learning_rate 0.08514690190274268322 --batch_size 897 --hidden_size 7230 --dropout 0.48615655256435275078 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89358795434236526489,,1,,n1720,18582455,181_0,FAILED,SOBOL,81,0.085146901902742683221347874678,897,7230,0.486156552564352750778198242188,4,0.893587954342365264892578125,leaky_relu,normal
182,1753202932,683,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 14 --learning_rate 0.01883105843244120559 --batch_size 2123 --hidden_size 1918 --dropout 0.29032034799456596375 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.11856682691723108292,,1,,n1720,18582507,182_0,FAILED,SOBOL,14,0.01883105843244120558566123691,2123,1918,0.2903203479945659637451171875,3,0.118566826917231082916259765625,leaky_relu,normal
183,1753202920,695,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 141 --learning_rate 0.05401575921773910799 --batch_size 1868 --hidden_size 5342 --dropout 0.10314241796731948853 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.6688970634713768959,,1,,n1720,18582498,183_0,FAILED,SOBOL,141,0.054015759217739107989064706317,1868,5342,0.103142417967319488525390625,2,0.668897063471376895904541015625,leaky_relu,normal
184,1753202921,694,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 129 --learning_rate 0.03161054758494720451 --batch_size 2551 --hidden_size 7929 --dropout 0.35094397189095616341 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29229540005326271057,,1,,n1720,18582499,184_0,FAILED,SOBOL,129,0.031610547584947204513561302974,2551,7929,0.350943971890956163406372070312,2,0.2922954000532627105712890625,leaky_relu,normal
185,1753202934,681,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 26 --learning_rate 0.09586772493831813291 --batch_size 1785 --hidden_size 3418 --dropout 0.03861351357772946358 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99886207655072212219,,1,,n1720,18582510,185_0,FAILED,SOBOL,26,0.095867724938318132910097801869,1785,3418,0.038613513577729463577270507812,3,0.9988620765507221221923828125,leaky_relu,normal
186,1753202925,690,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 69 --learning_rate 0.0014274717249907554 --batch_size 3530 --hidden_size 5666 --dropout 0.24908811133354902267 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.02022026199847459793,,1,,n1720,18582500,186_0,FAILED,SOBOL,69,0.001427471724990755398698727419,3530,5666,0.249088111333549022674560546875,4,0.020220261998474597930908203125,leaky_relu,normal
187,1753202928,687,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 196 --learning_rate 0.06514806415941566675 --batch_size 718 --hidden_size 1466 --dropout 0.43728402908891439438 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.68865325767546892166,,1,,n1720,18582504,187_0,FAILED,SOBOL,196,0.065148064159415666751762330478,718,1466,0.437284029088914394378662109375,1,0.688653257675468921661376953125,leaky_relu,normal
188,1753202930,685,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 162 --learning_rate 0.02259006852516904501 --batch_size 1287 --hidden_size 497 --dropout 0.44413617020472884178 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14241334516555070877,,1,,n1720,18582506,188_0,FAILED,SOBOL,162,0.022590068525169045010603241508,1287,497,0.444136170204728841781616210938,2,0.142413345165550708770751953125,leaky_relu,normal
189,1753202926,689,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 102 --learning_rate 0.06115889853071421883 --batch_size 2565 --hidden_size 4683 --dropout 0.13096701493486762047 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.5667038382962346077,,1,,n1720,18582501,189_0,FAILED,SOBOL,102,0.061158898530714218833015394239,2565,4683,0.130967014934867620468139648438,3,0.566703838296234607696533203125,leaky_relu,normal
190,1753202928,687,1753203615,1753203621,6,python3 .tests/mnist/train --epochs 35 --learning_rate 0.04164835793515667822 --batch_size 325 --hidden_size 2322 --dropout 0.09231016971170902252 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.4201018698513507843,,1,,n1720,18582505,190_0,FAILED,SOBOL,35,0.041648357935156678222288206825,325,2322,0.09231016971170902252197265625,4,0.4201018698513507843017578125,leaky_relu,normal
191,1753202933,682,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 121 --learning_rate 0.08114398341663182912 --batch_size 3647 --hidden_size 6819 --dropout 0.27960623614490032196 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.87081098929047584534,,1,,n1720,18582509,191_0,FAILED,SOBOL,121,0.081143983416631829119758378965,3647,6819,0.27960623614490032196044921875,1,0.8708109892904758453369140625,leaky_relu,normal
192,1753202927,688,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 122 --learning_rate 0.03552222371743992552 --batch_size 419 --hidden_size 3378 --dropout 0.39527085889130830765 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92267550621181726456,,1,,n1720,18582503,192_0,FAILED,SOBOL,122,0.035522223717439925516625720547,419,3378,0.395270858891308307647705078125,2,0.922675506211817264556884765625,leaky_relu,normal
193,1753202932,683,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 34 --learning_rate 0.0996399555185809721 --batch_size 3742 --hidden_size 7809 --dropout 0.20711690280586481094 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.34891924355179071426,,1,,n1720,18582508,193_0,FAILED,SOBOL,34,0.099639955518580972104736304118,3742,7809,0.207116902805864810943603515625,3,0.348919243551790714263916015625,leaky_relu,normal
194,1753202926,689,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 100 --learning_rate 0.00365508275134488912 --batch_size 1446 --hidden_size 1490 --dropout 0.01225586468353867531 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63980954140424728394,,1,,n1720,18582502,194_0,FAILED,SOBOL,100,0.003655082751344889118588765697,1446,1490,0.012255864683538675308227539062,4,0.639809541404247283935546875,leaky_relu,normal
195,1753202934,681,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 165 --learning_rate 0.06752892923280597037 --batch_size 2723 --hidden_size 5737 --dropout 0.32456724951043725014 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.08856565505266189575,,1,,n1720,18582511,195_0,FAILED,SOBOL,165,0.06752892923280597037294370466,2723,5737,0.324567249510437250137329101562,1,0.088565655052661895751953125,leaky_relu,normal
196,1753202934,681,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 197 --learning_rate 0.02033616203693672936 --batch_size 3435 --hidden_size 4675 --dropout 0.30209196731448173523 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.51004946976900100708,,1,,n1720,18582512,196_0,FAILED,SOBOL,197,0.020336162036936729358149733571,3435,4675,0.3020919673144817352294921875,2,0.510049469769001007080078125,leaky_relu,normal
197,1753203010,605,1753203615,1753203622,7,python3 .tests/mnist/train --epochs 67 --learning_rate 0.05865570375472307918 --batch_size 624 --hidden_size 410 --dropout 0.11474630981683731079 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21856939047574996948,,1,,n1720,18582558,197_0,FAILED,SOBOL,67,0.058655703754723079179633771219,624,410,0.114746309816837310791015625,3,0.218569390475749969482421875,leaky_relu,normal
198,1753203226,390,1753203616,1753203628,12,python3 .tests/mnist/train --epochs 25 --learning_rate 0.03756633572401479187 --batch_size 2393 --hidden_size 6875 --dropout 0.1690472322516143322 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.80243507120758295059,,1,,n1720,18582630,198_0,FAILED,SOBOL,25,0.037566335724014791874747487554,2393,6875,0.169047232251614332199096679688,4,0.802435071207582950592041015625,leaky_relu,normal
199,1753203226,390,1753203616,1753203622,6,python3 .tests/mnist/train --epochs 131 --learning_rate 0.07730048970449716894 --batch_size 1626 --hidden_size 2426 --dropout 0.48222783161327242851 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.4689150610938668251,,1,,n1720,18582631,199_0,FAILED,SOBOL,131,0.077300489704497168941266238562,1626,2426,0.482227831613272428512573242188,1,0.468915061093866825103759765625,leaky_relu,normal
200,1753207342,31,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.01229820330673828642 --batch_size 2282 --hidden_size 861 --dropout 0.22173619549721479416 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.60116343572735786438,,1,,n1720,18583239,200_0,FAILED,SOBOL,143,0.012298203306738286419430572494,2282,861,0.221736195497214794158935546875,1,0.6011634357273578643798828125,leaky_relu,normal
201,1753207349,54,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 13 --learning_rate 0.07290988071914762669 --batch_size 2026 --hidden_size 4351 --dropout 0.41000852640718221664 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.17388028278946876526,,1,,n1720,18583251,201_0,FAILED,SOBOL,13,0.072909880719147626693121821972,2026,4351,0.410008526407182216644287109375,4,0.1738802827894687652587890625,leaky_relu,normal
202,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 79 --learning_rate 0.02999492243146523879 --batch_size 3292 --hidden_size 2998 --dropout 0.37037657620385289192 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.83635142166167497635,,1,,n1720,18583242,202_0,FAILED,SOBOL,79,0.029994922431465238787939853182,3292,2998,0.370376576203852891921997070312,3,0.836351421661674976348876953125,leaky_relu,normal
203,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 185 --learning_rate 0.09114318476282060044 --batch_size 992 --hidden_size 6176 --dropout 0.05818332778289914131 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38863490242511034012,,1,,n1720,18583246,203_0,FAILED,SOBOL,185,0.091143184762820600441912688439,992,6176,0.058183327782899141311645507812,2,0.388634902425110340118408203125,leaky_relu,normal
204,1753207348,55,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 176 --learning_rate 0.04628868058314547507 --batch_size 1049 --hidden_size 7237 --dropout 0.06503550149500370026 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96586923021823167801,,1,,n1720,18583250,204_0,FAILED,SOBOL,176,0.046288680583145475067041729744,1049,7237,0.06503550149500370025634765625,1,0.965869230218231678009033203125,leaky_relu,normal
205,1753207349,54,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 88 --learning_rate 0.08265099543966353268 --batch_size 2839 --hidden_size 4077 --dropout 0.25225539319217205048 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.25838514883071184158,,1,,n1720,18583252,205_0,FAILED,SOBOL,88,0.082650995439663532682317281797,2839,4077,0.25225539319217205047607421875,4,0.258385148830711841583251953125,leaky_relu,normal
206,1753207348,55,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 46 --learning_rate 0.01474174790838733359 --batch_size 55 --hidden_size 5285 --dropout 0.46370514994487166405 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.72164607420563697815,,1,,n1720,18583249,206_0,FAILED,SOBOL,46,0.014741747908387333593216439453,55,5285,0.463705149944871664047241210938,3,0.7216460742056369781494140625,leaky_relu,normal
207,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 110 --learning_rate 0.05017726728897542454 --batch_size 3888 --hidden_size 1813 --dropout 0.15039854636415839195 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.05413054302334785461,,1,,n1720,18583245,207_0,FAILED,SOBOL,110,0.050177267288975424541774827958,3888,1813,0.150398546364158391952514648438,2,0.0541305430233478546142578125,leaky_relu,normal
208,1753207346,57,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 116 --learning_rate 0.01743496514242142553 --batch_size 1842 --hidden_size 7121 --dropout 0.33356049377471208572 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.33716441504657268524,,1,,n1720,18583248,208_0,FAILED,SOBOL,116,0.017434965142421425532415213411,1842,7121,0.333560493774712085723876953125,4,0.33716441504657268524169921875,leaky_relu,normal
209,1753207344,29,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.05384605650464073523 --batch_size 2098 --hidden_size 2152 --dropout 0.02078043762594461441 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.88755583576858043671,,1,,n1720,18583247,209_0,FAILED,SOBOL,52,0.053846056504640735229649806115,2098,2152,0.020780437625944614410400390625,1,0.88755583576858043670654296875,leaky_relu,normal
210,1753207344,29,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 82 --learning_rate 0.04993677473403514144 --batch_size 792 --hidden_size 4909 --dropout 0.20104144001379609108 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.10031989868730306625,,1,,n1720,18583243,210_0,FAILED,SOBOL,82,0.04993677473403514144312254075,792,4909,0.201041440013796091079711914062,2,0.100319898687303066253662109375,leaky_relu,normal
211,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.08532351202657446898 --batch_size 3092 --hidden_size 140 --dropout 0.38773478427901864052 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.67492886539548635483,,1,,n1720,18583241,211_0,FAILED,SOBOL,171,0.085323512026574468980477661262,3092,140,0.387734784279018640518188476562,3,0.674928865395486354827880859375,leaky_relu,normal
212,1753207343,35,1753207378,1753207384,6,python3 .tests/mnist/train --epochs 179 --learning_rate 0.02720103816650807846 --batch_size 3035 --hidden_size 1252 --dropout 0.48830645158886909485 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.22251155134290456772,,1,,n1720,18583244,212_0,FAILED,SOBOL,179,0.027201038166508078458560859758,3035,1252,0.4883064515888690948486328125,4,0.222511551342904567718505859375,leaky_relu,normal
213,1753207349,54,1753207403,1753207409,6,python3 .tests/mnist/train --epochs 73 --learning_rate 0.08776393944537268232 --batch_size 1245 --hidden_size 6003 --dropout 0.17657871544361114502 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.55298183020204305649,,1,,n1720,18583253,213_0,FAILED,SOBOL,73,0.087763939445372682324197910475,1245,6003,0.17657871544361114501953125,1,0.552981830202043056488037109375,leaky_relu,normal
214,1753207342,31,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 19 --learning_rate 0.00894589300211518987 --batch_size 4069 --hidden_size 3137 --dropout 0.10575753776356577873 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.4649732690304517746,,1,,n1720,18583238,214_0,FAILED,SOBOL,19,0.008945893002115189868161948539,4069,3137,0.105757537763565778732299804688,2,0.46497326903045177459716796875,leaky_relu,normal
215,1753207343,30,1753207373,1753207379,6,python3 .tests/mnist/train --epochs 149 --learning_rate 0.07014293779367580806 --batch_size 235 --hidden_size 8087 --dropout 0.29356435639783740044 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.75950331799685955048,,1,,n1720,18583240,215_0,FAILED,SOBOL,149,0.070142937793675808055837705979,235,8087,0.293564356397837400436401367188,3,0.75950331799685955047607421875,leaky_relu,normal
216,1753207783,12,1753207795,1753207802,7,python3 .tests/mnist/train --epochs 137 --learning_rate 0.04143397243786603457 --batch_size 3673 --hidden_size 5559 --dropout 0.03356867562979459763 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.13869897555559873581,,1,,n1720,18583365,216_0,FAILED,SOBOL,137,0.041433972437866034566056328003,3673,5559,0.033568675629794597625732421875,3,0.138698975555598735809326171875,leaky_relu,normal
217,1753207784,16,1753207800,1753207806,6,python3 .tests/mnist/train --epochs 31 --learning_rate 0.07980229066135362259 --batch_size 350 --hidden_size 1568 --dropout 0.34622296597808599472 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.58946927916258573532,,1,,n1720,18583367,217_0,FAILED,SOBOL,31,0.079802290661353622591711598488,350,1568,0.346222965978085994720458984375,2,0.589469279162585735321044921875,leaky_relu,normal
218,1753207784,16,1753207800,1753207806,6,python3 .tests/mnist/train --epochs 61 --learning_rate 0.02280983670800924151 --batch_size 2670 --hidden_size 7508 --dropout 0.4317130562849342823 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.42381656356155872345,,1,,n1720,18583370,218_0,FAILED,SOBOL,61,0.022809836708009241512673526131,2670,7508,0.431713056284934282302856445312,1,0.42381656356155872344970703125,leaky_relu,normal
219,1753207803,22,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 191 --learning_rate 0.06249520860044285864 --batch_size 1392 --hidden_size 3844 --dropout 0.24489370780065655708 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.84804617054760456085,,1,,n1720,18583374,219_0,FAILED,SOBOL,191,0.0624952086004428586374359611,1392,3844,0.244893707800656557083129882812,4,0.84804617054760456085205078125,leaky_relu,normal
220,1753207804,21,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 159 --learning_rate 0.00047353571280837057 --batch_size 681 --hidden_size 2731 --dropout 0.12869896180927753448 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.30137889273464679718,,1,,n1720,18583375,220_0,FAILED,SOBOL,159,0.000473535712808370568525917488,681,2731,0.12869896180927753448486328125,3,0.30137889273464679718017578125,leaky_relu,normal
221,1753207818,7,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 94 --learning_rate 0.06454249138040468736 --batch_size 3492 --hidden_size 6413 --dropout 0.4405450727790594101 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.969750942662358284,,1,,n1720,18583379,221_0,FAILED,SOBOL,94,0.064542491380404687362215554458,3492,6413,0.44054507277905941009521484375,2,0.96975094266235828399658203125,leaky_relu,normal
222,1753207819,6,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 40 --learning_rate 0.03255757618639618794 --batch_size 1700 --hidden_size 583 --dropout 0.27687272941693663597 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.01113619934767484665,,1,,n1720,18583380,222_0,FAILED,SOBOL,40,0.032557576186396187944982472118,1700,583,0.276872729416936635971069335938,1,0.011136199347674846649169921875,leaky_relu,normal
223,1753207820,5,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 128 --learning_rate 0.09648020512806251836 --batch_size 2466 --hidden_size 4593 --dropout 0.08918404718860983849 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71776400040835142136,,1,,n1720,18583381,223_0,FAILED,SOBOL,128,0.096480205128062518360465560363,2466,4593,0.089184047188609838485717773438,4,0.717764000408351421356201171875,leaky_relu,normal
224,1753207821,34,1753207855,1753207861,6,python3 .tests/mnist/train --epochs 126 --learning_rate 0.00604750691261142503 --batch_size 3205 --hidden_size 8007 --dropout 0.475785065907984972 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11499126814305782318,,1,,n1720,18583383,224_0,FAILED,SOBOL,126,0.006047506912611425033965417697,3205,8007,0.475785065907984972000122070312,4,0.11499126814305782318115234375,leaky_relu,normal
225,1753207817,8,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 44 --learning_rate 0.06679947932446375636 --batch_size 905 --hidden_size 3312 --dropout 0.16395433293655514717 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.65659538470208644867,,1,,n1720,18583378,225_0,FAILED,SOBOL,44,0.066799479324463756357843635669,905,3312,0.163954332936555147171020507812,1,0.65659538470208644866943359375,leaky_relu,normal
226,1753207816,9,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 96 --learning_rate 0.0363492329638451378 --batch_size 2243 --hidden_size 6050 --dropout 0.12448543589562177658 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.32249319460242986679,,1,,n1720,18583377,226_0,FAILED,SOBOL,96,0.036349232963845137800440454612,2243,6050,0.124485435895621776580810546875,2,0.322493194602429866790771484375,leaky_relu,normal
227,1753207821,34,1753207855,1753207861,6,python3 .tests/mnist/train --epochs 154 --learning_rate 0.09734508920675144505 --batch_size 1988 --hidden_size 1044 --dropout 0.31218925770372152328 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90588916745036840439,,1,,n1720,18583382,227_0,FAILED,SOBOL,154,0.097345089206751445054521809652,1988,1044,0.312189257703721523284912109375,3,0.905889167450368404388427734375,leaky_relu,normal
228,1753207815,10,1753207825,1753207831,6,python3 .tests/mnist/train --epochs 193 --learning_rate 0.03995742644853890468 --batch_size 126 --hidden_size 92 --dropout 0.31897845631465315819 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.45249922480434179306,,1,,n1720,18583376,228_0,FAILED,SOBOL,193,0.039957426448538904684149031254,126,92,0.318978456314653158187866210938,4,0.452499224804341793060302734375,leaky_relu,normal
229,1753207999,7,1753208006,1753208012,6,python3 .tests/mnist/train --epochs 58 --learning_rate 0.07656970487078652854 --batch_size 3960 --hidden_size 5117 --dropout 0.00630902638658881187 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77612775471061468124,,1,,n1720,18583406,229_0,FAILED,SOBOL,58,0.076569704870786528538850745917,3960,5117,0.006309026386588811874389648438,1,0.776127754710614681243896484375,leaky_relu,normal
230,1753208053,13,1753208066,1753208072,6,python3 .tests/mnist/train --epochs 28 --learning_rate 0.02116450472008436778 --batch_size 1104 --hidden_size 2232 --dropout 0.21771011687815189362 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.23498568497598171234,,1,,n1720,18583408,230_0,FAILED,SOBOL,28,0.021164504720084367783705658894,1104,2232,0.21771011687815189361572265625,2,0.23498568497598171234130859375,leaky_relu,normal
231,1753208061,35,1753208096,1753208102,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.05636217236826196464 --batch_size 2893 --hidden_size 6945 --dropout 0.40451408736407756805 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.53635730408132076263,,1,,n1720,18583409,231_0,FAILED,SOBOL,140,0.056362172368261964638946892592,2893,6945,0.40451408736407756805419921875,3,0.53635730408132076263427734375,leaky_relu,normal
232,1753208264,13,1753208277,1753208283,6,python3 .tests/mnist/train --epochs 152 --learning_rate 0.02926099455002695304 --batch_size 1534 --hidden_size 4418 --dropout 0.14158250624313950539 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.408718097023665905,,1,,n1720,18583430,232_0,FAILED,SOBOL,152,0.029260994550026953042731747701,1534,4418,0.141582506243139505386352539062,3,0.408718097023665904998779296875,leaky_relu,normal
233,1753208266,11,1753208277,1753208283,6,python3 .tests/mnist/train --epochs 16 --learning_rate 0.09353113132314756772 --batch_size 2813 --hidden_size 664 --dropout 0.453295102808624506 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86631846707314252853,,1,,n1720,18583431,233_0,FAILED,SOBOL,16,0.093531131323147567724340945006,2813,664,0.453295102808624505996704101562,2,0.866318467073142528533935546875,leaky_relu,normal
234,1753208283,23,1753208306,1753208313,7,python3 .tests/mnist/train --epochs 70 --learning_rate 0.01000781459584832236 --batch_size 461 --hidden_size 6622 --dropout 0.25850746501237154007 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15379759110510349274,,1,,n1720,18583432,234_0,FAILED,SOBOL,70,0.010007814595848322364313176536,461,6622,0.258507465012371540069580078125,1,0.15379759110510349273681640625,leaky_relu,normal
235,1753208283,24,1753208307,1753208313,6,python3 .tests/mnist/train --epochs 182 --learning_rate 0.07374136793864891071 --batch_size 3783 --hidden_size 2684 --dropout 0.07068526837974786758 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57119683362543582916,,1,,n1720,18583433,235_0,FAILED,SOBOL,182,0.073741367938648910707044592527,3783,2684,0.070685268379747867584228515625,4,0.57119683362543582916259765625,leaky_relu,normal
236,1753208306,31,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 166 --learning_rate 0.0140091527193784704 --batch_size 2320 --hidden_size 3636 --dropout 0.04826920805498957634 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02354929782450199127,,1,,n1720,18583435,236_0,FAILED,SOBOL,166,0.01400915271937847039751545708,2320,3636,0.048269208054989576339721679688,3,0.02354929782450199127197265625,leaky_relu,normal
237,1753208307,30,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 84 --learning_rate 0.05256654803035781115 --batch_size 1553 --hidden_size 7555 --dropout 0.36106464220210909843 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.7007122281938791275,,1,,n1720,18583437,237_0,FAILED,SOBOL,84,0.052566548030357811149837488074,1553,7555,0.361064642202109098434448242188,2,0.70071222819387912750244140625,leaky_relu,normal
238,1753208304,33,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 56 --learning_rate 0.04399695917982608673 --batch_size 3378 --hidden_size 1743 --dropout 0.41516239568591117859 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.28896588366478681564,,1,,n1720,18583434,238_0,FAILED,SOBOL,56,0.043996959179826086727693734701,3378,1743,0.4151623956859111785888671875,1,0.288965883664786815643310546875,leaky_relu,normal
239,1753208311,26,1753208337,1753208343,6,python3 .tests/mnist/train --epochs 114 --learning_rate 0.08348114847810939043 --batch_size 567 --hidden_size 5479 --dropout 0.22848419100046157837 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.98680262546986341476,,1,,n1720,18583440,239_0,FAILED,SOBOL,114,0.083481148478109390431711744895,567,5479,0.228484191000461578369140625,4,0.986802625469863414764404296875,leaky_relu,normal
240,1753208308,30,1753208338,1753208344,6,python3 .tests/mnist/train --epochs 108 --learning_rate 0.04754415965648368242 --batch_size 2613 --hidden_size 2474 --dropout 0.28749538632109761238 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.6526498282328248024,,1,,n1720,18583438,240_0,FAILED,SOBOL,108,0.047544159656483682419025882382,2613,2474,0.287495386321097612380981445312,2,0.652649828232824802398681640625,leaky_relu,normal
241,1753208307,30,1753208337,1753208343,6,python3 .tests/mnist/train --epochs 50 --learning_rate 0.08605277250725776317 --batch_size 1335 --hidden_size 6667 --dropout 0.10029087262228131294 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07206326071172952652,,1,,n1720,18583436,241_0,FAILED,SOBOL,50,0.086052772507257763168198039239,1335,6667,0.100290872622281312942504882812,3,0.072063260711729526519775390625,leaky_relu,normal
242,1753208310,27,1753208337,1753208344,7,python3 .tests/mnist/train --epochs 90 --learning_rate 0.01660814681230112985 --batch_size 3599 --hidden_size 329 --dropout 0.18569993507117033005 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.90983530879020690918,,1,,n1720,18583439,242_0,FAILED,SOBOL,90,0.016608146812301129852107450802,3599,329,0.185699935071170330047607421875,4,0.9098353087902069091796875,leaky_relu,normal
243,1753208506,12,1753208518,1753208525,7,python3 .tests/mnist/train --epochs 172 --learning_rate 0.05614111224412918211 --batch_size 277 --hidden_size 4850 --dropout 0.49902167823165655136 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.36542154848575592041,,1,,n1720,18583471,243_0,FAILED,SOBOL,172,0.056141112244129182107243991595,277,4850,0.499021678231656551361083984375,1,0.36542154848575592041015625,leaky_relu,normal
244,1753208539,9,1753208548,1753208554,6,python3 .tests/mnist/train --epochs 187 --learning_rate 0.00655499319387599887 --batch_size 1740 --hidden_size 5817 --dropout 0.38276401674374938011 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78788585960865020752,,1,,n1720,18583489,244_0,FAILED,SOBOL,187,0.006554993193875998866437804224,1740,5817,0.382764016743749380111694335938,2,0.78788585960865020751953125,leaky_relu,normal
245,1753208558,20,1753208578,1753208584,6,python3 .tests/mnist/train --epochs 76 --learning_rate 0.07087391205504536829 --batch_size 2507 --hidden_size 1314 --dropout 0.19447654625400900841 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.48761466145515441895,,1,,n1720,18583490,245_0,FAILED,SOBOL,76,0.070873912055045368285632889638,2507,1314,0.194476546254009008407592773438,3,0.4876146614551544189453125,leaky_relu,normal
246,1753208728,31,1753208759,1753208766,7,python3 .tests/mnist/train --epochs 10 --learning_rate 0.02637250456707551996 --batch_size 770 --hidden_size 7762 --dropout 0.03099973686039447784 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.52459883037954568863,,1,,n1720,18583509,246_0,FAILED,SOBOL,10,0.026372504567075519960051011026,770,7762,0.03099973686039447784423828125,4,0.524598830379545688629150390625,leaky_relu,normal
247,1753208771,18,1753208789,1753208795,6,python3 .tests/mnist/train --epochs 146 --learning_rate 0.09005728140417486316 --batch_size 3581 --hidden_size 3586 --dropout 0.34317760728299617767 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.19986964110285043716,,1,,n1720,18583511,247_0,FAILED,SOBOL,146,0.090057281404174863159717290273,3581,3586,0.34317760728299617767333984375,1,0.199869641102850437164306640625,leaky_relu,normal
248,1753208780,9,1753208789,1753208795,6,python3 .tests/mnist/train --epochs 134 --learning_rate 0.02354395625004544745 --batch_size 847 --hidden_size 2022 --dropout 0.07975010061636567116 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82332811877131462097,,1,,n1720,18583517,248_0,FAILED,SOBOL,134,0.023543956250045447453622671219,847,2022,0.079750100616365671157836914062,1,0.8233281187713146209716796875,leaky_relu,normal
249,1753208793,26,1753208819,1753208825,6,python3 .tests/mnist/train --epochs 22 --learning_rate 0.06010745221208781131 --batch_size 3147 --hidden_size 5238 --dropout 0.26708061853423714638 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.40483203157782554626,,1,,n1720,18583518,249_0,FAILED,SOBOL,22,0.060107452212087811305174511745,3147,5238,0.267080618534237146377563476562,4,0.4048320315778255462646484375,leaky_relu,normal
250,1753213312,13,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 64 --learning_rate 0.04372416948815808363 --batch_size 1913 --hidden_size 3902 --dropout 0.44717094022780656815 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.61418682802468538284,,1,,n1720,18584512,250_0,FAILED,SOBOL,64,0.043724169488158083629603112286,1913,3902,0.447170940227806568145751953125,3,0.614186828024685382843017578125,leaky_relu,normal
251,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 199 --learning_rate 0.07897061326988041863 --batch_size 2168 --hidden_size 7318 --dropout 0.13397496286779642105 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.15768306422978639603,,1,,n1720,18584524,251_0,FAILED,SOBOL,199,0.078970613269880418627622020722,2168,7318,0.133974962867796421051025390625,2,0.157683064229786396026611328125,leaky_relu,normal
252,1753213313,13,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 160 --learning_rate 0.03328997971480712748 --batch_size 4030 --hidden_size 6351 --dropout 0.23460567323490977287 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.7358902590349316597,,1,,n1720,18584514,252_0,FAILED,SOBOL,160,0.033289979714807127475495462932,4030,6351,0.234605673234909772872924804688,1,0.735890259034931659698486328125,leaky_relu,normal
253,1753213318,7,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 102 --learning_rate 0.09409073421470821874 --batch_size 196 --hidden_size 2917 --dropout 0.42277500731870532036 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.0352476881816983223,,1,,n1720,18584517,253_0,FAILED,SOBOL,102,0.094090734214708218741129996943,196,2917,0.422775007318705320358276367188,4,0.035247688181698322296142578125,leaky_relu,normal
254,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 38 --learning_rate 0.00276544877672567965 --batch_size 2948 --hidden_size 4143 --dropout 0.35199486091732978821 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.95162519440054893494,,1,,n1720,18584521,254_0,FAILED,SOBOL,38,0.00276544877672567964571603838,2948,4143,0.3519948609173297882080078125,3,0.9516251944005489349365234375,leaky_relu,normal
255,1753213311,14,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 120 --learning_rate 0.06371252851393073569 --batch_size 1159 --hidden_size 909 --dropout 0.0396986156702041626 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.27726785466074943542,,1,,n1720,18584510,255_0,FAILED,SOBOL,120,0.063712528513930735685200090757,1159,909,0.03969861567020416259765625,2,0.2772678546607494354248046875,leaky_relu,normal
256,1753213316,10,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 119 --learning_rate 0.00251812175372615431 --batch_size 914 --hidden_size 6929 --dropout 0.21296145115047693253 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75749707501381635666,,1,,n1720,18584515,256_0,FAILED,SOBOL,119,0.002518121753726154307684304001,914,6929,0.212961451150476932525634765625,4,0.757497075013816356658935546875,leaky_relu,normal
257,1753213311,15,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 37 --learning_rate 0.06405588828902691878 --batch_size 3214 --hidden_size 2216 --dropout 0.40114222932606935501 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45529030542820692062,,1,,n1720,18584511,257_0,FAILED,SOBOL,37,0.064055888289026918780422192867,3214,2216,0.401142229326069355010986328125,1,0.455290305428206920623779296875,leaky_relu,normal
258,1753213318,8,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 103 --learning_rate 0.03362953009596094528 --batch_size 1972 --hidden_size 5101 --dropout 0.31481835851445794106 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.55501822568476200104,,1,,n1720,18584518,258_0,FAILED,SOBOL,103,0.033629530095960945279554010767,1972,5101,0.314818358514457941055297851562,2,0.55501822568476200103759765625,leaky_relu,normal
259,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 161 --learning_rate 0.09385026826895774554 --batch_size 2228 --hidden_size 76 --dropout 0.00247252220287919044 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.23222538270056247711,,1,,n1720,18584520,259_0,FAILED,SOBOL,161,0.093850268268957745543268345045,2228,76,0.002472522202879190444946289062,3,0.23222538270056247711181640625,leaky_relu,normal
260,1753213317,8,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 199 --learning_rate 0.04348446423029527635 --batch_size 3962 --hidden_size 1060 --dropout 0.12062423676252365112 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68477966822683811188,,1,,n1720,18584516,260_0,FAILED,SOBOL,199,0.04348446423029527635462088142,3962,1060,0.120624236762523651123046875,4,0.68477966822683811187744140625,leaky_relu,normal
261,1753213310,15,1753213325,1753213331,6,python3 .tests/mnist/train --epochs 63 --learning_rate 0.07930939998589456308 --batch_size 129 --hidden_size 6066 --dropout 0.30793568119406700134 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10221932269632816315,,1,,n1720,18584509,261_0,FAILED,SOBOL,63,0.079309399985894563078758778829,129,6066,0.3079356811940670013427734375,1,0.10221932269632816314697265625,leaky_relu,normal
262,1753213319,37,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 23 --learning_rate 0.02388807969028130043 --batch_size 2888 --hidden_size 3328 --dropout 0.47244937671348452568 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.87773518543690443039,,1,,n1720,18584519,262_0,FAILED,SOBOL,23,0.023888079690281300432319611105,2888,3328,0.472449376713484525680541992188,2,0.877735185436904430389404296875,leaky_relu,normal
263,1753213312,14,1753213326,1753213332,6,python3 .tests/mnist/train --epochs 135 --learning_rate 0.05985936450120062091 --batch_size 1099 --hidden_size 8023 --dropout 0.15929536102339625359 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.33529585879296064377,,1,,n1720,18584513,263_0,FAILED,SOBOL,135,0.059859364501200620911625094323,1099,8023,0.159295361023396253585815429688,3,0.335295858792960643768310546875,leaky_relu,normal
264,1753213319,37,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 146 --learning_rate 0.02652303517283871939 --batch_size 2809 --hidden_size 5495 --dropout 0.41979079600423574448 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.70402494631707668304,,1,,n1720,18584523,264_0,FAILED,SOBOL,146,0.026523035172838719392141015874,2809,5495,0.419790796004235744476318359375,3,0.70402494631707668304443359375,leaky_relu,normal
265,1753213320,36,1753213356,1753213362,6,python3 .tests/mnist/train --epochs 11 --learning_rate 0.09000583523381501527 --batch_size 1532 --hidden_size 1759 --dropout 0.23148425202816724777 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.00531443022191524506,,1,,n1720,18584522,265_0,FAILED,SOBOL,11,0.090005835233815015272718085271,1532,1759,0.231484252028167247772216796875,2,0.00531443022191524505615234375,leaky_relu,normal
266,1753213831,8,1753213839,1753213845,6,python3 .tests/mnist/train --epochs 75 --learning_rate 0.00650888077048584861 --batch_size 3788 --hidden_size 7571 --dropout 0.05230921553447842598 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.98345960583537817001,,1,,n1720,18584602,266_0,FAILED,SOBOL,75,0.006508880770485848607509460351,3788,7571,0.052309215534478425979614257812,1,0.983459605835378170013427734375,leaky_relu,normal
267,1753213831,8,1753213839,1753213845,6,python3 .tests/mnist/train --epochs 187 --learning_rate 0.07101605723053217023 --batch_size 465 --hidden_size 3652 --dropout 0.36452904762700200081 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.30717003252357244492,,1,,n1720,18584604,267_0,FAILED,SOBOL,187,0.071016057230532170230219435325,465,3652,0.364529047627002000808715820312,4,0.307170032523572444915771484375,leaky_relu,normal
268,1753213831,12,1753213843,1753213849,6,python3 .tests/mnist/train --epochs 173 --learning_rate 0.01675105565292760862 --batch_size 1544 --hidden_size 2668 --dropout 0.26200809888541698456 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.85394424106925725937,,1,,n1720,18584603,268_0,FAILED,SOBOL,173,0.016751055652927608619062738171,1544,2668,0.26200809888541698455810546875,3,0.853944241069257259368896484375,leaky_relu,normal
269,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 91 --learning_rate 0.05609423913285136593 --batch_size 2311 --hidden_size 6606 --dropout 0.07481502927839756012 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43741829600185155869,,1,,n1720,18584610,269_0,FAILED,SOBOL,91,0.056094239132851365925436226689,2311,6606,0.07481502927839756011962890625,2,0.437418296001851558685302734375,leaky_relu,normal
270,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 49 --learning_rate 0.04749347417401150045 --batch_size 582 --hidden_size 648 --dropout 0.14455781271681189537 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.58354081772267818451,,1,,n1720,18584611,270_0,FAILED,SOBOL,49,0.047493474174011500454906098412,582,648,0.144557812716811895370483398438,1,0.58354081772267818450927734375,leaky_relu,normal
271,1753213840,28,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 107 --learning_rate 0.08620253944788128231 --batch_size 3393 --hidden_size 4402 --dropout 0.45782996481284499168 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.12506661377847194672,,1,,n1720,18584609,271_0,FAILED,SOBOL,107,0.086202539447881282308472350451,3393,4402,0.457829964812844991683959960938,4,0.12506661377847194671630859375,leaky_relu,normal
272,1753213831,10,1753213841,1753213847,6,python3 .tests/mnist/train --epochs 113 --learning_rate 0.04404383229110390291 --batch_size 1347 --hidden_size 3570 --dropout 0.0266249561682343483 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.48265519365668296814,,1,,n1720,18584601,272_0,FAILED,SOBOL,113,0.044043832291103902909501499607,1347,3570,0.026624956168234348297119140625,2,0.4826551936566829681396484375,leaky_relu,normal
273,1753213840,28,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 55 --learning_rate 0.08333823963748292207 --batch_size 2624 --hidden_size 7746 --dropout 0.33943183440715074539 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.80825768038630485535,,1,,n1720,18584606,273_0,FAILED,SOBOL,55,0.083338239637482922073097313387,2624,7746,0.339431834407150745391845703125,3,0.8082576803863048553466796875,leaky_relu,normal
274,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 85 --learning_rate 0.01385938577875494952 --batch_size 264 --hidden_size 1298 --dropout 0.37798592308536171913 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.20485990215092897415,,1,,n1720,18584608,274_0,FAILED,SOBOL,85,0.013859385778754949522517669891,264,1298,0.377985923085361719131469726562,4,0.204859902150928974151611328125,leaky_relu,normal
275,1753213841,58,1753213899,1753213905,6,python3 .tests/mnist/train --epochs 167 --learning_rate 0.05261723351282999311 --batch_size 3587 --hidden_size 5801 --dropout 0.19125812733545899391 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.50425726640969514847,,1,,n1720,18584615,275_0,FAILED,SOBOL,167,0.052617233512829993113957272044,3587,5801,0.191258127335458993911743164062,1,0.504257266409695148468017578125,leaky_relu,normal
276,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 181 --learning_rate 0.01005926076620817199 --batch_size 2508 --hidden_size 4866 --dropout 0.18245661258697509766 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.08266675937920808792,,1,,n1720,18584614,276_0,FAILED,SOBOL,181,0.010059260766208171986035857515,2508,4866,0.18245661258697509765625,2,0.082666759379208087921142578125,leaky_relu,normal
277,1753213840,28,1753213868,1753213881,13,python3 .tests/mnist/train --epochs 69 --learning_rate 0.07359083733288571127 --batch_size 1741 --hidden_size 345 --dropout 0.49415013566613197327 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.62620674539357423782,,1,,n1720,18584607,277_0,FAILED,SOBOL,69,0.07359083733288571127495458768,1741,345,0.4941501356661319732666015625,3,0.626206745393574237823486328125,leaky_relu,normal
278,1753213834,34,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 17 --learning_rate 0.0291188493745401511 --batch_size 3574 --hidden_size 6683 --dropout 0.2837859313003718853 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.3548487834632396698,,1,,n1720,18584605,278_0,FAILED,SOBOL,17,0.029118849374540151098145202013,3574,6683,0.283785931300371885299682617188,4,0.3548487834632396697998046875,leaky_relu,normal
279,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 152 --learning_rate 0.09357724374653772492 --batch_size 763 --hidden_size 2490 --dropout 0.09600569633767008781 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93630870804190635681,,1,,n1720,18584612,279_0,FAILED,SOBOL,152,0.093577243746537724922163192787,763,2490,0.096005696337670087814331054688,1,0.9363087080419063568115234375,leaky_relu,normal
280,1753213841,27,1753213868,1753213874,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.02082571800407022333 --batch_size 3146 --hidden_size 925 --dropout 0.35600520577281713486 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.05613546911627054214,,1,,n1720,18584613,280_0,FAILED,SOBOL,140,0.020825718004070223332568900787,3146,925,0.356005205772817134857177734375,1,0.056135469116270542144775390625,leaky_relu,normal
281,1753214059,21,1753214080,1753214086,6,python3 .tests/mnist/train --epochs 29 --learning_rate 0.05660187762612477191 --batch_size 846 --hidden_size 4159 --dropout 0.04331670235842466354 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.73132843617349863052,,1,,n1720,18584642,281_0,FAILED,SOBOL,29,0.056601877626124771913929123457,846,4159,0.043316702358424663543701171875,4,0.731328436173498630523681640625,leaky_relu,normal
282,1753214343,8,1753214351,1753214358,7,python3 .tests/mnist/train --epochs 57 --learning_rate 0.04020551415942609508 --batch_size 2176 --hidden_size 2933 --dropout 0.23901962535455822945 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25634934008121490479,,1,,n1720,18584693,282_0,FAILED,SOBOL,57,0.040205514159426095077698448677,2176,2933,0.239019625354558229446411132812,3,0.25634934008121490478515625,leaky_relu,normal
283,1753214388,23,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 193 --learning_rate 0.07622558143055066515 --batch_size 1920 --hidden_size 6367 --dropout 0.42586555751040577888 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.95615670084953308105,,1,,n1720,18584696,283_0,FAILED,SOBOL,193,0.076225581430550665151812950171,1920,6367,0.425865557510405778884887695312,2,0.9561567008495330810546875,leaky_relu,normal
284,1753214394,17,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 155 --learning_rate 0.03600587318874896164 --batch_size 186 --hidden_size 7302 --dropout 0.45029774866998195648 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.37878468632698059082,,1,,n1720,18584701,284_0,FAILED,SOBOL,155,0.036005873188748961644112256408,186,7302,0.45029774866998195648193359375,1,0.3787846863269805908203125,leaky_relu,normal
285,1753214392,19,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 97 --learning_rate 0.09759241622975096953 --batch_size 4019 --hidden_size 3886 --dropout 0.13847845979034900665 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.83445329964160919189,,1,,n1720,18584699,285_0,FAILED,SOBOL,97,0.097592416229750969525191806042,4019,3886,0.13847845979034900665283203125,4,0.83445329964160919189453125,leaky_relu,normal
286,1753214395,16,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 43 --learning_rate 0.00628797285836189997 --batch_size 1172 --hidden_size 5222 --dropout 0.0833433433435857296 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.18369961623102426529,,1,,n1720,18584703,286_0,FAILED,SOBOL,43,0.006287972858361899966550545571,1172,5222,0.083343343343585729598999023438,3,0.183699616231024265289306640625,leaky_relu,normal
287,1753214395,18,1753214413,1753214419,6,python3 .tests/mnist/train --epochs 125 --learning_rate 0.06645992894330993161 --batch_size 2961 --hidden_size 2006 --dropout 0.2709975740872323513 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60303139034658670425,,1,,n1720,18584704,287_0,FAILED,SOBOL,125,0.066459928943309931614891183926,2961,2006,0.270997574087232351303100585938,2,0.603031390346586704254150390625,leaky_relu,normal
288,1753214389,22,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 128 --learning_rate 0.03279804362077266139 --batch_size 3733 --hidden_size 2410 --dropout 0.16592121170833706856 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.19017333164811134338,,1,,n1720,18584697,288_0,FAILED,SOBOL,128,0.03279804362077266138841835641,3733,2410,0.165921211708337068557739257812,2,0.1901733316481113433837890625,leaky_relu,normal
289,1753214388,23,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 40 --learning_rate 0.09614065623553470774 --batch_size 411 --hidden_size 6860 --dropout 0.47772536100819706917 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.52260594442486763,,1,,n1720,18584695,289_0,FAILED,SOBOL,40,0.096140656235534707740875148829,411,6860,0.477725361008197069168090820312,3,0.5226059444248676300048828125,leaky_relu,normal
290,1753214395,16,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 94 --learning_rate 0.00013017444908618929 --batch_size 2739 --hidden_size 394 --dropout 0.2985017215833067894 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.49734185356646776199,,1,,n1720,18584702,290_0,FAILED,SOBOL,94,0.000130174449086189287713710705,2739,394,0.298501721583306789398193359375,4,0.497341853566467761993408203125,leaky_relu,normal
291,1753214390,21,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 158 --learning_rate 0.06478981691477821159 --batch_size 1461 --hidden_size 4659 --dropout 0.11083211284130811691 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.78990891296416521072,,1,,n1720,18584698,291_0,FAILED,SOBOL,158,0.064789816914778211587311318453,1461,4659,0.110832112841308116912841796875,1,0.789908912964165210723876953125,leaky_relu,normal
292,1753214394,17,1753214411,1753214418,7,python3 .tests/mnist/train --epochs 191 --learning_rate 0.02305792590752243909 --batch_size 621 --hidden_size 5753 --dropout 0.00824443390592932701 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.36733814794570207596,,1,,n1720,18584700,292_0,FAILED,SOBOL,191,0.023057925907522439090691079855,621,5753,0.008244433905929327011108398438,2,0.367338147945702075958251953125,leaky_relu,normal
293,1753214588,35,1753214623,1753214629,6,python3 .tests/mnist/train --epochs 62 --learning_rate 0.06215108664883300937 --batch_size 3432 --hidden_size 1506 --dropout 0.32094831531867384911 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.91966895479708909988,,1,,n1720,18584731,293_0,FAILED,SOBOL,62,0.062151086648833009373760205563,3432,1506,0.320948315318673849105834960938,3,0.919668954797089099884033203125,leaky_relu,normal
294,1753214611,12,1753214623,1753214629,6,python3 .tests/mnist/train --epochs 30 --learning_rate 0.04109518423322588293 --batch_size 1631 --hidden_size 7825 --dropout 0.39085420779883861542 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.07017754390835762024,,1,,n1720,18584733,294_0,FAILED,SOBOL,30,0.041095184233225882930451433594,1631,7825,0.39085420779883861541748046875,4,0.0701775439083576202392578125,leaky_relu,normal
295,1753214610,15,1753214625,1753214631,6,python3 .tests/mnist/train --epochs 137 --learning_rate 0.08004199443059042962 --batch_size 2398 --hidden_size 3394 --dropout 0.2040234152227640152 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.64284634962677955627,,1,,n1720,18584732,295_0,FAILED,SOBOL,137,0.080041994430590429621119596959,2398,3394,0.20402341522276401519775390625,1,0.6428463496267795562744140625,leaky_relu,normal
296,1753214613,10,1753214623,1753214629,6,python3 .tests/mnist/train --epochs 149 --learning_rate 0.00880374633800238247 --batch_size 2029 --hidden_size 1829 --dropout 0.46695116767659783363 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.27146324608474969864,,1,,n1720,18584735,296_0,FAILED,SOBOL,149,0.008803746338002382473830742526,2029,1829,0.466951167676597833633422851562,1,0.271463246084749698638916015625,leaky_relu,normal
297,1753214612,13,1753214625,1753214631,6,python3 .tests/mnist/train --epochs 18 --learning_rate 0.07018904872843996501 --batch_size 2285 --hidden_size 5301 --dropout 0.1552730225957930088 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.93786896858364343643,,1,,n1720,18584734,297_0,FAILED,SOBOL,18,0.070189048728439965008085721365,2285,5301,0.155273022595793008804321289062,4,0.937868968583643436431884765625,leaky_relu,normal
298,1753214821,13,1753214834,1753214840,6,python3 .tests/mnist/train --epochs 74 --learning_rate 0.02725248582549393353 --batch_size 987 --hidden_size 4093 --dropout 0.06874604616314172745 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.04102165251970291138,,1,,n1720,18584768,298_0,FAILED,SOBOL,74,0.027252485825493933530028201062,987,4093,0.068746046163141727447509765625,3,0.041021652519702911376953125,leaky_relu,normal
299,1753214821,13,1753214834,1753214840,6,python3 .tests/mnist/train --epochs 179 --learning_rate 0.08761341032823548314 --batch_size 3287 --hidden_size 7253 --dropout 0.25654142070561647415 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.74961607903242111206,,1,,n1720,18584769,299_0,FAILED,SOBOL,179,0.087613410328235483137682138022,3287,7253,0.256541420705616474151611328125,2,0.749616079032421112060546875,leaky_relu,normal
300,1753219718,25,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 170 --learning_rate 0.04978700630478561512 --batch_size 2847 --hidden_size 6160 --dropout 0.37474836362525820732 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.17127143591642379761,,1,,n1720,18585663,300_0,FAILED,SOBOL,170,0.049787006304785615118380093236,2847,6160,0.374748363625258207321166992188,1,0.171271435916423797607421875,leaky_relu,normal
301,1753219712,31,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 82 --learning_rate 0.0853741960204206507 --batch_size 1059 --hidden_size 2982 --dropout 0.06192634580656886101 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.62009824067354202271,,1,,n1720,18585654,301_0,FAILED,SOBOL,82,0.085374196020420650699023212837,1059,2982,0.061926345806568861007690429688,4,0.620098240673542022705078125,leaky_relu,normal
302,1753219719,54,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.01748183974232524543 --batch_size 3874 --hidden_size 4335 --dropout 0.22651349753141403198 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39121301565319299698,,1,,n1720,18585665,302_0,FAILED,SOBOL,52,0.017481839742325245429244162665,3874,4335,0.226513497531414031982421875,3,0.391213015653192996978759765625,leaky_relu,normal
303,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 116 --learning_rate 0.05370314915264026018 --batch_size 40 --hidden_size 845 --dropout 0.41322591528296470642 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.81738630030304193497,,1,,n1720,18585656,303_0,FAILED,SOBOL,116,0.053703149152640260177715703094,40,845,0.4132259152829647064208984375,2,0.817386300303041934967041015625,leaky_relu,normal
304,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 110 --learning_rate 0.01469106391454115534 --batch_size 2087 --hidden_size 8071 --dropout 0.10225778119638562202 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.5421627415344119072,,1,,n1720,18585666,304_0,FAILED,SOBOL,110,0.014691063914541155344117839832,2087,8071,0.102257781196385622024536132812,4,0.542162741534411907196044921875,leaky_relu,normal
305,1753219714,31,1753219745,1753219751,6,python3 .tests/mnist/train --epochs 46 --learning_rate 0.05032703571822494393 --batch_size 1831 --hidden_size 3121 --dropout 0.28943571122363209724 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24874297808855772018,,1,,n1720,18585659,305_0,FAILED,SOBOL,46,0.050327035718224943927623371565,1831,3121,0.289435711223632097244262695312,1,0.248742978088557720184326171875,leaky_relu,normal
306,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 88 --learning_rate 0.04643158793514595012 --batch_size 3105 --hidden_size 5987 --dropout 0.48533411230891942978 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.77035270817577838898,,1,,n1720,18585668,306_0,FAILED,SOBOL,88,0.046431587935145950118975832765,3105,5987,0.485334112308919429779052734375,2,0.77035270817577838897705078125,leaky_relu,normal
307,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 176 --learning_rate 0.08260412083975970932 --batch_size 805 --hidden_size 1236 --dropout 0.17204658221453428268 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.43877256102859973907,,1,,n1720,18585655,307_0,FAILED,SOBOL,176,0.082604120839759709316041380589,805,1236,0.172046582214534282684326171875,3,0.43877256102859973907470703125,leaky_relu,normal
308,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 185 --learning_rate 0.02994881149670109224 --batch_size 1245 --hidden_size 156 --dropout 0.19641198357567191124 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89229971356689929962,,1,,n1720,18585657,308_0,FAILED,SOBOL,185,0.029948811496701092244032693657,1245,156,0.196411983575671911239624023438,4,0.89229971356689929962158203125,leaky_relu,normal
309,1753219715,28,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 80 --learning_rate 0.09128533142693341651 --batch_size 3033 --hidden_size 4925 --dropout 0.38473390555009245872 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31658093817532062531,,1,,n1720,18585662,309_0,FAILED,SOBOL,80,0.091285331426933416509861274335,3033,4925,0.384733905550092458724975585938,1,0.31658093817532062530517578125,leaky_relu,normal
310,1753219719,24,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 13 --learning_rate 0.0124487324238754804 --batch_size 242 --hidden_size 2168 --dropout 0.32951769791543483734 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.67021522950381040573,,1,,n1720,18585664,310_0,FAILED,SOBOL,13,0.012448732423875480401775917016,242,2168,0.32951769791543483734130859375,2,0.670215229503810405731201171875,leaky_relu,normal
311,1753219714,29,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.07285843306016177856 --batch_size 4076 --hidden_size 7136 --dropout 0.01731300540268421173 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.12093415390700101852,,1,,n1720,18585658,311_0,FAILED,SOBOL,143,0.072858433060161778560548384576,4076,7136,0.01731300540268421173095703125,3,0.120934153907001018524169921875,leaky_relu,normal
312,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 131 --learning_rate 0.03791045767562464114 --batch_size 351 --hidden_size 4609 --dropout 0.28073671320453286171 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99649834446609020233,,1,,n1720,18585667,312_0,FAILED,SOBOL,131,0.037910457675624641138423243092,351,4609,0.280736713204532861709594726562,3,0.99649834446609020233154296875,leaky_relu,normal
313,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 25 --learning_rate 0.07705240050498396442 --batch_size 3673 --hidden_size 599 --dropout 0.09344064677134156227 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29095746390521526337,,1,,n1720,18585669,313_0,FAILED,SOBOL,25,0.077052400504983964424354780931,3673,599,0.093440646771341562271118164062,2,0.29095746390521526336669921875,leaky_relu,normal
314,1753219720,53,1753219773,1753219779,6,python3 .tests/mnist/train --epochs 68 --learning_rate 0.0200964582676999258 --batch_size 1385 --hidden_size 6429 --dropout 0.13203571084886789322 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.6909863566979765892,,1,,n1720,18585670,314_0,FAILED,SOBOL,68,0.020096458267699925798188687054,1385,6429,0.132035710848867893218994140625,1,0.690986356697976589202880859375,leaky_relu,normal
315,1753219715,28,1753219743,1753219749,6,python3 .tests/mnist/train --epochs 197 --learning_rate 0.05899449195936322388 --batch_size 2663 --hidden_size 2747 --dropout 0.44520486611872911453 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.02152684982866048813,,1,,n1720,18585661,315_0,FAILED,SOBOL,197,0.05899449195936322387634476172,2663,2747,0.445204866118729114532470703125,4,0.021526849828660488128662109375,leaky_relu,normal
316,1753220288,29,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 164 --learning_rate 0.00399463164387270798 --batch_size 3503 --hidden_size 3828 --dropout 0.43645875854417681694 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.56928155478090047836,,1,,n1720,18585725,316_0,FAILED,SOBOL,164,0.003994631643872707978115688121,3503,3828,0.436458758544176816940307617188,3,0.569281554780900478363037109375,leaky_relu,normal
317,1753220289,28,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 100 --learning_rate 0.06728846179842949693 --batch_size 692 --hidden_size 7492 --dropout 0.24826284078881144524 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14396455045789480209,,1,,n1720,18585726,317_0,FAILED,SOBOL,100,0.067288461798429496929507820369,692,7492,0.248262840788811445236206054688,2,0.143964550457894802093505859375,leaky_relu,normal
318,1753220290,27,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 34 --learning_rate 0.03527489818306640129 --batch_size 2453 --hidden_size 1552 --dropout 0.03772789239883422852 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.8682035934180021286,,1,,n1720,18585727,318_0,FAILED,SOBOL,34,0.035274898183066401291529956552,2453,1552,0.037727892398834228515625,1,0.86820359341800212860107421875,leaky_relu,normal
319,1753220292,25,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 122 --learning_rate 0.09998331678230315545 --batch_size 1686 --hidden_size 5543 --dropout 0.35005835071206092834 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.41852026991546154022,,1,,n1720,18585728,319_0,FAILED,SOBOL,122,0.099983316782303155445532638623,1686,5543,0.3500583507120609283447265625,4,0.41852026991546154022216796875,leaky_relu,normal
320,1753220293,26,1753220319,1753220325,6,python3 .tests/mnist/train --epochs 120 --learning_rate 0.04170666369413957714 --batch_size 2356 --hidden_size 560 --dropout 0.48134340252727270126 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.35151926707476377487,,1,,n1720,18585732,320_0,FAILED,SOBOL,120,0.041706663694139577136521523926,2356,560,0.481343402527272701263427734375,3,0.351519267074763774871826171875,leaky_relu,normal
321,1753220300,50,1753220350,1753220356,6,python3 .tests/mnist/train --epochs 35 --learning_rate 0.08098964192830027109 --batch_size 1589 --hidden_size 4490 --dropout 0.16816280316561460495 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92424925696104764938,,1,,n1720,18585740,321_0,FAILED,SOBOL,35,0.080989641928300271089824491355,1589,4490,0.168162803165614604949951171875,2,0.924249256961047649383544921875,leaky_relu,normal
322,1753220299,18,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 102 --learning_rate 0.02245173423225060166 --batch_size 3342 --hidden_size 2772 --dropout 0.11392366187646985054 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.08599579520523548126,,1,,n1720,18585734,322_0,FAILED,SOBOL,102,0.022451734232250601663860578583,3342,2772,0.113923661876469850540161132812,1,0.08599579520523548126220703125,leaky_relu,normal
323,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 163 --learning_rate 0.061198151365481325 --batch_size 531 --hidden_size 6502 --dropout 0.30126931937411427498 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63826571591198444366,,1,,n1720,18585738,323_0,FAILED,SOBOL,163,0.061198151365481325003603529922,531,6502,0.301269319374114274978637695312,4,0.63826571591198444366455078125,leaky_relu,normal
324,1753220298,19,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 196 --learning_rate 0.00146596089461818345 --batch_size 1482 --hidden_size 7483 --dropout 0.32563475333154201508 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21624414809048175812,,1,,n1720,18585733,324_0,FAILED,SOBOL,196,0.001465960894618183445875514437,1482,7483,0.32563475333154201507568359375,3,0.21624414809048175811767578125,leaky_relu,normal
325,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 69 --learning_rate 0.06501049055438488933 --batch_size 2760 --hidden_size 3740 --dropout 0.01332336850464344025 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.50875026173889636993,,1,,n1720,18585736,325_0,FAILED,SOBOL,69,0.065010490554384889327899088585,2760,3740,0.01332336850464344024658203125,2,0.50875026173889636993408203125,leaky_relu,normal
326,1753220293,24,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.03145544540872798056 --batch_size 512 --hidden_size 5599 --dropout 0.20824475726112723351 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.47127142082899808884,,1,,n1720,18585731,326_0,FAILED,SOBOL,27,0.031455445408727980560747994332,512,5599,0.208244757261127233505249023438,1,0.471271420828998088836669921875,leaky_relu,normal
327,1753220292,25,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 129 --learning_rate 0.09592679436244071212 --batch_size 3834 --hidden_size 1655 --dropout 0.39639871334657073021 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.80376515816897153854,,1,,n1720,18585730,327_0,FAILED,SOBOL,129,0.095926794362440712116146812605,3834,1655,0.396398713346570730209350585938,4,0.803765158168971538543701171875,leaky_relu,normal
328,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 141 --learning_rate 0.01847931471569463566 --batch_size 81 --hidden_size 3160 --dropout 0.15152923110872507095 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.17255426757037639618,,1,,n1720,18585739,328_0,FAILED,SOBOL,141,0.018479314715694635656850763894,81,3160,0.151529231108725070953369140625,4,0.17255426757037639617919921875,leaky_relu,normal
329,1753220299,18,1753220317,1753220323,6,python3 .tests/mnist/train --epochs 15 --learning_rate 0.05426842147633433727 --batch_size 3915 --hidden_size 8191 --dropout 0.46483583468943834305 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.59878873638808727264,,1,,n1720,18585735,329_0,FAILED,SOBOL,15,0.054268421476334337272273700137,3915,8191,0.464835834689438343048095703125,1,0.59878873638808727264404296875,leaky_relu,normal
330,1753220300,45,1753220345,1753220351,6,python3 .tests/mnist/train --epochs 81 --learning_rate 0.0487827195649035289 --batch_size 1148 --hidden_size 1212 --dropout 0.25332388142123818398 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38993052300065755844,,1,,n1720,18585737,330_0,FAILED,SOBOL,81,0.048782719564903528897126250286,1148,1212,0.253323881421238183975219726562,2,0.389930523000657558441162109375,leaky_relu,normal
331,1753220588,29,1753220617,1753220624,7,python3 .tests/mnist/train --epochs 184 --learning_rate 0.08481573546323925572 --batch_size 2937 --hidden_size 5915 --dropout 0.06610398972406983376 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.83869644161313772202,,1,,n1720,18585795,331_0,FAILED,SOBOL,184,0.084815735463239255720324649701,2937,5915,0.066103989724069833755493164062,3,0.838696441613137722015380859375,leaky_relu,normal
332,1753220905,15,1753220920,1753220926,6,python3 .tests/mnist/train --epochs 175 --learning_rate 0.02742809596480801776 --batch_size 3266 --hidden_size 4933 --dropout 0.0573577880859375 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.25992443319410085678,,1,,n1720,18585848,332_0,FAILED,SOBOL,175,0.027428095964808017759306579819,3266,4933,0.0573577880859375,4,0.259924433194100856781005859375,leaky_relu,normal
333,1753220914,34,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 90 --learning_rate 0.08900321584809571529 --batch_size 965 --hidden_size 244 --dropout 0.36955103650689125061 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96845791395753622055,,1,,n1720,18585852,333_0,FAILED,SOBOL,90,0.089003215848095715290178020496,965,244,0.3695510365068912506103515625,1,0.968457913957536220550537109375,leaky_relu,normal
334,1753220909,11,1753220920,1753220926,6,python3 .tests/mnist/train --epochs 47 --learning_rate 0.00863342398433014635 --batch_size 2183 --hidden_size 7081 --dropout 0.40912317438051104546 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.05255991034209728241,,1,,n1720,18585851,334_0,FAILED,SOBOL,47,0.008633423984330146350174572945,2183,7081,0.409123174380511045455932617188,2,0.05255991034209728240966796875,leaky_relu,normal
335,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 108 --learning_rate 0.06879395542293786914 --batch_size 1928 --hidden_size 2064 --dropout 0.22085084347054362297 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.71902675740420818329,,1,,n1720,18585861,335_0,FAILED,SOBOL,108,0.068793955422937869137456345925,1928,2064,0.220850843470543622970581054688,3,0.71902675740420818328857421875,leaky_relu,normal
336,1753220908,17,1753220925,1753220931,6,python3 .tests/mnist/train --epochs 114 --learning_rate 0.01111065944880247104 --batch_size 3971 --hidden_size 5326 --dropout 0.29463308211416006088 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.88905649259686470032,,1,,n1720,18585850,336_0,FAILED,SOBOL,114,0.011110659448802471041539696728,3971,5326,0.294633082114160060882568359375,1,0.8890564925968647003173828125,leaky_relu,normal
337,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 53 --learning_rate 0.07263699724404142077 --batch_size 137 --hidden_size 1902 --dropout 0.10682626347988843918 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.3398365415632724762,,1,,n1720,18585856,337_0,FAILED,SOBOL,53,0.072636997244041420773719153203,137,1902,0.106826263479888439178466796875,4,0.3398365415632724761962890625,leaky_relu,normal
338,1753220906,14,1753220920,1753220926,6,python3 .tests/mnist/train --epochs 84 --learning_rate 0.03129217188525944965 --batch_size 3008 --hidden_size 7214 --dropout 0.17770916270092129707 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.67345884162932634354,,1,,n1720,18585849,338_0,FAILED,SOBOL,84,0.031292171885259449648497565022,3008,7214,0.177709162700921297073364257812,3,0.673458841629326343536376953125,leaky_relu,normal
339,1753220915,33,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 169 --learning_rate 0.09150147982956842452 --batch_size 1219 --hidden_size 3974 --dropout 0.4894368988461792469 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.09767912048846483231,,1,,n1720,18585853,339_0,FAILED,SOBOL,169,0.091501479829568424517738378654,1219,3974,0.489436898846179246902465820312,2,0.097679120488464832305908203125,leaky_relu,normal
340,1753220916,32,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 178 --learning_rate 0.04582087065074592902 --batch_size 890 --hidden_size 3037 --dropout 0.38684919290244579315 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.55175547022372484207,,1,,n1720,18585860,340_0,FAILED,SOBOL,178,0.045820870650745929020253299768,890,3037,0.38684919290244579315185546875,1,0.551755470223724842071533203125,leaky_relu,normal
341,1753220916,32,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 75 --learning_rate 0.08165875987159089411 --batch_size 3190 --hidden_size 6264 --dropout 0.20015584863722324371 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.22011443693190813065,,1,,n1720,18585855,341_0,FAILED,SOBOL,75,0.081658759871590894108273062102,3190,6264,0.20015584863722324371337890625,4,0.220114436931908130645751953125,leaky_relu,normal
342,1753220916,32,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 21 --learning_rate 0.01529496906027197865 --batch_size 1869 --hidden_size 837 --dropout 0.01995513727888464928 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.76075935736298561096,,1,,n1720,18585854,342_0,FAILED,SOBOL,21,0.015294969060271978653076097032,1869,837,0.019955137278884649276733398438,3,0.7607593573629856109619140625,leaky_relu,normal
343,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 147 --learning_rate 0.05127920882506296213 --batch_size 2124 --hidden_size 4247 --dropout 0.33273519342765212059 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.46740077808499336243,,1,,n1720,18585857,343_0,FAILED,SOBOL,147,0.051279208825062962129326393779,2124,4247,0.332735193427652120590209960938,2,0.4674007780849933624267578125,leaky_relu,normal
344,1753220917,31,1753220948,1753220954,6,python3 .tests/mnist/train --epochs 135 --learning_rate 0.0351000502202659867 --batch_size 1792 --hidden_size 6835 --dropout 0.08836163673549890518 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.58704532776027917862,,1,,n1720,18585858,344_0,FAILED,SOBOL,135,0.035100050220265986700152183175,1792,6835,0.088361636735498905181884765625,2,0.587045327760279178619384765625,leaky_relu,normal
345,1753220916,33,1753220949,1753220955,6,python3 .tests/mnist/train --epochs 32 --learning_rate 0.09859579779198393568 --batch_size 2558 --hidden_size 2338 --dropout 0.27605031896382570267 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.13742312882095575333,,1,,n1720,18585859,345_0,FAILED,SOBOL,32,0.098595797791983935676185524244,2558,2338,0.276050318963825702667236328125,3,0.137423128820955753326416015625,leaky_relu,normal
346,1753221195,26,1753221221,1753221227,6,python3 .tests/mnist/train --epochs 63 --learning_rate 0.00416266746800392912 --batch_size 718 --hidden_size 4699 --dropout 0.4396604062058031559 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.85043924301862716675,,1,,n1720,18585889,346_0,FAILED,SOBOL,63,0.004162667468003929116537875643,718,4699,0.439660406205803155899047851562,4,0.850439243018627166748046875,leaky_relu,normal
347,1753221357,14,1753221371,1753221377,6,python3 .tests/mnist/train --epochs 190 --learning_rate 0.06868279292741791275 --batch_size 3529 --hidden_size 513 --dropout 0.12781429523602128029 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.42506129294633865356,,1,,n1720,18585915,347_0,FAILED,SOBOL,190,0.068682792927417912753895734568,3529,513,0.127814295236021280288696289062,1,0.425061292946338653564453125,leaky_relu,normal
348,1753221472,19,1753221491,1753221498,7,python3 .tests/mnist/train --epochs 157 --learning_rate 0.01909669676478952319 --batch_size 2578 --hidden_size 1450 --dropout 0.24602132290601730347 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.97238863259553909302,,1,,n1720,18585919,348_0,FAILED,SOBOL,157,0.01909669676478952318743331773,2578,1450,0.246021322906017303466796875,2,0.972388632595539093017578125,leaky_relu,normal
349,1753221475,16,1753221491,1753221498,7,python3 .tests/mnist/train --epochs 96 --learning_rate 0.05842845745915547367 --batch_size 1300 --hidden_size 5649 --dropout 0.43284067139029502869 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.30286823958158493042,,1,,n1720,18585920,349_0,FAILED,SOBOL,96,0.058428457459155473674439207343,1300,5649,0.4328406713902950286865234375,3,0.302868239581584930419921875,leaky_relu,normal
350,1753226895,29,1753226924,1753226930,6,python3 .tests/mnist/train --epochs 41 --learning_rate 0.03891550659202039353 --batch_size 3636 --hidden_size 3402 --dropout 0.34729070914909243584 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71509638521820306778,,1,,n1720,18586432,350_0,FAILED,SOBOL,41,0.038915506592020393528130739469,3636,3402,0.347290709149092435836791992188,4,0.715096385218203067779541015625,leaky_relu,normal
351,1753226894,29,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 126 --learning_rate 0.07761314759170637179 --batch_size 314 --hidden_size 7913 --dropout 0.03463641880080103874 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.00961668882519006729,,1,,n1720,18586429,351_0,FAILED,SOBOL,126,0.077613147591706371786202112162,314,7913,0.034636418800801038742065429688,1,0.009616688825190067291259765625,leaky_relu,normal
352,1753226887,6,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 124 --learning_rate 0.02484101404324173812 --batch_size 1077 --hidden_size 4168 --dropout 0.40533676603808999062 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.65907750651240348816,,1,,n1720,18586423,352_0,FAILED,SOBOL,124,0.024841014043241738118439343452,1077,4168,0.405336766038089990615844726562,1,0.6590775065124034881591796875,leaky_relu,normal
353,1753226886,7,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 45 --learning_rate 0.06046555710686370849 --batch_size 2866 --hidden_size 1013 --dropout 0.21853279555216431618 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11669912561774253845,,1,,n1720,18586421,353_0,FAILED,SOBOL,45,0.060465557106863708491939490841,2866,1013,0.218532795552164316177368164062,4,0.1166991256177425384521484375,leaky_relu,normal
354,1753226884,9,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 98 --learning_rate 0.04253681729082018498 --batch_size 27 --hidden_size 6312 --dropout 0.00719342473894357681 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90343791712075471878,,1,,n1720,18586420,354_0,FAILED,SOBOL,98,0.042536817290820184978006324172,27,6312,0.007193424738943576812744140625,3,0.903437917120754718780517578125,leaky_relu,normal
355,1753226893,30,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 153 --learning_rate 0.07869791996674613266 --batch_size 3860 --hidden_size 2830 --dropout 0.31986285466700792313 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.32081644702702760696,,1,,n1720,18586427,355_0,FAILED,SOBOL,153,0.078697919966746132658386159164,3860,2830,0.319862854667007923126220703125,2,0.320816447027027606964111328125,leaky_relu,normal
356,1753226882,11,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 192 --learning_rate 0.033843392527289691 --batch_size 2270 --hidden_size 3925 --dropout 0.31106143398210406303 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77392016816884279251,,1,,n1720,18586419,356_0,FAILED,SOBOL,192,0.03384339252728969099637268414,2270,3925,0.311061433982104063034057617188,1,0.773920168168842792510986328125,leaky_relu,normal
357,1753226894,30,1753226924,1753226930,6,python3 .tests/mnist/train --epochs 59 --learning_rate 0.09519286592276766934 --batch_size 2015 --hidden_size 7421 --dropout 0.12335761217400431633 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.45106614101678133011,,1,,n1720,18586428,357_0,FAILED,SOBOL,59,0.095192865922767669339954466068,2015,7421,0.123357612174004316329956054688,4,0.451066141016781330108642578125,leaky_relu,normal
358,1753226896,27,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 30 --learning_rate 0.00229744718372821817 --batch_size 3304 --hidden_size 1981 --dropout 0.16288679838180541992 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.538594808429479599,,1,,n1720,18586433,358_0,FAILED,SOBOL,30,0.002297447183728218173676127734,3304,1981,0.162886798381805419921875,3,0.5385948084294795989990234375,leaky_relu,normal
359,1753226894,29,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 139 --learning_rate 0.06272010277388617716 --batch_size 1005 --hidden_size 5150 --dropout 0.47471753135323524475 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.23644892498850822449,,1,,n1720,18586431,359_0,FAILED,SOBOL,139,0.06272010277388617716098906385,1005,5150,0.4747175313532352447509765625,2,0.2364489249885082244873046875,leaky_relu,normal
360,1753226888,5,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 151 --learning_rate 0.04805193528942764553 --batch_size 3416 --hidden_size 7737 --dropout 0.22741573350504040718 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86488170269876718521,,1,,n1720,18586424,360_0,FAILED,SOBOL,151,0.048051935289427645525694998696,3416,7737,0.227415733505040407180786132812,2,0.864881702698767185211181640625,leaky_relu,normal
361,1753226886,9,1753226895,1753226901,6,python3 .tests/mnist/train --epochs 18 --learning_rate 0.0872068256295286115 --batch_size 604 --hidden_size 3482 --dropout 0.4140939381904900074 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.40646844450384378433,,1,,n1720,18586422,361_0,FAILED,SOBOL,18,0.087206825629528611498741952346,604,3482,0.414093938190490007400512695312,3,0.406468444503843784332275390625,leaky_relu,normal
362,1753226894,29,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 71 --learning_rate 0.01618578239884227443 --batch_size 2413 --hidden_size 5857 --dropout 0.35993392672389745712 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57260295748710632324,,1,,n1720,18586430,362_0,FAILED,SOBOL,71,0.016185782398842274432126941974,2413,5857,0.359933926723897457122802734375,4,0.5726029574871063232421875,leaky_relu,normal
363,1753226893,30,1753226923,1753226929,6,python3 .tests/mnist/train --epochs 180 --learning_rate 0.05509676508987322585 --batch_size 1647 --hidden_size 1402 --dropout 0.04713849257677793503 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15601588785648345947,,1,,n1720,18586426,363_0,FAILED,SOBOL,180,0.055096765089873225851313520707,1647,1402,0.047138492576777935028076171875,1,0.15601588785648345947265625,leaky_relu,normal
364,1753226882,11,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 165 --learning_rate 0.00790397314559668392 --batch_size 423 --hidden_size 306 --dropout 0.07157065114006400108 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.70236296951770782471,,1,,n1720,18586418,364_0,FAILED,SOBOL,165,0.007903973145596683916314084684,423,306,0.071570651140064001083374023438,2,0.70236296951770782470703125,leaky_relu,normal
365,1753226889,4,1753226893,1753226900,7,python3 .tests/mnist/train --epochs 86 --learning_rate 0.07118638051459566518 --batch_size 3746 --hidden_size 4747 --dropout 0.25939284777268767357 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02601221203804016113,,1,,n1720,18586425,365_0,FAILED,SOBOL,86,0.071186380514595665180976880038,3746,4747,0.259392847772687673568725585938,3,0.0260122120380401611328125,leaky_relu,normal
366,1753227555,31,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 57 --learning_rate 0.02513323021121323039 --batch_size 1441 --hidden_size 2514 --dropout 0.454120611771941185 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.98512219730764627457,,1,,n1720,18586443,366_0,FAILED,SOBOL,57,0.025133230211213230392841566641,1441,2514,0.45412061177194118499755859375,4,0.985122197307646274566650390625,leaky_relu,normal
367,1753227552,4,1753227556,1753227562,6,python3 .tests/mnist/train --epochs 112 --learning_rate 0.08983022453626618442 --batch_size 2719 --hidden_size 6756 --dropout 0.14240801520645618439 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.2864725673571228981,,1,,n1720,18586439,367_0,FAILED,SOBOL,112,0.089830224536266184420796321319,2719,6756,0.14240801520645618438720703125,1,0.286472567357122898101806640625,leaky_relu,normal
368,1753227556,30,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 106 --learning_rate 0.02890270041367038953 --batch_size 676 --hidden_size 1704 --dropout 0.34204713115468621254 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07368968706578016281,,1,,n1720,18586444,368_0,FAILED,SOBOL,106,0.028902700413670389528730808593,676,1704,0.342047131154686212539672851562,3,0.073689687065780162811279296875,leaky_relu,normal
369,1753227557,29,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 51 --learning_rate 0.0922338839162141072 --batch_size 3488 --hidden_size 5392 --dropout 0.02986926073208451271 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.65521049778908491135,,1,,n1720,18586445,369_0,FAILED,SOBOL,51,0.092233883916214107201447802709,3488,5392,0.029869260732084512710571289062,2,0.655210497789084911346435546875,leaky_relu,normal
370,1753227558,28,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 92 --learning_rate 0.01028069751271977993 --batch_size 1703 --hidden_size 3660 --dropout 0.19340784940868616104 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.3638255242258310318,,1,,n1720,18586449,370_0,FAILED,SOBOL,92,0.010280697512719779926348984134,1703,3660,0.193407849408686161041259765625,1,0.36382552422583103179931640625,leaky_relu,normal
371,1753227553,33,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 171 --learning_rate 0.07492890937756747916 --batch_size 2469 --hidden_size 7660 --dropout 0.38169531989842653275 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.90730432607233524323,,1,,n1720,18586442,371_0,FAILED,SOBOL,171,0.074928909377567479155324292606,2469,7660,0.381695319898426532745361328125,4,0.90730432607233524322509765625,leaky_relu,normal
372,1753227557,29,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 186 --learning_rate 0.01290721360230818321 --batch_size 3693 --hidden_size 6581 --dropout 0.49984694970771670341 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.48626325465738773346,,1,,n1720,18586447,372_0,FAILED,SOBOL,186,0.0129072136023081832090220189,3693,6581,0.499846949707716703414916992188,3,0.48626325465738773345947265625,leaky_relu,normal
373,1753227558,28,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 77 --learning_rate 0.05201332743670791792 --batch_size 371 --hidden_size 2595 --dropout 0.1865252065472304821 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78559949435293674469,,1,,n1720,18586448,373_0,FAILED,SOBOL,77,0.05201332743670791791679164362,371,2595,0.186525206547230482101440429688,2,0.78559949435293674468994140625,leaky_relu,normal
374,1753227552,34,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 12 --learning_rate 0.04498919270103797496 --batch_size 2651 --hidden_size 4441 --dropout 0.10117649286985397339 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.20125240366905927658,,1,,n1720,18586441,374_0,FAILED,SOBOL,12,0.044989192701037974964073384854,2651,4441,0.101176492869853973388671875,1,0.201252403669059276580810546875,leaky_relu,normal
375,1753227557,29,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 145 --learning_rate 0.08394895748011768633 --batch_size 1373 --hidden_size 767 --dropout 0.28838100656867027283 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.5269158361479640007,,1,,n1720,18586446,375_0,FAILED,SOBOL,145,0.083948957480117686325016279625,1373,767,0.2883810065686702728271484375,4,0.526915836147964000701904296875,leaky_relu,normal
376,1753227552,34,1753227586,1753227592,6,python3 .tests/mnist/train --epochs 133 --learning_rate 0.0048936426597647369 --batch_size 3047 --hidden_size 2272 --dropout 0.04058325337246060371 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.40254195593297481537,,1,,n1720,18586440,376_0,FAILED,SOBOL,133,0.004893642659764736897731740584,3047,2272,0.040583253372460603713989257812,4,0.40254195593297481536865234375,leaky_relu,normal
377,1753227550,6,1753227556,1753227562,6,python3 .tests/mnist/train --epochs 24 --learning_rate 0.06629189218878746293 --batch_size 1258 --hidden_size 7033 --dropout 0.35287949861958622932 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82193461619317531586,,1,,n1720,18586438,377_0,FAILED,SOBOL,24,0.066291892188787462925070315123,1258,7033,0.352879498619586229324340820312,1,0.82193461619317531585693359375,leaky_relu,normal
378,1753227549,7,1753227556,1753227562,6,python3 .tests/mnist/train --epochs 65 --learning_rate 0.03739339162083343132 --batch_size 4057 --hidden_size 68 --dropout 0.42359744664281606674 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.15994298364967107773,,1,,n1720,18586437,378_0,FAILED,SOBOL,65,0.03739339162083343132136903364,4057,68,0.423597446642816066741943359375,2,0.159942983649671077728271484375,leaky_relu,normal
379,1753227858,30,1753227888,1753227894,6,python3 .tests/mnist/train --epochs 198 --learning_rate 0.09776726475078613421 --batch_size 224 --hidden_size 5013 --dropout 0.23542811255902051926 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.61555041279643774033,,1,,n1720,18586451,379_0,FAILED,SOBOL,198,0.097767264750786134208659916567,224,5013,0.235428112559020519256591796875,3,0.615550412796437740325927734375,leaky_relu,normal
380,1753227874,14,1753227888,1753227894,6,python3 .tests/mnist/train --epochs 159 --learning_rate 0.03964476651446894456 --batch_size 1813 --hidden_size 6091 --dropout 0.13290719082579016685 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.03775127138942480087,,1,,n1720,18586452,380_0,FAILED,SOBOL,159,0.039644766514468944562654684205,1813,6091,0.132907190825790166854858398438,4,0.037751271389424800872802734375,leaky_relu,normal
381,1753227878,15,1753227893,1753227899,6,python3 .tests/mnist/train --epochs 104 --learning_rate 0.07522053307238966979 --batch_size 2069 --hidden_size 1132 --dropout 0.44610316818580031395 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.73749750759452581406,,1,,n1720,18586453,381_0,FAILED,SOBOL,104,0.075220533072389669793089694849,2069,1132,0.446103168185800313949584960938,1,0.737497507594525814056396484375,leaky_relu,normal
382,1753228508,12,1753228520,1753228526,6,python3 .tests/mnist/train --epochs 39 --learning_rate 0.02139175343466922716 --batch_size 819 --hidden_size 7984 --dropout 0.26595303229987621307 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.2747331615537405014,,1,,n1720,18586459,382_0,FAILED,SOBOL,39,0.021391753434669227157405302364,819,7984,0.26595303229987621307373046875,2,0.27473316155374050140380859375,leaky_relu,normal
383,1753228508,12,1753228520,1753228533,13,python3 .tests/mnist/train --epochs 118 --learning_rate 0.05760163819864392437 --batch_size 3119 --hidden_size 3209 --dropout 0.07862251438200473785 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.9499870743602514267,,1,,n1720,18586458,383_0,FAILED,SOBOL,118,0.057601638198643924371200597534,3119,3209,0.07862251438200473785400390625,3,0.94998707436025142669677734375,leaky_relu,normal
384,1753228587,24,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 117 --learning_rate 0.02668166353190317905 --batch_size 1880 --hidden_size 7592 --dropout 0.30458817444741725922 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.16765619069337844849,,1,,n1720,18586462,384_0,FAILED,SOBOL,117,0.026681663531903179048532237516,1880,7592,0.30458817444741725921630859375,1,0.167656190693378448486328125,leaky_relu,normal
385,1753228591,20,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 38 --learning_rate 0.08821329097356647719 --batch_size 2135 --hidden_size 3599 --dropout 0.11640310473740100861 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.62324856966733932495,,1,,n1720,18586466,385_0,FAILED,SOBOL,38,0.08821329097356647719330169366,2135,3599,0.11640310473740100860595703125,4,0.623248569667339324951171875,leaky_relu,normal
386,1753228584,27,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 105 --learning_rate 0.00937456881767138872 --batch_size 886 --hidden_size 5444 --dropout 0.17154254158958792686 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.39485910627990961075,,1,,n1720,18586460,386_0,FAILED,SOBOL,105,0.009374568817671388720746961098,886,5444,0.171542541589587926864624023438,3,0.394859106279909610748291015625,leaky_relu,normal
387,1753228587,24,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 160 --learning_rate 0.06958916789703072092 --batch_size 3186 --hidden_size 1778 --dropout 0.48388408636674284935 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.81426711473613977432,,1,,n1720,18586461,387_0,FAILED,SOBOL,160,0.069589167897030720921769386678,3186,1778,0.483884086366742849349975585938,2,0.814267114736139774322509765625,leaky_relu,normal
388,1753228587,25,1753228612,1753228619,7,python3 .tests/mnist/train --epochs 199 --learning_rate 0.01766557182511314592 --batch_size 2984 --hidden_size 700 --dropout 0.3969251653179526329 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.26680614147335290909,,1,,n1720,18586463,388_0,FAILED,SOBOL,199,0.017665571825113145915109313933,2984,700,0.396925165317952632904052734375,1,0.266806141473352909088134765625,leaky_relu,normal
389,1753228588,23,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 66 --learning_rate 0.05349664667434991111 --batch_size 1196 --hidden_size 4380 --dropout 0.20961038302630186081 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.94207546208053827286,,1,,n1720,18586465,389_0,FAILED,SOBOL,66,0.053496646674349911110279975901,1196,4380,0.209610383026301860809326171875,4,0.942075462080538272857666015625,leaky_relu,normal
390,1753228593,47,1753228640,1753228646,6,python3 .tests/mnist/train --epochs 23 --learning_rate 0.04960327440807596466 --batch_size 3995 --hidden_size 2649 --dropout 0.0139108230359852314 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.04570870846509933472,,1,,n1720,18586470,390_0,FAILED,SOBOL,23,0.049603274408075964663211721017,3995,2649,0.013910823035985231399536132812,3,0.045708708465099334716796875,leaky_relu,normal
391,1753228593,47,1753228640,1753228646,6,python3 .tests/mnist/train --epochs 132 --learning_rate 0.08558069831263274974 --batch_size 161 --hidden_size 6657 --dropout 0.32706150086596608162 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.7454397156834602356,,1,,n1720,18586472,391_0,FAILED,SOBOL,132,0.085580698312632749735762160981,161,6657,0.327061500865966081619262695312,2,0.745439715683460235595703125,leaky_relu,normal
392,1753228593,18,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 144 --learning_rate 0.00072538694934919481 --batch_size 3626 --hidden_size 5088 --dropout 0.06266313791275024414 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.3719813050702214241,,1,,n1720,18586467,392_0,FAILED,SOBOL,144,0.000725386949349194807244722849,3626,5088,0.062663137912750244140625,2,0.371981305070221424102783203125,leaky_relu,normal
393,1753228587,27,1753228614,1753228620,6,python3 .tests/mnist/train --epochs 12 --learning_rate 0.06421432610396296536 --batch_size 304 --hidden_size 121 --dropout 0.25096634402871131897 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.91547545511275529861,,1,,n1720,18586464,393_0,FAILED,SOBOL,12,0.064214326103962965364146953107,304,121,0.2509663440287113189697265625,3,0.915475455112755298614501953125,leaky_relu,normal
394,1753228593,52,1753228645,1753228651,6,python3 .tests/mnist/train --epochs 78 --learning_rate 0.03220283130658790904 --batch_size 2584 --hidden_size 6972 --dropout 0.46133392257615923882 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.06550324335694313049,,1,,n1720,18586471,394_0,FAILED,SOBOL,78,0.032202831306587909043770423523,2584,6972,0.461333922576159238815307617188,4,0.0655032433569431304931640625,leaky_relu,normal
395,1753228593,19,1753228612,1753228619,7,python3 .tests/mnist/train --epochs 187 --learning_rate 0.09671614686027170393 --batch_size 1306 --hidden_size 2206 --dropout 0.14911075262352824211 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.6470090039074420929,,1,,n1720,18586469,395_0,FAILED,SOBOL,187,0.096716146860271703933342735127,1306,2206,0.149110752623528242111206054688,1,0.6470090039074420928955078125,leaky_relu,normal
396,1753228593,18,1753228611,1753228617,6,python3 .tests/mnist/train --epochs 172 --learning_rate 0.04088706231592223461 --batch_size 739 --hidden_size 3283 --dropout 0.22044656518846750259 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.19379847124218940735,,1,,n1720,18586468,396_0,FAILED,SOBOL,172,0.040887062315922234612131092035,739,3283,0.220446565188467502593994140625,2,0.1937984712421894073486328125,leaky_relu,normal
397,1753228825,27,1753228852,1753228858,6,python3 .tests/mnist/train --epochs 93 --learning_rate 0.08022410670220853079 --batch_size 3550 --hidden_size 8036 --dropout 0.40763534326106309891 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.51944667473435401917,,1,,n1720,18586474,397_0,FAILED,SOBOL,93,0.080224106702208530794706575762,3550,8036,0.407635343261063098907470703125,3,0.5194466747343540191650390625,leaky_relu,normal
398,1753229019,16,1753229035,1753229041,6,python3 .tests/mnist/train --epochs 50 --learning_rate 0.02326604801090434091 --batch_size 1765 --hidden_size 1071 --dropout 0.36908557871356606483 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.49368658382445573807,,1,,n1720,18586478,398_0,FAILED,SOBOL,50,0.023266048010904340909155152417,1765,1071,0.369085578713566064834594726562,4,0.493686583824455738067626953125,leaky_relu,normal
399,1753229045,17,1753229062,1753229068,6,python3 .tests/mnist/train --epochs 105 --learning_rate 0.06196897419113666511 --batch_size 2532 --hidden_size 6024 --dropout 0.0558091350831091404 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.79303823132067918777,,1,,n1720,18586481,399_0,FAILED,SOBOL,105,0.061968974191136665108370351618,2532,6024,0.055809135083109140396118164062,1,0.793038231320679187774658203125,leaky_relu,normal
400,1753235046,47,1753235093,1753235099,6,python3 .tests/mnist/train --epochs 111 --learning_rate 0.0198868121834471813 --batch_size 490 --hidden_size 2890 --dropout 0.49092468433082103729 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.56469120737165212631,,1,,n1720,18586661,400_0,FAILED,SOBOL,111,0.019886812183447181295870009876,490,2890,0.49092468433082103729248046875,3,0.564691207371652126312255859375,leaky_relu,normal
401,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 56 --learning_rate 0.05917508043618872893 --batch_size 3812 --hidden_size 6378 --dropout 0.17811351455748081207 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.14808902796357870102,,1,,n1720,18586657,401_0,FAILED,SOBOL,56,0.059175080436188728927326963003,3812,6378,0.17811351455748081207275390625,2,0.148089027963578701019287109375,leaky_relu,normal
402,1753235043,17,1753235060,1753235067,7,python3 .tests/mnist/train --epochs 87 --learning_rate 0.03812010357379913561 --batch_size 1508 --hidden_size 938 --dropout 0.10837499191984534264 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.87282389216125011444,,1,,n1720,18586653,402_0,FAILED,SOBOL,87,0.03812010357379913561004514122,1508,938,0.108374991919845342636108398438,1,0.87282389216125011444091796875,leaky_relu,normal
403,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 166 --learning_rate 0.0768718122142367094 --batch_size 2786 --hidden_size 4114 --dropout 0.29509849613532423973 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.41442592255771160126,,1,,n1720,18586655,403_0,FAILED,SOBOL,166,0.076871812214236709404069358698,2786,4114,0.295098496135324239730834960938,4,0.41442592255771160125732421875,leaky_relu,normal
404,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 181 --learning_rate 0.03587163447812199979 --batch_size 3353 --hidden_size 5211 --dropout 0.33509277459233999252 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.99282015673816204071,,1,,n1720,18586663,404_0,FAILED,SOBOL,181,0.035871634478121999789479446008,3353,5211,0.335092774592339992523193359375,3,0.99282015673816204071044921875,leaky_relu,normal
405,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 72 --learning_rate 0.09940935013843700541 --batch_size 542 --hidden_size 2048 --dropout 0.02339591365307569504 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.29418599419295787811,,1,,n1720,18586660,405_0,FAILED,SOBOL,72,0.099409350138437005406366608895,542,2048,0.023395913653075695037841796875,2,0.29418599419295787811279296875,leaky_relu,normal
406,1753235035,24,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 18 --learning_rate 0.00339789516273885945 --batch_size 2351 --hidden_size 7347 --dropout 0.20257425354793667793 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.69469538982957601547,,1,,n1720,18586649,406_0,FAILED,SOBOL,18,0.003397895162738859449469419616,2351,7347,0.202574253547936677932739257812,1,0.694695389829576015472412109375,leaky_relu,normal
407,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 150 --learning_rate 0.067862428628373897 --batch_size 1584 --hidden_size 3873 --dropout 0.39035115065053105354 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.01832946296781301498,,1,,n1720,18586659,407_0,FAILED,SOBOL,150,0.067862428628373896999370629146,1584,3873,0.390351150650531053543090820312,4,0.018329462967813014984130859375,leaky_relu,normal
408,1753235045,43,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 138 --learning_rate 0.04661684455703944685 --batch_size 2204 --hidden_size 1349 --dropout 0.12644874304533004761 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.89596872217953205109,,1,,n1720,18586664,408_0,FAILED,SOBOL,138,0.04661684455703944685023287775,2204,1349,0.126448743045330047607421875,4,0.89596872217953205108642578125,leaky_relu,normal
409,1753235046,42,1753235088,1753235094,6,python3 .tests/mnist/train --epochs 30 --learning_rate 0.08239914327273145656 --batch_size 1949 --hidden_size 5782 --dropout 0.43913390859961509705 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.31336254067718982697,,1,,n1720,18586662,409_0,FAILED,SOBOL,30,0.082399143272731456555391105212,1949,5782,0.4391339085996150970458984375,1,0.31336254067718982696533203125,leaky_relu,normal
410,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 60 --learning_rate 0.01450580710656940858 --batch_size 3238 --hidden_size 3549 --dropout 0.2746235276572406292 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.66651609074324369431,,1,,n1720,18586656,410_0,FAILED,SOBOL,60,0.014505807106569408582164015797,3238,3549,0.274623527657240629196166992188,2,0.666516090743243694305419921875,leaky_relu,normal
411,1753235044,15,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 193 --learning_rate 0.05053201347133145366 --batch_size 938 --hidden_size 7799 --dropout 0.08777425764128565788 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.12412260007113218307,,1,,n1720,18586654,411_0,FAILED,SOBOL,193,0.050532013471331453657864329898,938,7799,0.087774257641285657882690429688,3,0.124122600071132183074951171875,leaky_relu,normal
412,1753235042,17,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 154 --learning_rate 0.01187638521902263135 --batch_size 1139 --hidden_size 6702 --dropout 0.03215690050274133682 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.54676584433764219284,,1,,n1720,18586652,412_0,FAILED,SOBOL,154,0.011876385219022631348217977632,1139,6702,0.032156900502741336822509765625,4,0.546765844337642192840576171875,leaky_relu,normal
413,1753235035,27,1753235062,1753235068,6,python3 .tests/mnist/train --epochs 99 --learning_rate 0.07345678916638717637 --batch_size 2928 --hidden_size 2439 --dropout 0.34397189784795045853 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.24460479151457548141,,1,,n1720,18586651,413_0,FAILED,SOBOL,99,0.073456789166387176370776046497,2928,2439,0.343971897847950458526611328125,1,0.244604791514575481414794921875,leaky_relu,normal
414,1753235045,14,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 44 --learning_rate 0.03052115851547568953 --batch_size 89 --hidden_size 4814 --dropout 0.43030003318563103676 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.76571846194565296173,,1,,n1720,18586658,414_0,FAILED,SOBOL,44,0.030521158515475689532170378016,89,4814,0.430300033185631036758422851562,2,0.76571846194565296173095703125,leaky_relu,normal
415,1753235035,24,1753235059,1753235065,6,python3 .tests/mnist/train --epochs 123 --learning_rate 0.09068697550678626873 --batch_size 3923 --hidden_size 367 --dropout 0.24264151090756058693 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.4428799021989107132,,1,,n1720,18586650,415_0,FAILED,SOBOL,123,0.090686975506786268730330391463,3923,367,0.242641510907560586929321289062,3,0.44287990219891071319580078125,leaky_relu,normal
416,1753235786,26,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 127 --learning_rate 0.00708437176737934399 --batch_size 2639 --hidden_size 4048 --dropout 0.31646787328645586967 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.8581525823101401329,,1,,n1720,18586672,416_0,FAILED,SOBOL,127,0.007084371767379343994008866758,2639,4048,0.316467873286455869674682617188,3,0.858152582310140132904052734375,leaky_relu,normal
417,1753235785,27,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 42 --learning_rate 0.07042084528850392489 --batch_size 1362 --hidden_size 7267 --dropout 0.00466801552101969719 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.43275934364646673203,,1,,n1720,18586670,417_0,FAILED,SOBOL,42,0.070420845288503924885858964444,1362,7267,0.004668015521019697189331054688,2,0.432759343646466732025146484375,leaky_relu,normal
418,1753235784,28,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 95 --learning_rate 0.02594754398986697311 --batch_size 3698 --hidden_size 1840 --dropout 0.21519863605499267578 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.57936260662972927094,,1,,n1720,18586668,418_0,FAILED,SOBOL,95,0.025947543989866973107583092428,3698,1840,0.21519863605499267578125,1,0.57936260662972927093505859375,leaky_relu,normal
419,1753235797,15,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 156 --learning_rate 0.09060104736192152453 --batch_size 375 --hidden_size 5258 --dropout 0.40287253633141517639 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.12975551746785640717,,1,,n1720,18586677,419_0,FAILED,SOBOL,156,0.090601047361921524525563143015,375,5258,0.4028725363314151763916015625,4,0.12975551746785640716552734375,leaky_relu,normal
420,1753235787,25,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 189 --learning_rate 0.04731136134415865613 --batch_size 1726 --hidden_size 4323 --dropout 0.47414538124576210976 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.7071694936603307724,,1,,n1720,18586673,420_0,FAILED,SOBOL,189,0.047311361344158656128122686368,1726,4323,0.474145381245762109756469726562,3,0.70716949366033077239990234375,leaky_relu,normal
421,1753235784,28,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 62 --learning_rate 0.08641066117910668753 --batch_size 2493 --hidden_size 891 --dropout 0.16144483769312500954 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.00170496664941310883,,1,,n1720,18586669,421_0,FAILED,SOBOL,62,0.086410661179106687534989816868,2493,891,0.161444837693125009536743164062,2,0.00170496664941310882568359375,leaky_relu,normal
422,1753235797,44,1753235841,1753235847,6,python3 .tests/mnist/train --epochs 33 --learning_rate 0.01693316829670220638 --batch_size 652 --hidden_size 6203 --dropout 0.12284640315920114517 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.98034620191901922226,,1,,n1720,18586678,422_0,FAILED,SOBOL,33,0.016933168296702206384596323119,652,6203,0.122846403159201145172119140625,1,0.980346201919019222259521484375,leaky_relu,normal
423,1753235797,15,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 136 --learning_rate 0.05588611758770421767 --batch_size 3464 --hidden_size 2971 --dropout 0.30968053359538316727 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.31081034149974584579,,1,,n1720,18586676,423_0,FAILED,SOBOL,136,0.055886117587704217668509443229,3464,2971,0.309680533595383167266845703125,4,0.310810341499745845794677734375,leaky_relu,normal
424,1753235797,44,1753235841,1753235847,6,python3 .tests/mnist/train --epochs 148 --learning_rate 0.03302964963670820125 --batch_size 829 --hidden_size 447 --dropout 0.05065567931160330772 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.68161473609507083893,,1,,n1720,18586679,424_0,FAILED,SOBOL,148,0.033029649636708201254631234178,829,447,0.050655679311603307723999023438,4,0.68161473609507083892822265625,leaky_relu,normal
425,1753235797,44,1753235841,1753235847,6,python3 .tests/mnist/train --epochs 21 --learning_rate 0.09442109112078324318 --batch_size 3129 --hidden_size 4638 --dropout 0.36233716225251555443 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.10585012473165988922,,1,,n1720,18586680,425_0,FAILED,SOBOL,21,0.094421091120783243177960741832,3129,4638,0.362337162252515554428100585938,1,0.10585012473165988922119140625,leaky_relu,normal
426,1753235786,26,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 74 --learning_rate 0.00311800202690064917 --batch_size 1807 --hidden_size 2391 --dropout 0.41755000315606594086 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.88087016623467206955,,1,,n1720,18586671,426_0,FAILED,SOBOL,74,0.003118002026900649169272039529,1807,2391,0.41755000315606594085693359375,2,0.880870166234672069549560546875,leaky_relu,normal
427,1753235788,24,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 177 --learning_rate 0.06348506562327967118 --batch_size 2063 --hidden_size 6910 --dropout 0.22975796647369861603 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.33163492660969495773,,1,,n1720,18586674,427_0,FAILED,SOBOL,177,0.06348506562327967117642657513,2063,6910,0.22975796647369861602783203125,3,0.331634926609694957733154296875,leaky_relu,normal
428,1753235797,15,1753235812,1753235818,6,python3 .tests/mnist/train --epochs 168 --learning_rate 0.02409458161033689941 --batch_size 4036 --hidden_size 7846 --dropout 0.14285825984552502632 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.75330554228276014328,,1,,n1720,18586675,428_0,FAILED,SOBOL,168,0.024094581610336899407665001149,4036,7846,0.142858259845525026321411132812,4,0.753305542282760143280029296875,leaky_relu,normal
429,1753235993,30,1753236023,1753236029,6,python3 .tests/mnist/train --epochs 83 --learning_rate 0.0596756322323344704 --batch_size 203 --hidden_size 3341 --dropout 0.45568456919863820076 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.45993149559944868088,,1,,n1720,18586682,429_0,FAILED,SOBOL,83,0.059675632232334470395063164005,203,3341,0.455684569198638200759887695312,1,0.459931495599448680877685546875,leaky_relu,normal
430,1753235993,32,1753236025,1753236032,7,python3 .tests/mnist/train --epochs 54 --learning_rate 0.04327796212416142735 --batch_size 3074 --hidden_size 5702 --dropout 0.25978185143321752548 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.55917891301214694977,,1,,n1720,18586683,430_0,FAILED,SOBOL,54,0.043277962124161427348578712326,3074,5702,0.259781851433217525482177734375,2,0.55917891301214694976806640625,leaky_relu,normal
431,1753235994,29,1753236023,1753236029,6,python3 .tests/mnist/train --epochs 115 --learning_rate 0.07949313244083897056 --batch_size 1284 --hidden_size 1524 --dropout 0.07307372521609067917 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.22755304910242557526,,1,,n1720,18586684,431_0,FAILED,SOBOL,115,0.079493132440838970564911392103,1284,1524,0.073073725216090679168701171875,3,0.22755304910242557525634765625,leaky_relu,normal
432,1753236541,24,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 109 --learning_rate 0.04041049228468910487 --batch_size 3327 --hidden_size 6448 --dropout 0.38013131869956851006 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.38201887905597686768,,1,,n1720,18586707,432_0,FAILED,SOBOL,109,0.040410492284689104869332965109,3327,6448,0.380131318699568510055541992188,1,0.38201887905597686767578125,leaky_relu,normal
433,1753236550,15,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 48 --learning_rate 0.07604032499473542539 --batch_size 1027 --hidden_size 2697 --dropout 0.19295768020674586296 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.83076944947242736816,,1,,n1720,18586714,433_0,FAILED,SOBOL,48,0.076040324994735425390146588143,1027,2697,0.192957680206745862960815429688,4,0.8307694494724273681640625,leaky_relu,normal
434,1753236541,24,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 89 --learning_rate 0.02062074006488546704 --batch_size 2245 --hidden_size 4556 --dropout 0.02836626023054122925 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.18049656692892313004,,1,,n1720,18586708,434_0,FAILED,SOBOL,89,0.020620740064885467041078115358,2245,4556,0.028366260230541229248046875,3,0.180496566928923130035400390625,leaky_relu,normal
435,1753236548,17,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 174 --learning_rate 0.05678713387586176858 --batch_size 1989 --hidden_size 620 --dropout 0.34165808185935020447 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.60674608591943979263,,1,,n1720,18586712,435_0,FAILED,SOBOL,174,0.056787133875861768583792610343,1989,620,0.3416580818593502044677734375,2,0.606746085919439792633056640625,leaky_relu,normal
436,1753236542,23,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 183 --learning_rate 0.00568961656605824866 --batch_size 16 --hidden_size 1603 --dropout 0.28597781667485833168 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.06025797966867685318,,1,,n1720,18586709,436_0,FAILED,SOBOL,183,0.005689616566058248656179152647,16,1603,0.285977816674858331680297851562,1,0.060257979668676853179931640625,leaky_relu,normal
437,1753236549,16,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 80 --learning_rate 0.06703227558992803925 --batch_size 3849 --hidden_size 5525 --dropout 0.09765923256054520607 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.72674005571752786636,,1,,n1720,18586713,437_0,FAILED,SOBOL,80,0.067032275589928039249976166047,3849,5525,0.097659232560545206069946289062,4,0.726740055717527866363525390625,leaky_relu,normal
438,1753236551,14,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 15 --learning_rate 0.03660422966713085952 --batch_size 1082 --hidden_size 3807 --dropout 0.1841828981414437294 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.25225695967674255371,,1,,n1720,18586716,438_0,FAILED,SOBOL,15,0.036604229667130859515733476428,1082,3807,0.184182898141443729400634765625,3,0.2522569596767425537109375,leaky_relu,normal
439,1753236545,20,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 142 --learning_rate 0.09702006939705461186 --batch_size 2871 --hidden_size 7545 --dropout 0.49639092851430177689 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.960775032639503479,,1,,n1720,18586710,439_0,FAILED,SOBOL,142,0.097020069397054611859410044872,2871,7545,0.496390928514301776885986328125,2,0.96077503263950347900390625,leaky_relu,normal
440,1753236550,15,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 130 --learning_rate 0.01367879786016419456 --batch_size 1421 --hidden_size 5976 --dropout 0.2368701486848294735 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.07852672506123781204,,1,,n1720,18586715,440_0,FAILED,SOBOL,130,0.013678797860164194563625805756,1421,5976,0.236870148684829473495483398438,2,0.078526725061237812042236328125,leaky_relu,normal
441,1753236545,20,1753236565,1753236571,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.05282687978316098765 --batch_size 2698 --hidden_size 1279 --dropout 0.42416955297812819481 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.63081169594079256058,,1,,n1720,18586711,441_0,FAILED,SOBOL,27,0.052826879783160987646972728271,2698,1279,0.424169552978128194808959960938,3,0.630811695940792560577392578125,leaky_relu,normal
442,1753236713,32,1753236745,1753236751,6,python3 .tests/mnist/train --epochs 68 --learning_rate 0.0442244203957729079 --batch_size 450 --hidden_size 8116 --dropout 0.35426035337150096893 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.35895797237753868103,,1,,n1720,18586767,442_0,FAILED,SOBOL,68,0.044224420395772907899090142791,450,8116,0.35426035337150096893310546875,4,0.3589579723775386810302734375,leaky_relu,normal
443,1753236714,31,1753236745,1753236751,6,python3 .tests/mnist/train --epochs 195 --learning_rate 0.08312859318107367057 --batch_size 3773 --hidden_size 3107 --dropout 0.04109453596174716949 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.93167261406779289246,,1,,n1720,18586768,443_0,FAILED,SOBOL,195,0.083128593181073670570491174203,3773,3107,0.04109453596174716949462890625,1,0.9316726140677928924560546875,leaky_relu,normal
444,1753236716,29,1753236745,1753236751,6,python3 .tests/mnist/train --epochs 162 --learning_rate 0.02969281583232805111 --batch_size 2422 --hidden_size 2125 --dropout 0.08114785002544522285 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.47944257780909538269,,1,,n1720,18586769,444_0,FAILED,SOBOL,162,0.029692815832328051106614452692,2422,2125,0.081147850025445222854614257812,2,0.4794425778090953826904296875,leaky_relu,normal
445,1753236893,33,1753236926,1753236932,6,python3 .tests/mnist/train --epochs 101 --learning_rate 0.09298050689324736939 --batch_size 1655 --hidden_size 7148 --dropout 0.26934805931523442268 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.81192090734839439392,,1,,n1720,18586773,445_0,FAILED,SOBOL,101,0.092980506893247369393229462275,1655,7148,0.269348059315234422683715820312,3,0.8119209073483943939208984375,leaky_relu,normal
446,1753236901,25,1753236926,1753236932,6,python3 .tests/mnist/train --epochs 36 --learning_rate 0.00948529449449852027 --batch_size 3408 --hidden_size 168 --dropout 0.4485674416646361351 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.20804256666451692581,,1,,n1720,18586774,446_0,FAILED,SOBOL,36,0.009485294494498520273539909908,3408,168,0.448567441664636135101318359375,4,0.208042566664516925811767578125,leaky_relu,normal
447,1753236914,12,1753236926,1753236932,6,python3 .tests/mnist/train --epochs 121 --learning_rate 0.07418757400009781677 --batch_size 597 --hidden_size 4879 --dropout 0.1362412748858332634 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.50056390929967164993,,1,,n1720,18586775,447_0,FAILED,SOBOL,121,0.074187574000097816773191539141,597,4879,0.136241274885833263397216796875,1,0.500563909299671649932861328125,leaky_relu,normal
448,1753237138,29,1753237167,1753237173,6,python3 .tests/mnist/train --epochs 122 --learning_rate 0.0159792801066301754 --batch_size 3569 --hidden_size 1159 --dropout 0.00104593485593795776 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.69918790459632873535,,1,,n1720,18586778,448_0,FAILED,SOBOL,122,0.015979280106630175395387993831,3569,1159,0.001045934855937957763671875,2,0.6991879045963287353515625,leaky_relu,normal
449,1753237139,28,1753237167,1753237173,6,python3 .tests/mnist/train --epochs 34 --learning_rate 0.05528049698658287631 --batch_size 757 --hidden_size 5936 --dropout 0.3142308257520198822 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.02971322834491729736,,1,,n1720,18586779,449_0,FAILED,SOBOL,34,0.055280496986582876306481892925,757,5936,0.3142308257520198822021484375,3,0.02971322834491729736328125,leaky_relu,normal
450,1753243795,25,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 100 --learning_rate 0.04825843776771799459 --batch_size 2518 --hidden_size 3179 --dropout 0.39977647317573428154 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.98832715395838022232,,1,,n1720,18586944,450_0,FAILED,SOBOL,100,0.048258437767717994593130725889,2518,3179,0.399776473175734281539916992188,4,0.988327153958380222320556640625,leaky_relu,normal
451,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 164 --learning_rate 0.08702309354674071795 --batch_size 1752 --hidden_size 8140 --dropout 0.21243510721251368523 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.28280174080282449722,,1,,n1720,18586953,451_0,FAILED,SOBOL,164,0.087023093546740717951770704985,1752,8140,0.212435107212513685226440429688,1,0.282801740802824497222900390625,leaky_relu,normal
452,1753243789,31,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 196 --learning_rate 0.02573311104262247795 --batch_size 290 --hidden_size 7060 --dropout 0.15675480756908655167 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.86076491419225931168,,1,,n1720,18586936,452_0,FAILED,SOBOL,196,0.025733111042622477948604853282,290,7060,0.156754807569086551666259765625,2,0.860764914192259311676025390625,leaky_relu,normal
453,1753243787,33,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 66 --learning_rate 0.08925940205659717297 --batch_size 3612 --hidden_size 2118 --dropout 0.46906953025609254837 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.41109687928110361099,,1,,n1720,18586933,453_0,FAILED,SOBOL,66,0.089259402056597172969709674817,3612,2118,0.469069530256092548370361328125,3,0.411096879281103610992431640625,leaky_relu,normal
454,1753243797,26,1753243823,1753243829,6,python3 .tests/mnist/train --epochs 26 --learning_rate 0.00730409250026568813 --batch_size 1324 --hidden_size 4984 --dropout 0.30545607814565300941 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.57675065100193023682,,1,,n1720,18586946,454_0,FAILED,SOBOL,26,0.007304092500265688125971053068,1324,4984,0.305456078145653009414672851562,4,0.57675065100193023681640625,leaky_relu,normal
455,1753243798,51,1753243849,1753243862,13,python3 .tests/mnist/train --epochs 131 --learning_rate 0.07175720280818641272 --batch_size 2602 --hidden_size 225 --dropout 0.11730545992031693459 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.15141853690147399902,,1,,n1720,18586950,455_0,FAILED,SOBOL,131,0.071757202808186412723578939676,2602,225,0.117305459920316934585571289062,1,0.1514185369014739990234375,leaky_relu,normal
456,1753243789,31,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 143 --learning_rate 0.04271892974851653618 --batch_size 1179 --hidden_size 2817 --dropout 0.3660778682678937912 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.77802014816552400589,,1,,n1720,18586938,456_0,FAILED,SOBOL,143,0.042718929748516536182290082024,1179,2817,0.36607786826789379119873046875,1,0.778020148165524005889892578125,leaky_relu,normal
457,1753243790,30,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 14 --learning_rate 0.07848979786336422737 --batch_size 2968 --hidden_size 6489 --dropout 0.05277460254728794098 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.44645546842366456985,,1,,n1720,18586939,457_0,FAILED,SOBOL,14,0.078489797863364227370475134649,2968,6489,0.05277460254728794097900390625,4,0.446455468423664569854736328125,leaky_relu,normal
458,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 78 --learning_rate 0.02465890177162364041 --batch_size 177 --hidden_size 549 --dropout 0.23297194531187415123 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.53446463868021965027,,1,,n1720,18586952,458_0,FAILED,SOBOL,78,0.024658901771623640414299316603,177,549,0.232971945311874151229858398438,3,0.5344646386802196502685546875,leaky_relu,normal
459,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 184 --learning_rate 0.06067367902416736375 --batch_size 4010 --hidden_size 4532 --dropout 0.42019517486914992332 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.24102970585227012634,,1,,n1720,18586948,459_0,FAILED,SOBOL,184,0.060673679024167363749153736308,4010,4532,0.420195174869149923324584960938,2,0.2410297058522701263427734375,leaky_relu,normal
460,1753243788,32,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 176 --learning_rate 0.00172195655899122372 --batch_size 2148 --hidden_size 5612 --dropout 0.46024858113378286362 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.66227295622229576111,,1,,n1720,18586935,460_0,FAILED,SOBOL,176,0.001721956558991223715932017413,2148,5612,0.460248581133782863616943359375,1,0.6622729562222957611083984375,leaky_relu,normal
461,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 88 --learning_rate 0.06331531508807093644 --batch_size 1892 --hidden_size 1610 --dropout 0.14805962424725294113 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.11297677084803581238,,1,,n1720,18586949,461_0,FAILED,SOBOL,88,0.063315315088070936444530900644,1892,1610,0.148059624247252941131591796875,4,0.1129767708480358123779296875,leaky_relu,normal
462,1753243789,31,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 46 --learning_rate 0.03441888333810493722 --batch_size 3166 --hidden_size 7440 --dropout 0.07717239903286099434 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.90021138358861207962,,1,,n1720,18586937,462_0,FAILED,SOBOL,46,0.034418883338104937219537049486,3166,7440,0.077172399032860994338989257812,3,0.900211383588612079620361328125,leaky_relu,normal
463,1753243796,24,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 110 --learning_rate 0.0945976534225046739 --batch_size 866 --hidden_size 3750 --dropout 0.26544902147725224495 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.324507896788418293,,1,,n1720,18586945,463_0,FAILED,SOBOL,110,0.094597653422504673903503658039,866,3750,0.265449021477252244949340820312,2,0.324507896788418292999267578125,leaky_relu,normal
464,1753243798,51,1753243849,1753243855,6,python3 .tests/mnist/train --epochs 116 --learning_rate 0.03681942479088903125 --batch_size 2913 --hidden_size 4710 --dropout 0.1877562403678894043 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.03359824325889348984,,1,,n1720,18586947,464_0,FAILED,SOBOL,116,0.036819424790889031251506224862,2913,4710,0.187756240367889404296875,4,0.033598243258893489837646484375,leaky_relu,normal
465,1753243793,27,1753243820,1753243826,6,python3 .tests/mnist/train --epochs 52 --learning_rate 0.0983640012319199758 --batch_size 1124 --hidden_size 470 --dropout 0.37556735053658485413 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.74217744078487157822,,1,,n1720,18586942,465_0,FAILED,SOBOL,52,0.098364001231919975798412281165,1124,470,0.3755673505365848541259765625,1,0.742177440784871578216552734375,leaky_relu,normal
466,1753244584,20,1753244604,1753244610,6,python3 .tests/mnist/train --epochs 82 --learning_rate 0.00546760930363088867 --batch_size 3939 --hidden_size 6790 --dropout 0.33599095745012164116 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.27891709469258785248,,1,,n1720,18586981,466_0,FAILED,SOBOL,82,0.005467609303630888671621246289,3939,6790,0.335990957450121641159057617188,2,0.27891709469258785247802734375,leaky_relu,normal
467,1753244591,12,1753244603,1753244609,6,python3 .tests/mnist/train --epochs 170 --learning_rate 0.06569515589373187137 --batch_size 106 --hidden_size 2351 --dropout 0.02426751283928751945 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.94533822499215602875,,1,,n1720,18586984,467_0,FAILED,SOBOL,170,0.065695155893731871366014729574,106,2351,0.024267512839287519454956054688,3,0.94533822499215602874755859375,leaky_relu,normal
468,1753244582,20,1753244602,1753244609,7,python3 .tests/mnist/train --epochs 178 --learning_rate 0.02157234172541648218 --batch_size 1968 --hidden_size 3445 --dropout 0.09554038289934396744 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.39939931593835353851,,1,,n1720,18586979,468_0,FAILED,SOBOL,178,0.021572341725416482177690724598,1968,3445,0.095540382899343967437744140625,4,0.39939931593835353851318359375,leaky_relu,normal
469,1753244585,16,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 72 --learning_rate 0.0573919923004694299 --batch_size 2224 --hidden_size 7903 --dropout 0.28223706502467393875 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.82558794878423213959,,1,,n1720,18586982,469_0,FAILED,SOBOL,72,0.057391992300469429899578699406,2224,7903,0.282237065024673938751220703125,1,0.82558794878423213958740234375,leaky_relu,normal
470,1753244593,8,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 20 --learning_rate 0.03946417803764343951 --batch_size 926 --hidden_size 1437 --dropout 0.49374571302905678749 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.16311551537364721298,,1,,n1720,18586986,470_0,FAILED,SOBOL,20,0.039464178037643439511672482922,926,1437,0.493745713029056787490844726562,2,0.163115515373647212982177734375,leaky_relu,normal
471,1753244594,7,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 149 --learning_rate 0.07543017915664240736 --batch_size 3226 --hidden_size 5694 --dropout 0.18096899474039673805 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.61192726995795965195,,1,,n1720,18586988,471_0,FAILED,SOBOL,149,0.07543017915664240735651446812,3226,5694,0.180968994740396738052368164062,3,0.611927269957959651947021484375,leaky_relu,normal
472,1753244587,15,1753244602,1753244609,7,python3 .tests/mnist/train --epochs 138 --learning_rate 0.01087905343286693118 --batch_size 555 --hidden_size 7195 --dropout 0.42924544773995876312 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.48938431777060031891,,1,,n1720,18586983,472_0,FAILED,SOBOL,138,0.010879053432866931175326818959,555,7195,0.42924544773995876312255859375,3,0.48938431777060031890869140625,leaky_relu,normal
473,1753244584,18,1753244602,1753244609,7,python3 .tests/mnist/train --epochs 32 --learning_rate 0.07435656235879287146 --batch_size 3367 --hidden_size 4025 --dropout 0.24156010337173938751 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.78196678496897220612,,1,,n1720,18586980,473_0,FAILED,SOBOL,32,0.074356562358792871458845752386,3367,4025,0.24156010337173938751220703125,2,0.78196678496897220611572265625,leaky_relu,normal
474,1753244594,7,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 60 --learning_rate 0.02830434430744498825 --batch_size 1566 --hidden_size 5379 --dropout 0.04663540562614798546 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.19810025673359632492,,1,,n1720,18586987,474_0,FAILED,SOBOL,60,0.028304344307444988249056194718,1566,5379,0.046635405626147985458374023438,1,0.198100256733596324920654296875,leaky_relu,normal
475,1753244594,36,1753244630,1753244636,6,python3 .tests/mnist/train --epochs 190 --learning_rate 0.09280623112106696493 --batch_size 2332 --hidden_size 1881 --dropout 0.35848485445603728294 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.53051764052361249924,,1,,n1720,18586989,475_0,FAILED,SOBOL,190,0.092806231121066964928623121978,2332,1881,0.358484854456037282943725585938,4,0.530517640523612499237060546875,leaky_relu,normal
476,1753244591,10,1753244601,1753244607,6,python3 .tests/mnist/train --epochs 158 --learning_rate 0.04478421494793147217 --batch_size 3794 --hidden_size 786 --dropout 0.271585061214864254 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.07786023896187543869,,1,,n1720,18586985,476_0,FAILED,SOBOL,158,0.044784214947931472172726330427,3794,786,0.271585061214864253997802734375,3,0.077860238961875438690185546875,leaky_relu,normal
477,1753244975,16,1753244991,1753244998,7,python3 .tests/mnist/train --epochs 94 --learning_rate 0.08413421428808942615 --batch_size 472 --hidden_size 4266 --dropout 0.0847700042650103569 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.65051399450749158859,,1,,n1720,18586992,477_0,FAILED,SOBOL,94,0.084134214288089426148076199752,472,4266,0.084770004265010356903076171875,2,0.650513994507491588592529296875,leaky_relu,normal
478,1753244992,28,1753245020,1753245027,7,python3 .tests/mnist/train --epochs 40 --learning_rate 0.0131121911693364377 --batch_size 2800 --hidden_size 3058 --dropout 0.13900487916544079781 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.35962478257715702057,,1,,n1720,18586994,478_0,FAILED,SOBOL,40,0.013112191169336437704395770254,2800,3058,0.139004879165440797805786132812,1,0.35962478257715702056884765625,leaky_relu,normal
479,1753244992,28,1753245020,1753245027,7,python3 .tests/mnist/train --epochs 128 --learning_rate 0.05182807081481442119 --batch_size 1522 --hidden_size 6210 --dropout 0.45166346104815602303 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.91197093762457370758,,1,,n1720,18586995,479_0,FAILED,SOBOL,128,0.051828070814814421185534598635,1522,6210,0.451663461048156023025512695312,4,0.91197093762457370758056640625,leaky_relu,normal
480,1753244995,25,1753245020,1753245027,7,python3 .tests/mnist/train --epochs 125 --learning_rate 0.04899084111005068409 --batch_size 248 --hidden_size 5870 --dropout 0.11221311381086707115 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.26455102022737264633,,1,,n1720,18586996,480_0,FAILED,SOBOL,125,0.048990841110050684092946937653,248,5870,0.112213113810867071151733398438,4,0.264551020227372646331787109375,leaky_relu,normal
481,1753244981,10,1753244991,1753244998,7,python3 .tests/mnist/train --epochs 43 --learning_rate 0.08463362281946465449 --batch_size 4081 --hidden_size 1357 --dropout 0.29901279276236891747 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.96434297319501638412,,1,,n1720,18586993,481_0,FAILED,SOBOL,43,0.0846336228194646544853441128,4081,1357,0.299012792762368917465209960938,1,0.964342973195016384124755859375,leaky_relu,normal
482,1753245346,6,1753245352,1753245358,6,python3 .tests/mnist/train --epochs 97 --learning_rate 0.0182711929844692339 --batch_size 1234 --hidden_size 7694 --dropout 0.47916725091636180878 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.04796440713107585907,,1,,n1720,18586999,482_0,FAILED,SOBOL,97,0.01827119298446923389978024943,1234,7694,0.47916725091636180877685546875,2,0.04796440713107585906982421875,leaky_relu,normal
483,1753245745,563,1753246308,1753246314,6,python3 .tests/mnist/train --epochs 155 --learning_rate 0.05445053430618718854 --batch_size 3023 --hidden_size 3493 --dropout 0.16649352945387363434 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.72317260317504405975,,1,,n1720,18587003,483_0,FAILED,SOBOL,155,0.054450534306187188537951016087,3023,3493,0.16649352945387363433837890625,3,0.72317260317504405975341796875,leaky_relu,normal
484,1753245755,553,1753246308,1753246314,6,python3 .tests/mnist/train --epochs 194 --learning_rate 0.0080382118562236423 --batch_size 3080 --hidden_size 2559 --dropout 0.2064877157099545002 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.1762610655277967453,,1,,n1720,18587004,484_0,FAILED,SOBOL,194,0.00803821185622364230149994313,3080,2559,0.206487715709954500198364257812,4,0.17626106552779674530029296875,leaky_relu,normal
485,1753245810,500,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 59 --learning_rate 0.06936944660590961542 --batch_size 779 --hidden_size 6742 --dropout 0.39418819965794682503 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.5956078898161649704,,1,,n1720,18587007,485_0,FAILED,SOBOL,59,0.06936944660590961542201426937,779,6742,0.394188199657946825027465820312,1,0.59560788981616497039794921875,leaky_relu,normal
486,1753245810,499,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 27 --learning_rate 0.02802330790683627004 --batch_size 2109 --hidden_size 295 --dropout 0.32347362395375967026 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.38625391479581594467,,1,,n1720,18587006,486_0,FAILED,SOBOL,27,0.028023307906836270042560954607,2109,295,0.323473623953759670257568359375,2,0.386253914795815944671630859375,leaky_relu,normal
487,1753245812,497,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 140 --learning_rate 0.08842772485120221904 --batch_size 1854 --hidden_size 4790 --dropout 0.01163955312222242355 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.84190717991441488266,,1,,n1720,18587008,487_0,FAILED,SOBOL,140,0.0884277248512022190363168761,1854,4790,0.011639553122222423553466796875,3,0.841907179914414882659912109375,leaky_relu,normal
488,1753245810,499,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 151 --learning_rate 0.02226800177730619765 --batch_size 2446 --hidden_size 6291 --dropout 0.25503845466300845146 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.21252745576202869415,,1,,n1720,18587005,488_0,FAILED,SOBOL,151,0.022268001777306197647154917263,2446,6291,0.255038454663008451461791992188,3,0.21252745576202869415283203125,leaky_relu,normal
489,1753245817,492,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 16 --learning_rate 0.06140465347161516707 --batch_size 1679 --hidden_size 2883 --dropout 0.06835691211745142937 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.51194004900753498077,,1,,n1720,18587012,489_0,FAILED,SOBOL,16,0.061404653471615167070751795109,1679,2883,0.068356912117451429367065429688,2,0.51194004900753498077392578125,leaky_relu,normal
490,1753245817,492,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 71 --learning_rate 0.04189039596300572765 --batch_size 3512 --hidden_size 4219 --dropout 0.15370898693799972534 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.47495720814913511276,,1,,n1720,18587013,490_0,FAILED,SOBOL,71,0.041890395963005727653083454243,3512,4219,0.153708986937999725341796875,1,0.474957208149135112762451171875,leaky_relu,normal
491,1753245819,490,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 182 --learning_rate 0.08078314000824467211 --batch_size 701 --hidden_size 995 --dropout 0.46650108322501182556 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.80054428707808256149,,1,,n1720,18587016,491_0,FAILED,SOBOL,182,0.08078314000824467211447910131,701,995,0.4665010832250118255615234375,4,0.800544287078082561492919921875,leaky_relu,normal
492,1753245815,495,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 167 --learning_rate 0.0320262680744752351 --batch_size 1413 --hidden_size 1928 --dropout 0.41088376054540276527 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.34690662752836942673,,1,,n1720,18587011,492_0,FAILED,SOBOL,167,0.032026268074475235103637515977,1413,1928,0.410883760545402765274047851562,3,0.346906627528369426727294921875,leaky_relu,normal
493,1753245813,496,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 85 --learning_rate 0.09532691408926621812 --batch_size 2691 --hidden_size 5170 --dropout 0.22305727237835526466 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.92835120391100645065,,1,,n1720,18587010,493_0,FAILED,SOBOL,85,0.095326914089266218121920815065,2691,5170,0.223057272378355264663696289062,2,0.928351203911006450653076171875,leaky_relu,normal
494,1753245819,491,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 55 --learning_rate 0.0008951380427926779 --batch_size 331 --hidden_size 3944 --dropout 0.05952300224453210831 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.09057854302227497101,,1,,n1720,18587015,494_0,FAILED,SOBOL,55,0.000895138042792677896507258506,331,3944,0.059523002244532108306884765625,1,0.09057854302227497100830078125,leaky_relu,normal
495,1753245818,491,1753246309,1753246315,6,python3 .tests/mnist/train --epochs 113 --learning_rate 0.06561037101363763335 --batch_size 3653 --hidden_size 7371 --dropout 0.37123130727559328079 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.63413357920944690704,,1,,n1720,18587014,495_0,FAILED,SOBOL,113,0.065610371013637633352821865174,3653,7371,0.371231307275593280792236328125,4,0.63413357920944690704345703125,leaky_relu,normal
496,1753246157,153,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 107 --learning_rate 0.00473501430070027724 --batch_size 1606 --hidden_size 17 --dropout 0.17550273379310965538 --activation leaky_relu --num_dense_layers 2 --init normal --weight_decay 0.97603630274534225464,,1,,n1720,18587018,496_0,FAILED,SOBOL,107,0.004735014300700277241340518941,1606,17,0.175502733793109655380249023438,2,0.976036302745342254638671875,leaky_relu,normal
497,1753246172,138,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 49 --learning_rate 0.068084436449036001 --batch_size 2373 --hidden_size 5031 --dropout 0.48767631268128752708 --activation leaky_relu --num_dense_layers 3 --init normal --weight_decay 0.29973126202821731567,,1,,n1720,18587019,497_0,FAILED,SOBOL,49,0.068084436449036001004486706734,2373,5031,0.487676312681287527084350585938,3,0.299731262028217315673828125,leaky_relu,normal
498,1753246218,92,1753246310,1753246316,6,python3 .tests/mnist/train --epochs 91 --learning_rate 0.03452770357364789294 --batch_size 644 --hidden_size 2293 --dropout 0.2929528113454580307 --activation leaky_relu --num_dense_layers 4 --init normal --weight_decay 0.71147890482097864151,,1,,n1720,18587020,498_0,FAILED,SOBOL,91,0.034527703573647892942855008869,644,2293,0.29295281134545803070068359375,4,0.711478904820978641510009765625,leaky_relu,normal
499,1753246342,32,1753246374,1753246380,6,python3 .tests/mnist/train --epochs 173 --learning_rate 0.09919415408428758352 --batch_size 3455 --hidden_size 6980 --dropout 0.10466104932129383087 --activation leaky_relu --num_dense_layers 1 --init normal --weight_decay 0.01278355810791254044,,1,,n1720,18587021,499_0,FAILED,SOBOL,173,0.099194154084287583517109965214,3455,6980,0.10466104932129383087158203125,1,0.012783558107912540435791015625,leaky_relu,normal</pre>
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<h1><img class='invert_icon' src='i/terminal.svg' style='height: 1em' /> Errors</h1>
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<pre id='simple_pre_tab_tab_progressbar_log'>2025-07-22 15:08:27: SOBOL, Started OmniOpt2 run...
2025-07-22 15:08:45: Sobol, getting new HP set #1/50
2025-07-22 15:08:58: Sobol, getting new HP set #2/50
2025-07-22 15:09:08: Sobol, getting new HP set #3/50
2025-07-22 15:09:22: Sobol, getting new HP set #4/50
2025-07-22 15:09:33: Sobol, getting new HP set #5/50
2025-07-22 15:09:46: Sobol, getting new HP set #6/50
2025-07-22 15:09:58: Sobol, getting new HP set #7/50
2025-07-22 15:10:09: Sobol, getting new HP set #8/50
2025-07-22 15:10:22: Sobol, getting new HP set #9/50
2025-07-22 15:10:35: Sobol, getting new HP set #10/50
2025-07-22 15:10:50: Sobol, getting new HP set #11/50
2025-07-22 15:11:00: Sobol, getting new HP set #12/50
2025-07-22 15:11:12: Sobol, getting new HP set #13/50
2025-07-22 15:11:25: Sobol, getting new HP set #14/50
2025-07-22 15:11:35: Sobol, getting new HP set #15/50
2025-07-22 15:11:46: Sobol, getting new HP set #16/50
2025-07-22 15:11:57: Sobol, getting new HP set #17/50
2025-07-22 15:12:07: Sobol, getting new HP set #18/50
2025-07-22 15:12:18: Sobol, getting new HP set #19/50
2025-07-22 15:12:29: Sobol, getting new HP set #20/50
2025-07-22 15:12:41: Sobol, getting new HP set #21/50
2025-07-22 15:12:52: Sobol, getting new HP set #22/50
2025-07-22 15:13:03: Sobol, getting new HP set #23/50
2025-07-22 15:13:13: Sobol, getting new HP set #24/50
2025-07-22 15:13:25: Sobol, getting new HP set #25/50
2025-07-22 15:13:33: Sobol, getting new HP set #26/50
2025-07-22 15:13:44: Sobol, getting new HP set #27/50
2025-07-22 15:13:55: Sobol, getting new HP set #28/50
2025-07-22 15:14:07: Sobol, getting new HP set #29/50
2025-07-22 15:14:17: Sobol, getting new HP set #30/50
2025-07-22 15:14:27: Sobol, getting new HP set #31/50
2025-07-22 15:14:37: Sobol, getting new HP set #32/50
2025-07-22 15:14:48: Sobol, getting new HP set #33/50
2025-07-22 15:14:56: Sobol, getting new HP set #34/50
2025-07-22 15:15:07: Sobol, getting new HP set #35/50
2025-07-22 15:15:20: Sobol, getting new HP set #36/50
2025-07-22 15:15:29: Sobol, getting new HP set #37/50
2025-07-22 15:15:43: Sobol, getting new HP set #38/50
2025-07-22 15:15:53: Sobol, getting new HP set #39/50
2025-07-22 15:16:04: Sobol, getting new HP set #40/50
2025-07-22 15:16:25: Sobol, getting new HP set #41/50
2025-07-22 15:16:35: Sobol, getting new HP set #42/50
2025-07-22 15:16:43: Sobol, getting new HP set #43/50
2025-07-22 15:16:52: Sobol, getting new HP set #44/50
2025-07-22 15:17:01: Sobol, getting new HP set #45/50
2025-07-22 15:17:14: Sobol, getting new HP set #46/50
2025-07-22 15:17:26: Sobol, getting new HP set #47/50
2025-07-22 15:17:35: Sobol, getting new HP set #48/50
2025-07-22 15:17:44: Sobol, getting new HP set #49/50
2025-07-22 15:17:54: Sobol, getting new HP set #50/50
2025-07-22 15:18:05: Sobol, requested 50 jobs, got 50, 11.23 s/job
2025-07-22 15:18:09: Sobol, eval #1/50 start
2025-07-22 15:18:16: Sobol, eval #2/50 start
2025-07-22 15:18:22: Sobol, eval #3/50 start
2025-07-22 15:18:26: Sobol, eval #4/50 start
2025-07-22 15:18:31: Sobol, eval #5/50 start
2025-07-22 15:18:35: Sobol, eval #6/50 start
2025-07-22 15:18:40: Sobol, eval #7/50 start
2025-07-22 15:18:45: Sobol, eval #8/50 start
2025-07-22 15:18:50: Sobol, eval #9/50 start
2025-07-22 15:18:54: Sobol, eval #10/50 start
2025-07-22 15:19:01: Sobol, eval #11/50 start
2025-07-22 15:19:07: Sobol, eval #12/50 start
2025-07-22 15:19:12: Sobol, eval #13/50 start
2025-07-22 15:19:17: Sobol, eval #14/50 start
2025-07-22 15:19:22: Sobol, eval #15/50 start
2025-07-22 15:19:27: Sobol, eval #16/50 start
2025-07-22 15:19:32: Sobol, eval #17/50 start
2025-07-22 15:19:38: Sobol, eval #18/50 start
2025-07-22 15:19:44: Sobol, eval #19/50 start
2025-07-22 15:19:49: Sobol, eval #20/50 start
2025-07-22 15:19:54: Sobol, eval #21/50 start
2025-07-22 15:20:00: Sobol, eval #22/50 start
2025-07-22 15:20:12: Sobol, eval #23/50 start
2025-07-22 15:20:19: Sobol, eval #24/50 start
2025-07-22 15:20:26: Sobol, eval #25/50 start
2025-07-22 15:20:33: Sobol, eval #26/50 start
2025-07-22 15:20:39: Sobol, eval #27/50 start
2025-07-22 15:20:45: Sobol, eval #28/50 start
2025-07-22 15:20:53: Sobol, eval #29/50 start
2025-07-22 15:20:59: Sobol, eval #30/50 start
2025-07-22 15:21:06: Sobol, eval #31/50 start
2025-07-22 15:21:13: Sobol, eval #32/50 start
2025-07-22 15:21:20: Sobol, eval #33/50 start
2025-07-22 15:21:29: Sobol, eval #34/50 start
2025-07-22 15:21:35: Sobol, eval #35/50 start
2025-07-22 15:21:43: Sobol, eval #36/50 start
2025-07-22 15:22:00: Sobol, eval #37/50 start
2025-07-22 15:22:12: Sobol, eval #38/50 start
2025-07-22 15:22:20: Sobol, eval #39/50 start
2025-07-22 15:22:30: Sobol, eval #40/50 start
2025-07-22 15:22:39: Sobol, eval #41/50 start
2025-07-22 15:22:48: Sobol, eval #42/50 start
2025-07-22 15:22:57: Sobol, eval #43/50 start
2025-07-22 15:23:05: Sobol, eval #44/50 start
2025-07-22 15:23:17: Sobol, eval #45/50 start
2025-07-22 15:23:26: Sobol, eval #46/50 start
2025-07-22 15:23:36: Sobol, eval #47/50 start
2025-07-22 15:23:47: Sobol, eval #48/50 start
2025-07-22 15:23:56: Sobol, eval #49/50 start
2025-07-22 15:24:06: Sobol, eval #50/50 start
2025-07-22 15:24:14: Sobol, starting new job
2025-07-22 15:24:14: Sobol, starting new job
2025-07-22 15:24:14: Sobol, starting new job
2025-07-22 15:24:14: Sobol, starting new job
2025-07-22 15:24:14: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:14: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:15: Sobol, starting new job
2025-07-22 15:24:16: Sobol, starting new job
2025-07-22 15:24:56: Sobol, unknown 9 = ∑9/50, started new job
2025-07-22 15:24:56: Sobol, unknown 9 = ∑9/50, started new job
2025-07-22 15:24:56: Sobol, unknown 9 = ∑9/50, started new job
2025-07-22 15:24:56: Sobol, unknown 9 = ∑9/50, started new job
2025-07-22 15:24:56: Sobol, unknown 11 = ∑11/50, started new job
2025-07-22 15:24:56: Sobol, unknown 11 = ∑11/50, started new job
2025-07-22 15:24:57: Sobol, unknown 11 = ∑11/50, started new job
2025-07-22 15:24:57: Sobol, unknown 12 = ∑12/50, started new job
2025-07-22 15:24:58: Sobol, unknown 14 = ∑14/50, started new job
2025-07-22 15:24:58: Sobol, unknown 14 = ∑14/50, started new job
2025-07-22 15:24:59: Sobol, unknown 16 = ∑16/50, started new job
2025-07-22 15:24:59: Sobol, unknown 16 = ∑16/50, started new job
2025-07-22 15:24:59: Sobol, unknown 16 = ∑16/50, started new job
2025-07-22 15:25:00: Sobol, unknown 16 = ∑16/50, started new job
2025-07-22 15:25:01: Sobol, pending 16 = ∑16/50, started new job
2025-07-22 15:25:01: Sobol, pending 16 = ∑16/50, started new job
2025-07-22 15:25:45: Sobol, completed/running 7/9 = ∑16/50, starting new job
2025-07-22 15:26:41: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:43: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:44: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:47: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:47: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:47: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:48: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:48: Sobol, completed 16 = ∑16/50, starting new job
2025-07-22 15:26:54: Sobol, completed/unknown 16/1 = ∑17/50, starting new job
2025-07-22 15:26:56: Sobol, completed/pending 16/1 = ∑17/50, started new job
2025-07-22 15:26:57: Sobol, completed/pending 16/1 = ∑17/50, starting new job
2025-07-22 15:26:57: Sobol, completed/pending 16/1 = ∑17/50, starting new job
2025-07-22 15:26:57: Sobol, completed/pending 16/1 = ∑17/50, starting new job
2025-07-22 15:26:57: Sobol, completed/pending 16/1 = ∑17/50, starting new job
2025-07-22 15:26:57: Sobol, completed/pending 16/1 = ∑17/50, starting new job
2025-07-22 15:26:58: Sobol, completed/pending 16/1 = ∑17/50, starting new job
2025-07-22 15:27:19: Sobol, completed/running/pending 16/1/1 = ∑18/50, started new job
2025-07-22 15:27:46: Sobol, completed/running/unknown 17/1/1 = ∑19/50, started new job
2025-07-22 15:27:59: Sobol, completed/pending/unknown 18/1/1 = ∑20/50, started new job
2025-07-22 15:28:10: Sobol, completed/pending 18/3 = ∑21/50, started new job
2025-07-22 15:28:11: Sobol, completed/pending/unknown 18/3/4 = ∑25/50, started new job
2025-07-22 15:28:12: Sobol, completed/running/pending 18/3/4 = ∑25/50, started new job
2025-07-22 15:28:13: Sobol, completed/running/pending/unknown 18/3/4/2 = ∑27/50, started new job
2025-07-22 15:28:14: Sobol, completed/running/pending/unknown 18/3/4/3 = ∑28/50, started new job
2025-07-22 15:28:15: Sobol, completed/running/pending/unknown 18/3/4/6 = ∑31/50, started new job
2025-07-22 15:28:15: Sobol, completed/running/pending/unknown 18/3/4/7 = ∑32/50, started new job
2025-07-22 15:28:16: Sobol, completed/running/pending/unknown 18/3/4/7 = ∑32/50, started new job
2025-07-22 15:28:17: Sobol, completed/running/pending 18/7/7 = ∑32/50, started new job
2025-07-22 15:28:17: Sobol, completed/running/pending 18/7/7 = ∑32/50, started new job
2025-07-22 15:28:18: Sobol, completed/running/pending 18/7/7 = ∑32/50, started new job
2025-07-22 15:28:18: Sobol, completed/running/pending 18/7/7 = ∑32/50, started new job
2025-07-22 15:28:20: Sobol, completed/running/pending 18/7/7 = ∑32/50, starting new job
2025-07-22 15:28:23: Sobol, completed/running/pending 18/7/7 = ∑32/50, starting new job
2025-07-22 15:28:26: Sobol, completed/running/pending 18/7/7 = ∑32/50, starting new job
2025-07-22 15:29:39: Sobol, completed 32 = ∑32/50, starting new job
2025-07-22 15:29:46: Sobol, completed 32 = ∑32/50, starting new job
2025-07-22 15:29:51: Sobol, completed 32 = ∑32/50, starting new job
2025-07-22 15:30:09: Sobol, completed/unknown 32/3 = ∑35/50, started new job
2025-07-22 15:30:09: Sobol, completed/unknown 32/3 = ∑35/50, started new job
2025-07-22 15:30:10: Sobol, completed/unknown 32/3 = ∑35/50, started new job
2025-07-22 15:30:12: Sobol, completed/unknown 32/3 = ∑35/50, starting new job
2025-07-22 15:30:13: Sobol, completed/pending 32/3 = ∑35/50, starting new job
2025-07-22 15:30:13: Sobol, completed/pending 32/3 = ∑35/50, starting new job
2025-07-22 15:30:14: Sobol, completed/pending 32/3 = ∑35/50, starting new job
2025-07-22 15:30:14: Sobol, completed/pending 32/3 = ∑35/50, starting new job
2025-07-22 15:30:14: Sobol, completed/pending 32/3 = ∑35/50, starting new job
2025-07-22 15:30:15: Sobol, completed/pending 32/3 = ∑35/50, starting new job
2025-07-22 15:30:55: Sobol, completed/unknown 35/1 = ∑36/50, started new job
2025-07-22 15:30:55: Sobol, completed/unknown 35/1 = ∑36/50, starting new job
2025-07-22 15:30:55: Sobol, completed/unknown 35/1 = ∑36/50, starting new job
2025-07-22 15:30:56: Sobol, completed/unknown 35/1 = ∑36/50, starting new job
2025-07-22 15:31:16: Sobol, completed/running/unknown 35/1/1 = ∑37/50, started new job
2025-07-22 15:31:25: Sobol, completed/pending/unknown 36/1/1 = ∑38/50, started new job
2025-07-22 15:32:00: Sobol, completed/unknown 38/7 = ∑45/50, started new job
2025-07-22 15:32:00: Sobol, completed/unknown 38/7 = ∑45/50, started new job
2025-07-22 15:32:01: Sobol, completed/unknown 38/7 = ∑45/50, started new job
2025-07-22 15:32:02: Sobol, completed/unknown 38/7 = ∑45/50, started new job
2025-07-22 15:32:03: Sobol, completed/pending 38/7 = ∑45/50, starting new job
2025-07-22 15:32:03: Sobol, completed/pending 38/7 = ∑45/50, started new job
2025-07-22 15:32:03: Sobol, completed/pending 38/7 = ∑45/50, started new job
2025-07-22 15:32:03: Sobol, completed/pending 38/7 = ∑45/50, started new job
2025-07-22 15:32:19: Sobol, completed/running/unknown 38/7/3 = ∑48/50, started new job
2025-07-22 15:32:19: Sobol, completed/running/pending 38/7/3 = ∑48/50, started new job
2025-07-22 15:32:19: Sobol, completed/running/pending 38/7/3 = ∑48/50, starting new job
2025-07-22 15:32:19: Sobol, completed/running/pending 38/7/3 = ∑48/50, started new job
2025-07-22 15:34:15: Sobol, completed/unknown 48/1 = ∑49/50, started new job
2025-07-22 15:34:21: Sobol, completed/pending/unknown 48/1/1 = ∑50/50, started new job
2025-07-22 15:35:40: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:40: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:40: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:40: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:40: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:41: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:42: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:42: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:42: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:42: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:40: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:44: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:43: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:44: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:44: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:46: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:45: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:46: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:46: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:47: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:48: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:48: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:35:49: Sobol, completed 50 = ∑50/50, job_failed
2025-07-22 15:39:54: Sobol, failed: 6 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 42 = ∑42/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:55: Sobol, failed: 8 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:39:56: Sobol, failed: 9 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 15:40:08: Sobol, failed: 13 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 15:40:08: Sobol, failed: 13 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 15:40:09: Sobol, failed: 13 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 15:40:10: Sobol, failed: 13 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-22 15:40:19: Sobol, failed: 16 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 24 = ∑24/50, job_failed
2025-07-22 15:40:19: Sobol, failed: 22 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 19 = ∑19/50, job_failed
2025-07-22 15:40:21: Sobol, failed: 32 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 15:40:21: Sobol, failed: 32 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 15:40:22: Sobol, failed: 32 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 15:42:39: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-22 15:42:57: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-22 15:43:25: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-22 15:43:53: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-22 15:44:25: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-22 15:44:55: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-22 15:45:28: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-22 15:46:00: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-22 15:46:32: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-22 15:47:04: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-22 15:47:36: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-22 15:48:08: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-22 15:48:40: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-22 15:49:08: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-22 15:49:38: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-22 15:50:01: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-22 15:50:27: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-22 15:50:49: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-22 15:51:10: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-22 15:51:33: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-22 15:51:54: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-22 15:52:21: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-22 15:52:52: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-22 15:53:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-22 15:53:46: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-22 15:54:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-22 15:54:37: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-22 15:55:02: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-22 15:55:26: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-22 15:55:53: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-22 15:56:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-22 15:56:42: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-22 15:57:05: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-22 15:57:29: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-22 15:57:53: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-22 15:58:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-22 15:58:39: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-22 15:59:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-22 15:59:26: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-22 15:59:49: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-22 16:00:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-22 16:00:33: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-22 16:00:57: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-22 16:01:23: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-22 16:01:51: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-22 16:02:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-22 16:02:46: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-22 16:03:14: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-22 16:03:41: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-22 16:04:06: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-22 16:04:32: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-22 16:05:00: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 26.46 s/job
2025-07-22 16:05:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-22 16:05:26: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-22 16:05:40: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-22 16:05:54: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-22 16:06:08: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-22 16:06:26: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-22 16:06:39: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-22 16:06:55: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-22 16:07:08: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-22 16:07:21: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-22 16:07:35: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-22 16:07:49: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-22 16:08:02: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-22 16:08:16: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-22 16:08:51: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-22 16:09:04: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-22 16:09:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-22 16:09:33: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-22 16:09:58: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-22 16:10:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-22 16:10:32: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-22 16:10:45: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-22 16:10:59: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-22 16:11:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-22 16:11:25: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-22 16:11:38: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-22 16:11:51: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-22 16:12:04: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-22 16:12:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-22 16:12:31: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-22 16:12:47: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-22 16:13:00: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-22 16:13:16: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-22 16:13:29: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-22 16:13:42: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-22 16:13:55: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-22 16:14:08: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-22 16:14:21: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-22 16:14:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-22 16:14:48: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-22 16:15:02: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-22 16:15:14: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-22 16:15:26: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-22 16:15:39: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-22 16:15:52: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-22 16:16:06: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-22 16:16:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-22 16:16:31: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-22 16:16:44: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-22 16:17:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-22 16:17:33: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:33: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:34: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:35: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:35: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:35: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:17:35: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 16:19:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-22 16:19:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-22 16:19:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 9 = ∑9/50, started new job
2025-07-22 16:19:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 10 = ∑10/50, started new job
2025-07-22 16:19:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 11 = ∑11/50, started new job
2025-07-22 16:19:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 11 = ∑11/50, started new job
2025-07-22 16:19:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 11 = ∑11/50, started new job
2025-07-22 16:19:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 11 = ∑11/50, started new job
2025-07-22 16:19:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 11 = ∑11/50, started new job
2025-07-22 16:19:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 11 = ∑11/50, started new job
2025-07-22 16:19:14: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 12/2 = ∑14/50, started new job
2025-07-22 16:19:15: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 12/3 = ∑15/50, started new job
2025-07-22 16:19:15: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 12/4 = ∑16/50, started new job
2025-07-22 16:19:16: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 12/4 = ∑16/50, started new job
2025-07-22 16:19:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 10/2/4 = ∑16/50, started new job
2025-07-22 16:19:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 10/2/4 = ∑16/50, started new job
2025-07-22 16:20:58: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:20:58: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:20:58: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:20:59: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:20:59: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:10: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:12: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:21:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:22:43: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 16:22:46: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/1 = ∑18/50, started new job
2025-07-22 16:22:48: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/1 = ∑18/50, started new job
2025-07-22 16:22:51: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/1/3 = ∑21/50, started new job
2025-07-22 16:22:53: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/1/3 = ∑21/50, started new job
2025-07-22 16:22:53: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/1/3 = ∑21/50, started new job
2025-07-22 16:22:58: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/4/2 = ∑23/50, started new job
2025-07-22 16:22:58: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/4/2 = ∑23/50, started new job
2025-07-22 16:23:02: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/6/4 = ∑27/50, started new job
2025-07-22 16:23:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/6/4 = ∑27/50, started new job
2025-07-22 16:23:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/6/4 = ∑27/50, started new job
2025-07-22 16:23:04: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/6/4 = ∑27/50, started new job
2025-07-22 16:23:06: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/10/4 = ∑31/50, started new job
2025-07-22 16:23:06: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/10/4 = ∑31/50, started new job
2025-07-22 16:23:07: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/10/4 = ∑31/50, started new job
2025-07-22 16:23:07: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 17/10/4 = ∑31/50, started new job
2025-07-22 16:24:43: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 31/1 = ∑32/50, started new job
2025-07-22 16:24:48: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:24:57: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:24:59: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:24:59: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:05: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:06: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:09: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:11: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 31/1 = ∑32/50, starting new job
2025-07-22 16:25:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 16:25:14: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 16:26:51: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 16:26:54: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/1 = ∑33/50, started new job
2025-07-22 16:26:55: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/1 = ∑33/50, starting new job
2025-07-22 16:27:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/1/2 = ∑35/50, started new job
2025-07-22 16:27:03: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/1/2 = ∑35/50, starting new job
2025-07-22 16:27:04: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/1/2 = ∑35/50, starting new job
2025-07-22 16:27:04: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/1/2 = ∑35/50, started new job
2025-07-22 16:27:07: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/1/3 = ∑36/50, started new job
2025-07-22 16:27:10: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/4/1 = ∑37/50, started new job
2025-07-22 16:27:13: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/5/1 = ∑38/50, started new job
2025-07-22 16:27:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/6/3 = ∑41/50, started new job
2025-07-22 16:27:20: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/6/5 = ∑43/50, started new job
2025-07-22 16:27:20: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/6/5 = ∑43/50, started new job
2025-07-22 16:27:21: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 32/6/6 = ∑44/50, started new job
2025-07-22 16:27:22: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 32/6/6 = ∑44/50, started new job
2025-07-22 16:27:23: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 32/6/6 = ∑44/50, started new job
2025-07-22 16:29:02: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 44/1 = ∑45/50, started new job
2025-07-22 16:29:08: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 44/1/1 = ∑46/50, started new job
2025-07-22 16:29:15: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 44/2/2 = ∑48/50, started new job
2025-07-22 16:29:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 44/4 = ∑48/50, started new job
2025-07-22 16:29:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 44/4 = ∑48/50, starting new job
2025-07-22 16:29:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 44/4 = ∑48/50, starting new job
2025-07-22 16:30:40: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/2 = ∑50/50, started new job
2025-07-22 16:30:41: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/2 = ∑50/50, started new job
2025-07-22 16:31:16: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:16: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:17: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:18: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:19: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:20: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:20: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:20: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:20: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:21: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:31:21: Sobol, failed: 50 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 16:35:47: Sobol, failed: 51 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 49 = ∑49/50, job_failed
2025-07-22 16:35:51: Sobol, failed: 53 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-22 16:35:51: Sobol, failed: 53 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 46 = ∑46/50, job_failed
2025-07-22 16:35:52: Sobol, failed: 55 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-22 16:35:53: Sobol, failed: 57 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 42 = ∑42/50, job_failed
2025-07-22 16:35:53: Sobol, failed: 58 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 42 = ∑42/50, job_failed
2025-07-22 16:35:54: Sobol, failed: 58 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 42 = ∑42/50, job_failed
2025-07-22 16:35:54: Sobol, failed: 58 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 42 = ∑42/50, job_failed
2025-07-22 16:36:08: Sobol, failed: 59 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 16:36:11: Sobol, failed: 63 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 35 = ∑35/50, job_failed
2025-07-22 16:36:12: Sobol, failed: 66 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-22 16:36:13: Sobol, failed: 66 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-22 16:36:13: Sobol, failed: 66 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-22 16:36:17: Sobol, failed: 67 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 30 = ∑30/50, job_failed
2025-07-22 16:36:19: Sobol, failed: 68 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 27 = ∑27/50, job_failed
2025-07-22 16:36:19: Sobol, failed: 68 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 25 = ∑25/50, job_failed
2025-07-22 16:36:19: Sobol, failed: 68 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 27 = ∑27/50, job_failed
2025-07-22 16:36:20: Sobol, failed: 80 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 16:38:58: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-22 16:39:23: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-22 16:39:52: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-22 16:40:23: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-22 16:40:53: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-22 16:41:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-22 16:41:54: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-22 16:42:25: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-22 16:42:56: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-22 16:43:26: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-22 16:43:56: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-22 16:44:27: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-22 16:44:57: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-22 16:45:28: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-22 16:46:02: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-22 16:46:28: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-22 16:46:55: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-22 16:47:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-22 16:47:55: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-22 16:48:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-22 16:48:59: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-22 16:49:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-22 16:50:02: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-22 16:50:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-22 16:50:57: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-22 16:51:23: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-22 16:51:52: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-22 16:52:20: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-22 16:52:53: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-22 16:53:22: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-22 16:54:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-22 16:54:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-22 16:55:02: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-22 16:55:33: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-22 16:56:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-22 16:56:33: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-22 16:57:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-22 16:57:33: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-22 16:58:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-22 16:58:35: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-22 16:59:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-22 16:59:37: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-22 17:00:07: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-22 17:00:37: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-22 17:01:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-22 17:01:41: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-22 17:02:12: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-22 17:02:44: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-22 17:03:16: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-22 17:03:46: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-22 17:04:28: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-22 17:04:58: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 30.71 s/job
2025-07-22 17:05:13: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-22 17:05:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-22 17:05:47: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-22 17:06:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-22 17:06:19: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-22 17:06:36: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-22 17:06:52: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-22 17:07:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-22 17:07:23: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-22 17:07:39: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-22 17:07:56: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-22 17:08:14: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-22 17:08:30: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-22 17:08:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-22 17:09:01: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-22 17:09:17: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-22 17:09:33: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-22 17:09:49: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-22 17:10:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-22 17:10:21: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-22 17:10:38: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-22 17:10:54: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-22 17:11:10: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-22 17:11:25: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-22 17:11:41: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-22 17:11:56: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-22 17:12:13: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-22 17:12:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-22 17:12:44: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-22 17:13:00: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-22 17:13:22: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-22 17:13:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-22 17:14:01: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-22 17:14:18: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-22 17:14:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-22 17:14:52: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-22 17:15:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-22 17:15:25: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-22 17:15:46: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-22 17:16:02: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-22 17:16:19: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-22 17:16:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-22 17:16:56: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-22 17:17:12: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-22 17:17:27: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-22 17:17:43: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-22 17:18:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-22 17:18:20: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-22 17:18:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-22 17:18:50: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-22 17:19:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:19:11: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 17:21:23: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/4 = ∑7/50, started new job
2025-07-22 17:21:23: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/4 = ∑7/50, started new job
2025-07-22 17:21:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/5 = ∑8/50, started new job
2025-07-22 17:21:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/5 = ∑8/50, started new job
2025-07-22 17:21:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/5 = ∑8/50, started new job
2025-07-22 17:21:24: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/5 = ∑8/50, started new job
2025-07-22 17:21:25: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/5 = ∑8/50, started new job
2025-07-22 17:21:25: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/5 = ∑8/50, started new job
2025-07-22 17:21:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 9 = ∑9/50, started new job
2025-07-22 17:21:32: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-22 17:21:33: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-22 17:21:33: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-22 17:21:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-22 17:21:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-22 17:21:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-22 17:21:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-22 17:23:53: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:23:53: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:23:53: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:23:55: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:23:55: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:23:59: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:24:01: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:24:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:24:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:24:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:24:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:25:46: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 17:26:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/1 = ∑17/50, started new job
2025-07-22 17:26:30: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/1 = ∑17/50, starting new job
2025-07-22 17:26:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/2/1 = ∑19/50, started new job
2025-07-22 17:26:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/2/3 = ∑21/50, started new job
2025-07-22 17:26:34: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/2/3 = ∑21/50, started new job
2025-07-22 17:26:35: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/2/3 = ∑21/50, started new job
2025-07-22 17:26:37: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/2/3 = ∑21/50, starting new job
2025-07-22 17:26:38: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/2/4 = ∑22/50, started new job
2025-07-22 17:26:42: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-22 17:26:43: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 16/7 = ∑23/50, starting new job
2025-07-22 17:26:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-22 17:26:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-22 17:26:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/2 = ∑25/50, starting new job
2025-07-22 17:26:46: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-22 17:26:46: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-22 17:28:19: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 27/1 = ∑28/50, started new job
2025-07-22 17:29:00: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 27/1/1 = ∑29/50, started new job
2025-07-22 17:29:15: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 28/1/1 = ∑30/50, started new job
2025-07-22 17:29:16: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 28/2 = ∑30/50, starting new job
2025-07-22 17:29:16: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 28/2 = ∑30/50, starting new job
2025-07-22 17:29:22: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 28/2/2 = ∑32/50, started new job
2025-07-22 17:29:25: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, started new job
2025-07-22 17:29:27: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, starting new job
2025-07-22 17:29:27: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, starting new job
2025-07-22 17:29:27: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, starting new job
2025-07-22 17:29:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, starting new job
2025-07-22 17:29:29: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, starting new job
2025-07-22 17:29:32: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 28/2/2 = ∑32/50, starting new job
2025-07-22 17:31:43: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 17:31:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 17:31:59: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 17:32:00: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 17:32:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/1 = ∑33/50, started new job
2025-07-22 17:32:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, starting new job
2025-07-22 17:32:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, started new job
2025-07-22 17:32:13: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/2/1 = ∑35/50, starting new job
2025-07-22 17:32:15: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/2 = ∑37/50, started new job
2025-07-22 17:32:15: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/2 = ∑37/50, started new job
2025-07-22 17:32:16: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/3 = ∑38/50, started new job
2025-07-22 17:32:19: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/5 = ∑40/50, started new job
2025-07-22 17:32:19: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/4 = ∑39/50, started new job
2025-07-22 17:32:19: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/5 = ∑40/50, starting new job
2025-07-22 17:32:20: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/3/5 = ∑40/50, started new job
2025-07-22 17:33:58: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, starting new job
2025-07-22 17:34:30: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 40/2 = ∑42/50, started new job
2025-07-22 17:34:30: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 40/2 = ∑42/50, started new job
2025-07-22 17:34:42: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 40/2/1 = ∑43/50, started new job
2025-07-22 17:34:45: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 40/3/1 = ∑44/50, started new job
2025-07-22 17:34:50: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 40/4/1 = ∑45/50, started new job
2025-07-22 17:34:51: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 40/4/1 = ∑45/50, starting new job
2025-07-22 17:35:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 44/1/1 = ∑46/50, started new job
2025-07-22 17:35:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 45/1/1 = ∑47/50, started new job
2025-07-22 17:35:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 45/1/1 = ∑47/50, starting new job
2025-07-22 17:36:49: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 47/1 = ∑48/50, started new job
2025-07-22 17:37:38: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/1 = ∑49/50, started new job
2025-07-22 17:37:56: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 48/1/1 = ∑50/50, started new job
2025-07-22 17:39:02: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:02: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:03: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:04: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:05: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:06: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:07: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:07: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:07: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:08: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:09: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:10: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:39:10: Sobol, failed: 100 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 17:44:46: Sobol, failed: 103 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-22 17:44:47: Sobol, failed: 103 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-22 17:44:47: Sobol, failed: 103 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-22 17:44:49: Sobol, failed: 106 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 44 = ∑44/50, job_failed
2025-07-22 17:44:49: Sobol, failed: 106 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 44 = ∑44/50, job_failed
2025-07-22 17:44:49: Sobol, failed: 106 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 44 = ∑44/50, job_failed
2025-07-22 17:44:50: Sobol, failed: 110 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-22 17:44:51: Sobol, failed: 110 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-22 17:44:51: Sobol, failed: 110 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-22 17:44:51: Sobol, failed: 110 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-22 17:44:55: Sobol, failed: 111 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 39 = ∑39/50, job_failed
2025-07-22 17:44:58: Sobol, failed: 112 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-22 17:45:00: Sobol, failed: 113 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 17:45:03: Sobol, failed: 114 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-22 17:45:07: Sobol, failed: 117 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-22 17:45:08: Sobol, failed: 117 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, job_failed
2025-07-22 17:45:08: Sobol, failed: 117 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, job_failed
2025-07-22 17:45:13: Sobol, failed: 132 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 17:48:33: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-22 17:48:58: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-22 17:49:34: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-22 17:50:10: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-22 17:50:49: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-22 17:51:25: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-22 17:52:01: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-22 17:52:52: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-22 17:53:28: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-22 17:54:03: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-22 17:54:45: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-22 17:55:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-22 17:55:55: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-22 17:56:31: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-22 17:57:05: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-22 17:57:42: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-22 17:58:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-22 17:58:45: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-22 17:59:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-22 17:59:53: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-22 18:00:36: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-22 18:01:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-22 18:01:44: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-22 18:02:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-22 18:02:55: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-22 18:03:29: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-22 18:04:03: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-22 18:04:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-22 18:05:09: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-22 18:05:51: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-22 18:06:27: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-22 18:07:02: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-22 18:07:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-22 18:08:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-22 18:08:46: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-22 18:09:22: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-22 18:09:56: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-22 18:10:31: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-22 18:11:04: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-22 18:11:38: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-22 18:12:13: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-22 18:12:52: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-22 18:13:27: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-22 18:14:01: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-22 18:14:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-22 18:15:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-22 18:15:46: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-22 18:16:32: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-22 18:17:05: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-22 18:17:38: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-22 18:18:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-22 18:18:56: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 35.98 s/job
2025-07-22 18:19:10: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-22 18:19:25: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-22 18:19:41: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-22 18:19:56: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-22 18:20:12: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-22 18:20:27: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-22 18:20:43: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-22 18:20:59: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-22 18:21:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-22 18:21:31: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-22 18:21:46: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-22 18:22:01: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-22 18:22:17: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-22 18:22:32: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-22 18:22:47: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-22 18:23:04: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-22 18:23:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-22 18:23:35: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-22 18:23:51: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-22 18:24:07: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-22 18:24:22: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-22 18:24:38: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-22 18:24:53: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-22 18:25:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-22 18:25:24: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-22 18:25:40: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-22 18:25:55: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-22 18:26:13: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-22 18:26:29: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-22 18:26:47: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-22 18:27:02: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-22 18:27:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-22 18:27:33: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-22 18:27:50: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-22 18:28:05: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-22 18:28:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-22 18:28:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-22 18:28:52: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-22 18:29:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-22 18:29:25: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-22 18:29:42: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-22 18:29:58: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-22 18:30:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-22 18:30:29: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-22 18:30:45: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-22 18:31:00: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-22 18:31:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-22 18:31:32: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-22 18:31:47: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-22 18:32:03: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-22 18:32:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:32:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 18:35:07: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 7 = ∑7/50, started new job
2025-07-22 18:35:07: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 7 = ∑7/50, started new job
2025-07-22 18:35:07: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 18:35:07: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 18:35:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 18:35:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 18:35:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 18:35:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 18:35:15: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/7 = ∑15/50, started new job
2025-07-22 18:35:15: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/7 = ∑15/50, started new job
2025-07-22 18:35:15: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/7 = ∑15/50, started new job
2025-07-22 18:35:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/8 = ∑16/50, started new job
2025-07-22 18:35:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/8 = ∑16/50, started new job
2025-07-22 18:35:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/8 = ∑16/50, started new job
2025-07-22 18:35:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/8 = ∑16/50, started new job
2025-07-22 18:35:17: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/8 = ∑16/50, started new job
2025-07-22 18:38:08: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:09: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:10: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:10: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:12: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:12: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:13: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:20: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:21: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:22: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:38:22: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:41:15: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 18:41:27: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/1/1 = ∑18/50, started new job
2025-07-22 18:41:28: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/1/4 = ∑21/50, started new job
2025-07-22 18:41:29: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/1/4 = ∑21/50, started new job
2025-07-22 18:41:29: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/1/4 = ∑21/50, started new job
2025-07-22 18:41:29: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/1/4 = ∑21/50, started new job
2025-07-22 18:41:33: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/3 = ∑25/50, started new job
2025-07-22 18:41:33: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/4 = ∑26/50, started new job
2025-07-22 18:41:34: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/5 = ∑27/50, started new job
2025-07-22 18:41:34: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/5 = ∑27/50, started new job
2025-07-22 18:41:34: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/6 = ∑28/50, started new job
2025-07-22 18:41:35: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/6 = ∑28/50, started new job
2025-07-22 18:41:36: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/7 = ∑29/50, started new job
2025-07-22 18:41:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/5/9 = ∑31/50, started new job
2025-07-22 18:41:38: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/13/1 = ∑31/50, started new job
2025-07-22 18:41:39: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/1/13/1 = ∑31/50, started new job
2025-07-22 18:44:38: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/15/1 = ∑32/50, started new job
2025-07-22 18:45:10: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:11: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:12: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:12: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:13: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:13: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:14: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:15: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:45:16: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:46:47: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/16 = ∑32/50, starting new job
2025-07-22 18:48:42: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/16/1 = ∑33/50, started new job
2025-07-22 18:48:44: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/16/2 = ∑34/50, started new job
2025-07-22 18:48:47: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/2/3 = ∑37/50, started new job
2025-07-22 18:48:48: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/2/3 = ∑37/50, started new job
2025-07-22 18:48:49: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/2/4 = ∑38/50, started new job
2025-07-22 18:48:49: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/5/3 = ∑40/50, started new job
2025-07-22 18:48:50: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/5/3 = ∑40/50, started new job
2025-07-22 18:48:51: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/5/3 = ∑40/50, started new job
2025-07-22 18:48:53: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/5/4 = ∑41/50, started new job
2025-07-22 18:48:55: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/10/3 = ∑45/50, started new job
2025-07-22 18:48:55: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/10/5 = ∑47/50, started new job
2025-07-22 18:48:56: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/10/5 = ∑47/50, started new job
2025-07-22 18:48:56: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/10/5 = ∑47/50, started new job
2025-07-22 18:48:56: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/10/5 = ∑47/50, started new job
2025-07-22 18:48:57: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/16/10/5 = ∑47/50, started new job
2025-07-22 18:50:12: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/31/1 = ∑48/50, started new job
2025-07-22 18:52:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/32 = ∑48/50, starting new job
2025-07-22 18:52:37: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/32 = ∑48/50, starting new job
2025-07-22 18:53:48: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 16/32/1 = ∑49/50, started new job
2025-07-22 18:53:49: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/32/1/1 = ∑50/50, started new job
2025-07-22 18:54:17: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:17: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:18: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:54:19: Sobol, failed: 150 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 16/34 = ∑50/50, job_failed
2025-07-22 18:58:21: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, finishing jobs, finished 16 jobs
2025-07-22 18:58:41: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, waiting for 34 jobs
2025-07-22 18:59:05: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, waiting for 34 jobs
2025-07-22 18:59:31: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, waiting for 34 jobs
2025-07-22 18:59:55: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, waiting for 34 jobs
2025-07-22 19:00:20: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, waiting for 34 jobs
2025-07-22 19:00:47: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:47: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:48: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:48: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:49: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:50: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:49: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:50: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:50: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:50: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:51: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:51: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:51: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:51: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:51: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:52: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:51: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:53: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:53: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:53: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:53: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:52: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:54: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:54: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:54: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:55: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:55: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:56: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:56: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:56: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:57: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:00:57: Sobol, failed: 166 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running 34 = ∑34/50, job_failed
2025-07-22 19:08:08: Sobol, failed: 168 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, job_failed
2025-07-22 19:08:09: Sobol, failed: 168 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, job_failed
2025-07-22 19:09:00: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), waiting for 34 jobs, finished 34 jobs
2025-07-22 19:09:23: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-22 19:10:01: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-22 19:10:38: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-22 19:11:16: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-22 19:11:53: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-22 19:12:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-22 19:13:15: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-22 19:13:57: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-22 19:14:39: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-22 19:15:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-22 19:16:01: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-22 19:16:43: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-22 19:17:22: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-22 19:18:01: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-22 19:18:41: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-22 19:19:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-22 19:20:01: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-22 19:20:42: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-22 19:21:23: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-22 19:22:03: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-22 19:22:42: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-22 19:23:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-22 19:24:01: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-22 19:24:42: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-22 19:25:23: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-22 19:26:06: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-22 19:26:48: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-22 19:27:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-22 19:28:11: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-22 19:28:54: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-22 19:29:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-22 19:30:13: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-22 19:30:54: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-22 19:31:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-22 19:32:11: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-22 19:32:49: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-22 19:33:25: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-22 19:34:04: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-22 19:34:41: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-22 19:35:19: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-22 19:35:57: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-22 19:36:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-22 19:37:12: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-22 19:37:49: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-22 19:38:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-22 19:39:05: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-22 19:39:43: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-22 19:40:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-22 19:40:59: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-22 19:41:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-22 19:42:14: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 39.46 s/job
2025-07-22 19:42:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-22 19:42:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-22 19:43:10: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-22 19:43:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-22 19:43:49: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-22 19:44:09: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-22 19:44:28: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-22 19:44:48: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-22 19:45:07: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-22 19:45:27: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-22 19:45:47: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-22 19:46:06: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-22 19:46:25: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-22 19:46:44: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-22 19:47:03: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-22 19:47:23: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-22 19:47:42: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-22 19:48:01: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-22 19:48:20: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-22 19:48:41: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-22 19:49:00: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-22 19:49:19: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-22 19:49:39: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-22 19:49:58: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-22 19:50:18: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-22 19:50:37: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-22 19:50:57: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-22 19:51:17: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-22 19:51:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-22 19:51:55: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-22 19:52:14: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-22 19:52:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-22 19:52:54: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-22 19:53:14: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-22 19:53:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-22 19:53:53: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-22 19:54:12: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-22 19:54:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-22 19:54:54: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-22 19:55:13: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-22 19:55:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-22 19:55:53: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-22 19:56:12: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-22 19:56:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-22 19:56:52: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-22 19:57:12: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-22 19:57:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-22 19:57:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-22 19:58:11: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-22 19:58:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-22 19:58:50: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:50: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:50: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:50: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:50: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:52: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 19:58:52: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 20:02:24: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 5 = ∑5/50, started new job
2025-07-22 20:02:25: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-22 20:02:25: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 9 = ∑9/50, started new job
2025-07-22 20:02:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 10 = ∑10/50, started new job
2025-07-22 20:02:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-22 20:02:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 9 = ∑9/50, started new job
2025-07-22 20:02:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 10 = ∑10/50, started new job
2025-07-22 20:02:27: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 10 = ∑10/50, started new job
2025-07-22 20:02:27: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 10/1 = ∑11/50, started new job
2025-07-22 20:02:28: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 10/1 = ∑11/50, started new job
2025-07-22 20:02:28: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 10/1 = ∑11/50, started new job
2025-07-22 20:02:31: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 10/6 = ∑16/50, started new job
2025-07-22 20:02:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 10/6 = ∑16/50, started new job
2025-07-22 20:02:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-22 20:02:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-22 20:02:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-22 20:06:10: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:10: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:11: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:19: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:19: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:28: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:29: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:29: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:31: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:31: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:31: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:06:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:09:38: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 20:09:45: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-22 20:09:46: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-22 20:09:47: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-22 20:10:06: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 17/2/2 = ∑21/50, started new job
2025-07-22 20:10:07: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 17/2/2 = ∑21/50, started new job
2025-07-22 20:10:17: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/2/1 = ∑22/50, starting new job
2025-07-22 20:10:17: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/2/2 = ∑23/50, started new job
2025-07-22 20:10:18: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/2/3 = ∑24/50, started new job
2025-07-22 20:10:19: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/2/4 = ∑25/50, started new job
2025-07-22 20:10:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/2/5 = ∑26/50, started new job
2025-07-22 20:10:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 19/7 = ∑26/50, starting new job
2025-07-22 20:10:22: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/7/1 = ∑27/50, started new job
2025-07-22 20:10:23: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/7/3 = ∑29/50, started new job
2025-07-22 20:10:24: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 19/7/3 = ∑29/50, started new job
2025-07-22 20:10:25: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 19/7/1/2 = ∑29/50, started new job
2025-07-22 20:13:22: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 29/1 = ∑30/50, started new job
2025-07-22 20:13:49: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 30 = ∑30/50, starting new job
2025-07-22 20:13:49: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 30 = ∑30/50, starting new job
2025-07-22 20:14:08: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 30 = ∑30/50, starting new job
2025-07-22 20:14:08: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 30 = ∑30/50, starting new job
2025-07-22 20:14:17: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 30/1 = ∑31/50, started new job
2025-07-22 20:14:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 30/1/1 = ∑32/50, starting new job
2025-07-22 20:14:28: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 30/1/1 = ∑32/50, started new job
2025-07-22 20:14:29: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 30/1/1 = ∑32/50, starting new job
2025-07-22 20:14:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 30/1/1 = ∑32/50, starting new job
2025-07-22 20:14:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 30/1/1 = ∑32/50, starting new job
2025-07-22 20:14:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 30/1/1 = ∑32/50, starting new job
2025-07-22 20:14:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 30/1/1 = ∑32/50, starting new job
2025-07-22 20:14:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 30/1/1 = ∑32/50, starting new job
2025-07-22 20:17:44: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 20:17:47: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/1 = ∑33/50, started new job
2025-07-22 20:17:51: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/2 = ∑34/50, started new job
2025-07-22 20:18:05: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/2/2 = ∑36/50, started new job
2025-07-22 20:18:07: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/2/2 = ∑36/50, started new job
2025-07-22 20:18:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 34/2 = ∑36/50, starting new job
2025-07-22 20:18:26: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 34/2/1 = ∑37/50, started new job
2025-07-22 20:18:28: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 34/2/4 = ∑40/50, started new job
2025-07-22 20:18:29: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 34/2/4/1 = ∑41/50, started new job
2025-07-22 20:18:29: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 34/2/4/1 = ∑41/50, started new job
2025-07-22 20:18:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 34/2/4/2 = ∑42/50, started new job
2025-07-22 20:18:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 34/2/4/2 = ∑42/50, started new job
2025-07-22 20:18:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 34/2/4/3 = ∑43/50, started new job
2025-07-22 20:18:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 36/7 = ∑43/50, starting new job
2025-07-22 20:21:24: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, starting new job
2025-07-22 20:21:50: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 43/1 = ∑44/50, started new job
2025-07-22 20:22:17: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 44 = ∑44/50, starting new job
2025-07-22 20:22:20: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 44/1 = ∑45/50, starting new job
2025-07-22 20:22:21: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 44/1 = ∑45/50, started new job
2025-07-22 20:22:41: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 45/1 = ∑46/50, started new job
2025-07-22 20:22:44: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 45/1 = ∑46/50, starting new job
2025-07-22 20:25:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 46/1 = ∑47/50, started new job
2025-07-22 20:26:13: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 47/1 = ∑48/50, started new job
2025-07-22 20:26:22: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 47/1/1 = ∑49/50, started new job
2025-07-22 20:26:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 47/2/1 = ∑50/50, started new job
2025-07-22 20:28:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:30: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:31: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:32: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:31: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:33: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:34: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:35: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:36: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:37: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:37: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:38: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:38: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:39: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:39: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:39: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:39: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:28:40: Sobol, failed: 200 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 20:36:44: Sobol, failed: 204 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 46 = ∑46/50, job_failed
2025-07-22 20:36:44: Sobol, failed: 204 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 45 = ∑45/50, job_failed
2025-07-22 20:36:45: Sobol, failed: 204 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 45 = ∑45/50, job_failed
2025-07-22 20:36:45: Sobol, failed: 204 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 45 = ∑45/50, job_failed
2025-07-22 20:36:47: Sobol, failed: 211 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-22 20:36:48: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:49: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:49: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:49: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:49: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:50: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:50: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:50: Sobol, failed: 213 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 20:36:54: Sobol, failed: 214 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-22 20:36:56: Sobol, failed: 215 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 35 = ∑35/50, job_failed
2025-07-22 20:37:00: Sobol, failed: 217 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-22 20:37:04: Sobol, failed: 222 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 25 = ∑25/50, job_failed
2025-07-22 20:37:05: Sobol, failed: 230 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 20:41:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-22 20:42:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-22 20:43:10: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-22 20:43:57: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-22 20:44:43: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-22 20:45:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-22 20:46:17: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-22 20:47:06: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-22 20:47:55: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-22 20:48:41: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-22 20:49:27: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-22 20:50:16: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-22 20:51:06: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-22 20:51:53: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-22 20:52:37: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-22 20:53:23: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-22 20:54:10: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-22 20:54:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-22 20:55:37: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-22 20:56:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-22 20:57:01: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-22 20:57:42: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-22 20:58:27: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-22 20:59:09: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-22 21:00:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-22 21:01:04: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-22 21:01:45: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-22 21:02:27: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-22 21:03:09: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-22 21:03:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-22 21:04:33: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-22 21:05:15: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-22 21:05:57: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-22 21:06:39: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-22 21:07:20: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-22 21:08:04: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-22 21:08:46: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-22 21:09:28: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-22 21:10:09: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-22 21:10:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-22 21:11:34: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-22 21:12:15: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-22 21:12:57: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-22 21:13:38: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-22 21:14:20: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-22 21:15:02: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-22 21:15:44: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-22 21:16:26: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-22 21:17:07: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-22 21:17:49: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-22 21:18:30: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-22 21:19:12: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 44.24 s/job
2025-07-22 21:19:32: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-22 21:19:54: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-22 21:20:15: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-22 21:20:37: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-22 21:20:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-22 21:21:20: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-22 21:21:41: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-22 21:22:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-22 21:22:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-22 21:22:47: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-22 21:23:08: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-22 21:23:31: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-22 21:23:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-22 21:24:13: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-22 21:24:36: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-22 21:24:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-22 21:25:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-22 21:25:42: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-22 21:26:11: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-22 21:26:36: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-22 21:26:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-22 21:27:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-22 21:27:41: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-22 21:28:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-22 21:28:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-22 21:28:46: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-22 21:29:08: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-22 21:29:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-22 21:29:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-22 21:30:14: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-22 21:30:36: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-22 21:30:57: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-22 21:31:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-22 21:31:40: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-22 21:32:02: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-22 21:32:23: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-22 21:32:45: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-22 21:33:06: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-22 21:33:28: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-22 21:33:49: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-22 21:34:11: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-22 21:34:33: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-22 21:34:55: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-22 21:35:18: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-22 21:35:39: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-22 21:36:00: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-22 21:36:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-22 21:36:44: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-22 21:37:06: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-22 21:37:28: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-22 21:37:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:53: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:53: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:37:53: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 21:41:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 1/1 = ∑2/50, started new job
2025-07-22 21:41:53: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 1/4 = ∑5/50, started new job
2025-07-22 21:41:53: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 1/5 = ∑6/50, started new job
2025-07-22 21:41:54: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 1/5 = ∑6/50, started new job
2025-07-22 21:41:54: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 1/5 = ∑6/50, started new job
2025-07-22 21:41:55: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 1/5 = ∑6/50, started new job
2025-07-22 21:41:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/1 = ∑8/50, started new job
2025-07-22 21:41:59: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/3 = ∑10/50, started new job
2025-07-22 21:42:00: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/3 = ∑10/50, started new job
2025-07-22 21:42:01: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/6 = ∑13/50, started new job
2025-07-22 21:42:02: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/9 = ∑16/50, started new job
2025-07-22 21:42:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/9 = ∑16/50, started new job
2025-07-22 21:42:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/9 = ∑16/50, started new job
2025-07-22 21:42:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/9 = ∑16/50, started new job
2025-07-22 21:42:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 7/9 = ∑16/50, started new job
2025-07-22 21:42:04: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending 10/6 = ∑16/50, started new job
2025-07-22 21:46:17: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:17: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:20: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:20: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:20: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:46:23: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:50:15: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 21:50:33: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/4 = ∑20/50, started new job
2025-07-22 21:50:34: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/4 = ∑20/50, started new job
2025-07-22 21:50:34: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/4 = ∑20/50, started new job
2025-07-22 21:50:34: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/4 = ∑20/50, started new job
2025-07-22 21:50:36: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/5 = ∑21/50, started new job
2025-07-22 21:50:42: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/5 = ∑26/50, started new job
2025-07-22 21:50:43: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/6 = ∑27/50, started new job
2025-07-22 21:50:43: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/8 = ∑29/50, started new job
2025-07-22 21:50:44: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/9 = ∑30/50, started new job
2025-07-22 21:50:44: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/9 = ∑30/50, started new job
2025-07-22 21:50:45: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/9 = ∑30/50, started new job
2025-07-22 21:50:45: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/9 = ∑30/50, started new job
2025-07-22 21:50:45: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/9 = ∑30/50, started new job
2025-07-22 21:50:45: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/4/1/10 = ∑31/50, started new job
2025-07-22 21:50:48: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 18/2/11 = ∑31/50, started new job
2025-07-22 21:54:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 31/1 = ∑32/50, started new job
2025-07-22 21:54:59: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:28: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:29: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:55:30: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:58:37: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-22 21:59:05: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/1 = ∑33/50, started new job
2025-07-22 21:59:07: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/1 = ∑33/50, starting new job
2025-07-22 21:59:07: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/1 = ∑33/50, starting new job
2025-07-22 21:59:09: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/1 = ∑33/50, starting new job
2025-07-22 21:59:09: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/1 = ∑33/50, starting new job
2025-07-22 21:59:50: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 33/3 = ∑36/50, started new job
2025-07-22 21:59:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 33/3 = ∑36/50, started new job
2025-07-22 21:59:51: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 33/4 = ∑37/50, started new job
2025-07-22 21:59:52: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 33/4 = ∑37/50, started new job
2025-07-22 21:59:55: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/3/3 = ∑39/50, started new job
2025-07-22 21:59:56: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/3/6 = ∑42/50, started new job
2025-07-22 21:59:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/3/7 = ∑43/50, started new job
2025-07-22 21:59:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/3/7 = ∑43/50, started new job
2025-07-22 21:59:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/3/7 = ∑43/50, started new job
2025-07-22 21:59:58: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/3/7 = ∑43/50, started new job
2025-07-22 22:03:10: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 43/1 = ∑44/50, started new job
2025-07-22 22:03:33: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 43/1/2 = ∑46/50, started new job
2025-07-22 22:03:34: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 43/3/2 = ∑48/50, started new job
2025-07-22 22:03:35: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 43/3/2 = ∑48/50, started new job
2025-07-22 22:03:35: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 43/3/2 = ∑48/50, started new job
2025-07-22 22:04:38: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 48 = ∑48/50, starting new job
2025-07-22 22:04:39: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 48 = ∑48/50, starting new job
2025-07-22 22:07:02: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/2 = ∑50/50, started new job
2025-07-22 22:07:03: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/2 = ∑50/50, started new job
2025-07-22 22:08:18: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:19: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:21: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:22: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:23: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:23: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:23: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:24: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:08:25: Sobol, failed: 250 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-22 22:17:30: Sobol, failed: 254 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 44 = ∑44/50, job_failed
2025-07-22 22:17:30: Sobol, failed: 257 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 256 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 257 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 259 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 259 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 254 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 259 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 22:17:31: Sobol, failed: 259 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-22 22:17:34: Sobol, failed: 260 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-22 22:17:35: Sobol, failed: 261 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 39 = ∑39/50, job_failed
2025-07-22 22:17:40: Sobol, failed: 262 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-22 22:17:41: Sobol, failed: 263 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-22 22:17:50: Sobol, failed: 267 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 30 = ∑30/50, job_failed
2025-07-22 22:17:51: Sobol, failed: 267 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 29 = ∑29/50, job_failed
2025-07-22 22:17:54: Sobol, failed: 274 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 22:17:54: Sobol, failed: 275 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 22:17:55: Sobol, failed: 272 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-22 22:23:11: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-22 22:23:45: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-22 22:24:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-22 22:25:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-22 22:26:16: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-22 22:27:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-22 22:27:57: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-22 22:28:46: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-22 22:29:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-22 22:30:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-22 22:31:16: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-22 22:32:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-22 22:32:50: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-22 22:33:36: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-22 22:34:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-22 22:35:08: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-22 22:35:56: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-22 22:36:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-22 22:37:29: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-22 22:38:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-22 22:39:02: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-22 22:39:48: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-22 22:40:34: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-22 22:41:20: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-22 22:42:07: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-22 22:42:55: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-22 22:43:41: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-22 22:44:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-22 22:45:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-22 22:46:01: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-22 22:46:47: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-22 22:47:33: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-22 22:48:20: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-22 22:49:06: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-22 22:49:52: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-22 22:50:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-22 22:51:25: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-22 22:52:11: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-22 22:52:57: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-22 22:53:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-22 22:54:29: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-22 22:55:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-22 22:56:01: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-22 22:56:47: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-22 22:57:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-22 22:58:21: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-22 22:59:09: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-22 22:59:57: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-22 23:00:44: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-22 23:01:30: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-22 23:02:16: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-22 23:03:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 47.19 s/job
2025-07-22 23:03:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-22 23:03:51: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-22 23:04:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-22 23:04:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-22 23:05:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-22 23:05:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-22 23:05:51: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-22 23:06:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-22 23:06:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-22 23:07:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-22 23:07:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-22 23:07:51: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-22 23:08:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-22 23:08:38: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-22 23:09:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-22 23:09:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-22 23:09:51: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-22 23:10:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-22 23:10:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-22 23:11:02: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-22 23:11:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-22 23:11:51: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-22 23:12:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-22 23:12:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-22 23:13:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-22 23:13:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-22 23:13:52: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-22 23:14:16: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-22 23:14:40: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-22 23:15:04: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-22 23:15:28: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-22 23:15:52: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-22 23:16:16: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-22 23:16:41: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-22 23:17:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-22 23:17:29: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-22 23:17:54: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-22 23:18:19: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-22 23:18:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-22 23:19:07: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-22 23:19:31: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-22 23:19:59: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-22 23:20:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-22 23:20:52: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-22 23:21:19: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-22 23:21:47: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-22 23:22:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-22 23:22:41: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-22 23:23:09: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-22 23:23:36: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-22 23:24:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:03: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:04: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:04: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:04: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:24:05: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-22 23:28:34: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 3 = ∑3/50, started new job
2025-07-22 23:28:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-22 23:28:36: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 7 = ∑7/50, started new job
2025-07-22 23:28:36: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 7 = ∑7/50, started new job
2025-07-22 23:28:36: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 23:28:37: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 23:28:37: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 23:28:37: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 8 = ∑8/50, started new job
2025-07-22 23:28:41: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 8/1 = ∑9/50, started new job
2025-07-22 23:28:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/2 = ∑15/50, started new job
2025-07-22 23:28:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/2 = ∑15/50, started new job
2025-07-22 23:28:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/2 = ∑15/50, started new job
2025-07-22 23:28:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/2 = ∑15/50, started new job
2025-07-22 23:28:43: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/2 = ∑15/50, started new job
2025-07-22 23:28:44: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/3 = ∑16/50, started new job
2025-07-22 23:28:46: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 13/3 = ∑16/50, started new job
2025-07-22 23:33:29: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:29: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:29: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:32: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:33: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:33: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:33: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:34: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:34: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:34: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:34: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:33:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-22 23:38:11: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-22 23:38:11: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-22 23:38:13: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-22 23:38:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/7 = ∑23/50, started new job
2025-07-22 23:38:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/7 = ∑23/50, started new job
2025-07-22 23:38:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/7 = ∑23/50, started new job
2025-07-22 23:38:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/7 = ∑23/50, started new job
2025-07-22 23:38:20: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/3 = ∑26/50, starting new job
2025-07-22 23:38:21: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-22 23:38:21: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/6 = ∑29/50, started new job
2025-07-22 23:38:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/8 = ∑31/50, started new job
2025-07-22 23:38:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/8 = ∑31/50, started new job
2025-07-22 23:38:23: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/8 = ∑31/50, started new job
2025-07-22 23:38:23: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/8 = ∑31/50, started new job
2025-07-22 23:38:24: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/8 = ∑31/50, started new job
2025-07-22 23:38:24: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/8 = ∑31/50, started new job
2025-07-22 23:43:12: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, started new job
2025-07-22 23:43:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:25: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:25: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:25: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:28: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:43:28: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 31/1 = ∑32/50, starting new job
2025-07-22 23:48:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/1 = ∑33/50, starting new job
2025-07-22 23:48:27: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, started new job
2025-07-22 23:48:28: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, started new job
2025-07-22 23:48:30: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/2/2 = ∑36/50, started new job
2025-07-22 23:48:30: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/2/2 = ∑36/50, started new job
2025-07-22 23:48:37: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/2 = ∑38/50, started new job
2025-07-22 23:48:37: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/4 = ∑40/50, started new job
2025-07-22 23:48:38: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/7 = ∑43/50, started new job
2025-07-22 23:48:38: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:48:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:48:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:48:39: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:48:40: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:48:40: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:48:40: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 32/4/10 = ∑46/50, started new job
2025-07-22 23:51:26: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 46 = ∑46/50, starting new job
2025-07-22 23:53:18: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 46/1 = ∑47/50, started new job
2025-07-22 23:53:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 46/1 = ∑47/50, starting new job
2025-07-22 23:53:35: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 46/1 = ∑47/50, starting new job
2025-07-22 23:55:59: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 47/1 = ∑48/50, started new job
2025-07-22 23:57:55: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/1 = ∑49/50, started new job
2025-07-22 23:57:57: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/2 = ∑50/50, started new job
2025-07-23 00:00:13: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:14: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:15: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:16: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:17: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:18: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:18: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:18: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:18: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:18: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:17: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:19: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:19: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:19: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:20: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:19: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:21: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:21: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:21: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:22: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:23: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:24: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:00:24: Sobol, failed: 300 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 00:10:37: Sobol, failed: 302 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 48 = ∑48/50, job_failed
2025-07-23 00:10:38: Sobol, failed: 302 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-23 00:10:41: Sobol, failed: 308 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:42: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:42: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:42: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:43: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:43: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:44: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:44: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 36 = ∑36/50, job_failed
2025-07-23 00:10:45: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 35 = ∑35/50, job_failed
2025-07-23 00:10:45: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 35 = ∑35/50, job_failed
2025-07-23 00:10:45: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 35 = ∑35/50, job_failed
2025-07-23 00:10:46: Sobol, failed: 314 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 35 = ∑35/50, job_failed
2025-07-23 00:10:48: Sobol, failed: 315 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 00:10:51: Sobol, failed: 316 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 00:10:59: Sobol, failed: 322 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 19 = ∑19/50, job_failed
2025-07-23 00:11:00: Sobol, failed: 330 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 00:16:55: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-23 00:17:28: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-23 00:18:20: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-23 00:19:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-23 00:20:03: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-23 00:20:54: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-23 00:21:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-23 00:22:37: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-23 00:23:28: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-23 00:24:19: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-23 00:25:10: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-23 00:26:02: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-23 00:26:54: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-23 00:27:47: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-23 00:28:39: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-23 00:29:30: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-23 00:30:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-23 00:31:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-23 00:32:03: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-23 00:32:54: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-23 00:33:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-23 00:34:38: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-23 00:35:29: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-23 00:36:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-23 00:37:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-23 00:38:04: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-23 00:38:54: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-23 00:39:44: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-23 00:40:35: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-23 00:41:26: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-23 00:42:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-23 00:43:08: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-23 00:43:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-23 00:44:49: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-23 00:45:40: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-23 00:46:32: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-23 00:47:24: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-23 00:48:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-23 00:49:07: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-23 00:49:59: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-23 00:50:51: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-23 00:51:43: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-23 00:52:36: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-23 00:53:28: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-23 00:54:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-23 00:55:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-23 00:56:05: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-23 00:56:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-23 00:57:50: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-23 00:58:40: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-23 00:59:32: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-23 01:00:23: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 51.54 s/job
2025-07-23 01:00:49: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-23 01:01:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-23 01:01:43: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-23 01:02:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-23 01:02:39: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-23 01:03:06: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-23 01:03:32: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-23 01:03:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-23 01:04:25: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-23 01:04:51: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-23 01:05:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-23 01:05:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-23 01:06:13: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-23 01:06:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-23 01:07:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-23 01:07:41: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-23 01:08:07: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-23 01:08:34: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-23 01:09:00: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-23 01:09:26: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-23 01:09:53: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-23 01:10:19: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-23 01:10:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-23 01:11:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-23 01:11:38: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-23 01:12:06: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-23 01:12:33: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-23 01:13:00: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-23 01:13:26: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-23 01:13:52: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-23 01:14:19: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-23 01:14:45: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-23 01:15:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-23 01:15:37: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-23 01:16:04: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-23 01:16:30: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-23 01:16:57: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-23 01:17:23: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-23 01:17:50: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-23 01:18:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-23 01:18:43: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-23 01:19:09: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-23 01:19:35: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-23 01:20:03: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-23 01:20:29: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-23 01:20:56: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-23 01:21:22: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-23 01:21:48: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-23 01:22:15: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-23 01:22:42: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-23 01:23:09: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:10: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:10: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:23:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 01:28:05: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 2 = ∑2/50, started new job
2025-07-23 01:28:05: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 2 = ∑2/50, started new job
2025-07-23 01:28:07: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 2/3 = ∑5/50, started new job
2025-07-23 01:28:08: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 2/3 = ∑5/50, started new job
2025-07-23 01:28:09: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 2/3 = ∑5/50, started new job
2025-07-23 01:28:10: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 2/6 = ∑8/50, started new job
2025-07-23 01:28:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 2/6 = ∑8/50, started new job
2025-07-23 01:28:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 2/6 = ∑8/50, started new job
2025-07-23 01:28:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/2 = ∑14/50, started new job
2025-07-23 01:28:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/2 = ∑14/50, started new job
2025-07-23 01:28:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/3 = ∑15/50, started new job
2025-07-23 01:28:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/3 = ∑15/50, started new job
2025-07-23 01:28:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/3 = ∑15/50, started new job
2025-07-23 01:28:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/3 = ∑15/50, started new job
2025-07-23 01:28:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/4 = ∑16/50, started new job
2025-07-23 01:28:19: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), running/pending/unknown 8/4/4 = ∑16/50, started new job
2025-07-23 01:33:45: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:45: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:46: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:47: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:47: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:48: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:48: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:48: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:48: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:49: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:49: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:33:50: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:38:55: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:39:09: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 01:39:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/2 = ∑18/50, starting new job
2025-07-23 01:39:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/2 = ∑18/50, started new job
2025-07-23 01:39:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/2 = ∑18/50, started new job
2025-07-23 01:39:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/6 = ∑22/50, started new job
2025-07-23 01:39:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/6 = ∑22/50, started new job
2025-07-23 01:39:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/6 = ∑22/50, started new job
2025-07-23 01:39:15: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/6 = ∑22/50, started new job
2025-07-23 01:39:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 16/3/5 = ∑24/50, started new job
2025-07-23 01:39:19: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/3/5/3 = ∑27/50, started new job
2025-07-23 01:39:20: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/3/5/5 = ∑29/50, started new job
2025-07-23 01:39:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/3/5/5 = ∑29/50, started new job
2025-07-23 01:39:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/3/5/5 = ∑29/50, started new job
2025-07-23 01:39:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/3/5/5 = ∑29/50, started new job
2025-07-23 01:39:21: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/3/5/5 = ∑29/50, started new job
2025-07-23 01:44:20: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 29/1 = ∑30/50, started new job
2025-07-23 01:44:36: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 29/1/1 = ∑31/50, started new job
2025-07-23 01:44:41: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 29/3 = ∑32/50, started new job
2025-07-23 01:49:33: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:49:33: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:49: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:50: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:50: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:51: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:51: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:53: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:55: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:56: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:57: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:50:58: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:54:51: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 01:55:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, started new job
2025-07-23 01:55:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, started new job
2025-07-23 01:56:26: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 34/1 = ∑35/50, started new job
2025-07-23 01:56:29: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/1/5 = ∑40/50, started new job
2025-07-23 01:56:30: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/1/5 = ∑40/50, started new job
2025-07-23 01:56:30: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/1/5 = ∑40/50, started new job
2025-07-23 01:56:30: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/1/5 = ∑40/50, started new job
2025-07-23 01:56:30: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/1/5 = ∑40/50, started new job
2025-07-23 01:56:34: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 34/7 = ∑41/50, started new job
2025-07-23 01:56:36: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/7/6 = ∑47/50, started new job
2025-07-23 01:56:36: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/7/6 = ∑47/50, started new job
2025-07-23 01:56:36: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/7/6 = ∑47/50, started new job
2025-07-23 01:56:37: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/7/6 = ∑47/50, started new job
2025-07-23 01:56:37: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 34/7/6 = ∑47/50, started new job
2025-07-23 01:56:37: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 34/13 = ∑47/50, started new job
2025-07-23 02:00:28: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 47/1 = ∑48/50, started new job
2025-07-23 02:00:55: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 47/1 = ∑48/50, starting new job
2025-07-23 02:02:41: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 48 = ∑48/50, starting new job
2025-07-23 02:03:40: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 48/1 = ∑49/50, started new job
2025-07-23 02:04:06: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 49/1 = ∑50/50, started new job
2025-07-23 02:05:09: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:10: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:10: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:11: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:12: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:13: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:13: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:13: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:13: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:14: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:15: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:15: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:13: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:16: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:17: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:18: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:05:19: Sobol, failed: 350 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 02:16:48: Sobol, failed: 353 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 46 = ∑46/50, job_failed
2025-07-23 02:16:49: Sobol, failed: 354 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-23 02:16:49: Sobol, failed: 356 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-23 02:16:50: Sobol, failed: 361 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-23 02:16:50: Sobol, failed: 364 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:51: Sobol, failed: 366 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:51: Sobol, failed: 364 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:52: Sobol, failed: 366 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:52: Sobol, failed: 366 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:52: Sobol, failed: 366 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:52: Sobol, failed: 366 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 34 = ∑34/50, job_failed
2025-07-23 02:16:54: Sobol, failed: 366 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-23 02:16:55: Sobol, failed: 367 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-23 02:16:55: Sobol, failed: 367 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-23 02:16:55: Sobol, failed: 367 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-23 02:16:56: Sobol, failed: 367 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-23 02:16:58: Sobol, failed: 367 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, job_failed
2025-07-23 02:17:00: Sobol, failed: 368 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, job_failed
2025-07-23 02:24:05: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-23 02:24:43: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-23 02:25:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-23 02:26:38: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-23 02:27:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-23 02:28:33: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-23 02:29:31: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-23 02:30:28: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-23 02:31:26: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-23 02:32:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-23 02:33:21: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-23 02:34:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-23 02:35:21: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-23 02:36:19: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-23 02:37:16: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-23 02:38:15: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-23 02:39:12: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-23 02:40:08: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-23 02:41:05: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-23 02:42:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-23 02:43:00: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-23 02:43:58: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-23 02:44:55: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-23 02:45:54: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-23 02:46:51: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-23 02:47:51: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-23 02:48:48: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-23 02:49:45: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-23 02:50:43: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-23 02:51:41: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-23 02:52:38: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-23 02:53:35: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-23 02:54:33: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-23 02:55:32: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-23 02:56:30: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-23 02:57:28: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-23 02:58:25: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-23 02:59:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-23 03:00:20: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-23 03:01:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-23 03:02:15: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-23 03:03:13: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-23 03:04:09: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-23 03:05:06: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-23 03:06:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-23 03:07:01: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-23 03:07:58: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-23 03:08:55: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-23 03:09:53: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-23 03:10:51: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-23 03:11:49: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-23 03:12:45: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 57.70 s/job
2025-07-23 03:13:13: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-23 03:13:42: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-23 03:14:12: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-23 03:14:41: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-23 03:15:11: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-23 03:15:41: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-23 03:16:11: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-23 03:16:41: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-23 03:17:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-23 03:17:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-23 03:18:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-23 03:18:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-23 03:19:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-23 03:19:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-23 03:20:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-23 03:20:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-23 03:21:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-23 03:21:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-23 03:22:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-23 03:22:39: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-23 03:23:09: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-23 03:23:39: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-23 03:24:08: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-23 03:24:38: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-23 03:25:08: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-23 03:25:37: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-23 03:26:07: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-23 03:26:37: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-23 03:27:06: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-23 03:27:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-23 03:28:07: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-23 03:28:37: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-23 03:29:07: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-23 03:29:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-23 03:30:06: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-23 03:30:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-23 03:31:05: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-23 03:31:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-23 03:32:05: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-23 03:32:35: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-23 03:33:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-23 03:33:34: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-23 03:34:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-23 03:34:33: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-23 03:35:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-23 03:35:32: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-23 03:36:02: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-23 03:36:33: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-23 03:37:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-23 03:37:32: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-23 03:38:02: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:02: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:38:05: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 03:43:56: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 3 = ∑3/50, started new job
2025-07-23 03:43:57: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 3 = ∑3/50, started new job
2025-07-23 03:43:57: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 3 = ∑3/50, started new job
2025-07-23 03:44:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/1 = ∑4/50, started new job
2025-07-23 03:44:06: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 3/3 = ∑6/50, started new job
2025-07-23 03:44:06: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/2 = ∑8/50, started new job
2025-07-23 03:44:08: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/8 = ∑14/50, started new job
2025-07-23 03:44:08: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/9 = ∑15/50, started new job
2025-07-23 03:44:09: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/10 = ∑16/50, started new job
2025-07-23 03:44:09: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/10 = ∑16/50, started new job
2025-07-23 03:44:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/10 = ∑16/50, started new job
2025-07-23 03:44:10: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/10 = ∑16/50, started new job
2025-07-23 03:44:11: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-23 03:44:11: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-23 03:44:11: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-23 03:44:12: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 16 = ∑16/50, started new job
2025-07-23 03:50:31: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:35: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:36: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:37: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:37: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:37: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:38: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:50:38: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:54:01: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:54:01: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:54:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 03:56:26: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-23 03:56:26: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/3 = ∑19/50, started new job
2025-07-23 03:56:27: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 16/5 = ∑21/50, started new job
2025-07-23 03:56:29: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-23 03:56:29: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-23 03:56:29: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-23 03:56:30: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-23 03:56:39: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/9/4 = ∑29/50, started new job
2025-07-23 03:56:39: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/9/4 = ∑29/50, started new job
2025-07-23 03:56:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/9/4 = ∑29/50, started new job
2025-07-23 03:56:40: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/9/4 = ∑29/50, started new job
2025-07-23 03:56:41: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/9/4 = ∑29/50, started new job
2025-07-23 03:56:41: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/9/4 = ∑29/50, started new job
2025-07-23 03:59:55: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 29/1/1 = ∑31/50, started new job
2025-07-23 03:59:56: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 29/1/2 = ∑32/50, started new job
2025-07-23 03:59:57: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 29/1/2 = ∑32/50, started new job
2025-07-23 04:02:57: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:02:58: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:02:58: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:02:58: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:02:59: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:03:01: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:03:02: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:03:02: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:03:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:03:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:05:46: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:05:47: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:05:49: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:08:46: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:08:56: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 04:09:03: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/2 = ∑34/50, started new job
2025-07-23 04:09:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/3 = ∑35/50, started new job
2025-07-23 04:09:05: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/3 = ∑35/50, started new job
2025-07-23 04:09:06: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/5 = ∑37/50, starting new job
2025-07-23 04:09:07: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/5 = ∑37/50, started new job
2025-07-23 04:09:08: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 32/5 = ∑37/50, started new job
2025-07-23 04:09:11: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/5/2 = ∑39/50, started new job
2025-07-23 04:09:12: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/5/5 = ∑42/50, started new job
2025-07-23 04:09:13: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 32/5/5 = ∑42/50, started new job
2025-07-23 04:09:14: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/10 = ∑42/50, started new job
2025-07-23 04:09:14: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/10 = ∑42/50, started new job
2025-07-23 04:11:55: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 42/2 = ∑44/50, started new job
2025-07-23 04:11:56: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 42/2 = ∑44/50, started new job
2025-07-23 04:11:59: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 42/3 = ∑45/50, started new job
2025-07-23 04:14:55: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 45/1 = ∑46/50, started new job
2025-07-23 04:15:04: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 45/1/1 = ∑47/50, started new job
2025-07-23 04:15:19: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 45/2/1 = ∑48/50, started new job
2025-07-23 04:15:34: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 45/3 = ∑48/50, starting new job
2025-07-23 04:15:34: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 45/3 = ∑48/50, starting new job
2025-07-23 04:18:59: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 48/1/1 = ∑50/50, started new job
2025-07-23 04:19:01: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 48/1/1 = ∑50/50, started new job
2025-07-23 04:21:14: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:15: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:16: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:16: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:17: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:16: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:17: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:17: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:19: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:19: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:18: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:20: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:20: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:20: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:21: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:21: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:21: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:22: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:21: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:22: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:23: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:25: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:25: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:21:25: Sobol, failed: 400 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 04:33:54: Sobol, failed: 403 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-23 04:33:55: Sobol, failed: 403 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-23 04:33:55: Sobol, failed: 403 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 47 = ∑47/50, job_failed
2025-07-23 04:33:56: Sobol, failed: 407 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-23 04:33:57: Sobol, failed: 407 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-23 04:33:57: Sobol, failed: 407 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-23 04:33:57: Sobol, failed: 407 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 43 = ∑43/50, job_failed
2025-07-23 04:34:01: Sobol, failed: 408 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 42 = ∑42/50, job_failed
2025-07-23 04:34:07: Sobol, failed: 409 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 41 = ∑41/50, job_failed
2025-07-23 04:34:09: Sobol, failed: 410 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-23 04:34:11: Sobol, failed: 411 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-23 04:34:12: Sobol, failed: 412 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-23 04:34:13: Sobol, failed: 413 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 37 = ∑37/50, job_failed
2025-07-23 04:34:21: Sobol, failed: 423 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 04:34:21: Sobol, failed: 432 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 04:34:21: Sobol, failed: 432 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 04:34:21: Sobol, failed: 432 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 04:34:22: Sobol, failed: 432 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 04:41:42: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
2025-07-23 04:42:23: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #1/50
2025-07-23 04:43:26: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #2/50
2025-07-23 04:44:29: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #3/50
2025-07-23 04:45:33: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #4/50
2025-07-23 04:46:35: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #5/50
2025-07-23 04:47:38: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #6/50
2025-07-23 04:48:48: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #7/50
2025-07-23 04:49:52: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #8/50
2025-07-23 04:50:55: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #9/50
2025-07-23 04:51:59: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #10/50
2025-07-23 04:53:03: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #11/50
2025-07-23 04:54:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #12/50
2025-07-23 04:55:13: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #13/50
2025-07-23 04:56:18: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #14/50
2025-07-23 04:57:22: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #15/50
2025-07-23 04:58:25: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #16/50
2025-07-23 04:59:30: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #17/50
2025-07-23 05:00:34: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #18/50
2025-07-23 05:01:37: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #19/50
2025-07-23 05:02:47: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #20/50
2025-07-23 05:03:55: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #21/50
2025-07-23 05:04:58: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #22/50
2025-07-23 05:06:03: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #23/50
2025-07-23 05:07:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #24/50
2025-07-23 05:08:11: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #25/50
2025-07-23 05:09:14: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #26/50
2025-07-23 05:10:17: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #27/50
2025-07-23 05:11:19: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #28/50
2025-07-23 05:12:22: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #29/50
2025-07-23 05:13:24: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #30/50
2025-07-23 05:14:27: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #31/50
2025-07-23 05:15:29: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #32/50
2025-07-23 05:16:33: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #33/50
2025-07-23 05:17:36: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #34/50
2025-07-23 05:18:40: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #35/50
2025-07-23 05:19:43: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #36/50
2025-07-23 05:20:46: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #37/50
2025-07-23 05:21:49: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #38/50
2025-07-23 05:22:51: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #39/50
2025-07-23 05:23:53: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #40/50
2025-07-23 05:24:56: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #41/50
2025-07-23 05:25:58: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #42/50
2025-07-23 05:27:01: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #43/50
2025-07-23 05:28:03: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #44/50
2025-07-23 05:29:06: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #45/50
2025-07-23 05:30:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #46/50
2025-07-23 05:31:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #47/50
2025-07-23 05:32:13: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #48/50
2025-07-23 05:33:15: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #49/50
2025-07-23 05:34:19: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), getting new HP set #50/50
2025-07-23 05:35:22: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), requested 50 jobs, got 50, 63.63 s/job
2025-07-23 05:35:53: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #1/50 start
2025-07-23 05:36:26: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #2/50 start
2025-07-23 05:36:58: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #3/50 start
2025-07-23 05:37:31: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #4/50 start
2025-07-23 05:38:05: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #5/50 start
2025-07-23 05:38:37: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #6/50 start
2025-07-23 05:39:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #7/50 start
2025-07-23 05:39:44: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #8/50 start
2025-07-23 05:40:16: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #9/50 start
2025-07-23 05:40:49: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #10/50 start
2025-07-23 05:41:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #11/50 start
2025-07-23 05:41:54: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #12/50 start
2025-07-23 05:42:26: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #13/50 start
2025-07-23 05:42:59: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #14/50 start
2025-07-23 05:43:33: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #15/50 start
2025-07-23 05:44:05: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #16/50 start
2025-07-23 05:44:38: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #17/50 start
2025-07-23 05:45:12: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #18/50 start
2025-07-23 05:45:44: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #19/50 start
2025-07-23 05:46:18: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #20/50 start
2025-07-23 05:46:50: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #21/50 start
2025-07-23 05:47:23: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #22/50 start
2025-07-23 05:47:55: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #23/50 start
2025-07-23 05:48:28: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #24/50 start
2025-07-23 05:49:00: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #25/50 start
2025-07-23 05:49:33: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #26/50 start
2025-07-23 05:50:05: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #27/50 start
2025-07-23 05:50:38: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #28/50 start
2025-07-23 05:51:11: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #29/50 start
2025-07-23 05:51:44: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #30/50 start
2025-07-23 05:52:17: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #31/50 start
2025-07-23 05:52:50: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #32/50 start
2025-07-23 05:53:23: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #33/50 start
2025-07-23 05:53:55: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #34/50 start
2025-07-23 05:54:28: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #35/50 start
2025-07-23 05:55:01: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #36/50 start
2025-07-23 05:55:34: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #37/50 start
2025-07-23 05:56:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #38/50 start
2025-07-23 05:56:40: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #39/50 start
2025-07-23 05:57:14: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #40/50 start
2025-07-23 05:57:48: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #41/50 start
2025-07-23 05:58:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #42/50 start
2025-07-23 05:58:53: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #43/50 start
2025-07-23 05:59:26: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #44/50 start
2025-07-23 05:59:58: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #45/50 start
2025-07-23 06:00:31: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #46/50 start
2025-07-23 06:01:05: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #47/50 start
2025-07-23 06:01:38: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #48/50 start
2025-07-23 06:02:12: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #49/50 start
2025-07-23 06:02:46: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), eval #50/50 start
2025-07-23 06:03:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:03:21: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), starting new job
2025-07-23 06:09:50: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 3 = ∑3/50, started new job
2025-07-23 06:09:50: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-23 06:09:50: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-23 06:09:51: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-23 06:09:51: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-23 06:09:51: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), unknown 6 = ∑6/50, started new job
2025-07-23 06:09:55: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/1 = ∑7/50, started new job
2025-07-23 06:09:57: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 6/3 = ∑9/50, started new job
2025-07-23 06:09:58: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending 9 = ∑9/50, started new job
2025-07-23 06:10:00: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:10:00: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:10:00: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:10:01: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:10:02: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:10:02: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:10:02: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), pending/unknown 9/7 = ∑16/50, started new job
2025-07-23 06:16:41: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:43: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:43: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:43: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:44: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:45: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:46: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:46: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:47: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:47: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:16:49: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:22:40: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:23:02: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 16 = ∑16/50, starting new job
2025-07-23 06:23:05: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 16/1 = ∑17/50, started new job
2025-07-23 06:23:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/3 = ∑20/50, started new job
2025-07-23 06:23:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/3 = ∑20/50, started new job
2025-07-23 06:23:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/3 = ∑20/50, started new job
2025-07-23 06:23:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/4 = ∑21/50, starting new job
2025-07-23 06:23:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/1/4 = ∑21/50, started new job
2025-07-23 06:23:14: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-23 06:23:14: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, started new job
2025-07-23 06:23:14: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/5/2 = ∑23/50, starting new job
2025-07-23 06:23:15: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/1 = ∑24/50, starting new job
2025-07-23 06:23:16: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-23 06:23:17: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 16/7/4 = ∑27/50, started new job
2025-07-23 06:23:18: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/7/3/1 = ∑27/50, started new job
2025-07-23 06:23:18: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 16/7/3/1 = ∑27/50, started new job
2025-07-23 06:29:39: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 27/1 = ∑28/50, started new job
2025-07-23 06:29:44: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 27/1/1 = ∑29/50, started new job
2025-07-23 06:29:44: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 27/1/1 = ∑29/50, starting new job
2025-07-23 06:30:04: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 29/3 = ∑32/50, started new job
2025-07-23 06:30:04: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 29/3 = ∑32/50, started new job
2025-07-23 06:30:06: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 29/3 = ∑32/50, started new job
2025-07-23 06:35:39: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 32 = ∑32/50, starting new job
2025-07-23 06:35:49: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 32/1 = ∑33/50, started new job
2025-07-23 06:35:57: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 32/1 = ∑33/50, starting new job
2025-07-23 06:36:52: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:53: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:55: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:56: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:56: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:56: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:58: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:36:59: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:37:01: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:37:01: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:37:01: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:42:26: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 33 = ∑33/50, starting new job
2025-07-23 06:42:28: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 33/1 = ∑34/50, started new job
2025-07-23 06:42:38: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending/unknown 33/1/1 = ∑35/50, started new job
2025-07-23 06:42:45: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/pending 33/2 = ∑35/50, starting new job
2025-07-23 06:43:26: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running 33/2 = ∑35/50, starting new job
2025-07-23 06:43:33: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/2/3 = ∑38/50, started new job
2025-07-23 06:43:33: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/2/3 = ∑38/50, started new job
2025-07-23 06:43:34: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/2/5 = ∑40/50, started new job
2025-07-23 06:43:34: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/2/5 = ∑40/50, started new job
2025-07-23 06:43:35: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/2/5 = ∑40/50, started new job
2025-07-23 06:43:38: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 33/2/5/1 = ∑41/50, started new job
2025-07-23 06:43:40: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 33/2/5/5 = ∑45/50, started new job
2025-07-23 06:43:41: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 33/2/5/5 = ∑45/50, started new job
2025-07-23 06:43:41: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 33/2/5/6 = ∑46/50, started new job
2025-07-23 06:43:42: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 33/2/5/5 = ∑45/50, started new job
2025-07-23 06:43:43: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending/unknown 33/2/5/6 = ∑46/50, started new job
2025-07-23 06:49:19: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/13/1 = ∑47/50, started new job
2025-07-23 06:49:35: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/14/1 = ∑48/50, started new job
2025-07-23 06:49:37: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/pending 33/14/1 = ∑48/50, starting new job
2025-07-23 06:50:20: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/running/unknown 33/15/1 = ∑49/50, started new job
2025-07-23 06:52:24: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed/unknown 49/1 = ∑50/50, started new job
2025-07-23 06:54:05: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:06: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:06: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:07: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:08: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:11: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:10: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:12: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:12: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:12: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:12: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:13: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:13: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:13: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:13: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:15: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 06:54:16: Sobol, failed: 450 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 50 = ∑50/50, job_failed
2025-07-23 07:07:48: Sobol, failed: 452 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 46 = ∑46/50, job_failed
2025-07-23 07:07:49: Sobol, failed: 455 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 45 = ∑45/50, job_failed
2025-07-23 07:07:50: Sobol, failed: 454 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 45 = ∑45/50, job_failed
2025-07-23 07:07:50: Sobol, failed: 455 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 45 = ∑45/50, job_failed
2025-07-23 07:07:51: Sobol, failed: 455 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 44 = ∑44/50, job_failed
2025-07-23 07:07:53: Sobol, failed: 460 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-23 07:07:53: Sobol, failed: 460 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-23 07:07:53: Sobol, failed: 460 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-23 07:07:54: Sobol, failed: 460 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-23 07:07:55: Sobol, failed: 460 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 40 = ∑40/50, job_failed
2025-07-23 07:08:00: Sobol, failed: 461 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 39 = ∑39/50, job_failed
2025-07-23 07:08:01: Sobol, failed: 462 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 38 = ∑38/50, job_failed
2025-07-23 07:08:17: Sobol, failed: 482 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 07:08:17: Sobol, failed: 482 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 07:08:17: Sobol, failed: 482 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 07:08:17: Sobol, failed: 482 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 07:08:17: Sobol, failed: 482 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 07:08:17: Sobol, failed: 482 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), completed 18 = ∑18/50, job_failed
2025-07-23 07:16:16: Sobol, failed: 500 ('VAL_ACC: <FLOAT>' not found, 'VAL_ACC: <FLOAT>' not found), finishing jobs, finished 50 jobs
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_progressbar_log")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<h1><img class='invert_icon' src='i/terminal.svg' style='height: 1em' /> Job Submit Durations</h1>
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<button onclick='download_as_file("simple_pre_tab_tab_job_submit_durations", "job_submit_durations.txt")'><img src='i/download.svg' style='height: 1em'> Download »job_submit_durations.txt« as file</button>
<pre id='simple_pre_tab_tab_job_submit_durations'> Job submission durations
┏━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Batch ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 680.634 │ 50 │ 13.613 │
│ 2 │ 819.618 │ 50 │ 16.392 │
│ 3 │ 1191.734 │ 50 │ 23.835 │
│ 4 │ 1316.394 │ 50 │ 26.328 │
│ 5 │ 1777.514 │ 50 │ 35.550 │
│ 6 │ 1825.497 │ 50 │ 36.510 │
│ 7 │ 2167.707 │ 50 │ 43.354 │
│ 8 │ 2517.345 │ 50 │ 50.347 │
│ 9 │ 2590.042 │ 50 │ 51.801 │
│ 10 │ 3043.248 │ 50 │ 60.865 │
├─────────┼───────────┼──────┼──────────────┤
│ Average │ 1792.973 │ │ │
│ Median │ 1801.505 │ │ │
│ Total │ 17929.731 │ │ │
│ Max │ 3043.248 │ │ │
│ Min │ 680.634 │ │ │
└─────────┴───────────┴──────┴──────────────┘
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_job_submit_durations")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("simple_pre_tab_tab_job_submit_durations", "job_submit_durations.txt")'><img src='i/download.svg' style='height: 1em'> Download »job_submit_durations.txt« as file</button>
<h1><img class='invert_icon' src='i/terminal.svg' style='height: 1em' /> Generation Times</h1>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_job_generation_times")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<pre id='simple_pre_tab_tab_job_generation_times'> Model generation times
┏━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━┳━━━━━━━━━━━━━━┓
┃ Iteration ┃ Seconds ┃ Jobs ┃ Time per job ┃
┡━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━╇━━━━━━━━━━━━━━┩
│ 1 │ 561.340 │ 50 │ 11.227 │
│ 2 │ 1322.905 │ 50 │ 26.458 │
│ 3 │ 1535.655 │ 50 │ 30.713 │
│ 4 │ 1798.765 │ 50 │ 35.975 │
│ 5 │ 1973.039 │ 50 │ 39.461 │
│ 6 │ 2211.937 │ 50 │ 44.239 │
│ 7 │ 2359.498 │ 50 │ 47.190 │
│ 8 │ 2576.968 │ 50 │ 51.539 │
│ 9 │ 2884.902 │ 50 │ 57.698 │
│ 10 │ 3181.573 │ 50 │ 63.631 │
├───────────┼───────────┼──────┼──────────────┤
│ Average │ 2040.658 │ │ │
│ Median │ 2092.488 │ │ │
│ Total │ 20406.583 │ │ │
│ Max │ 3181.573 │ │ │
│ Min │ 561.340 │ │ │
└───────────┴───────────┴──────┴──────────────┘
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_job_generation_times")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<h1><img class='invert_icon' src='i/table.svg' style='height: 1em' /> Args Overview</h1>
<h2>Arguments Overview </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value </th></tr></thead><tbody><tr><td> config_yaml</td><td>None </td></tr><tr><td> config_toml</td><td>None </td></tr><tr><td> config_json</td><td>None </td></tr><tr><td> num_random_steps</td><td>20 </td></tr><tr><td> max_eval</td><td>500 </td></tr><tr><td> run_program</td><td>[["'cHl0aG9uMyAudGVzdHMvbW5pc3QvdHJhaW4gLS1lcG9jaHMgJWVwb2NocyAtLWxlYXJuaW5nX3JhdGUgJWxyIC0tYmF0Y2hfc2l6ZSAlYmF0Y2hfc2l6ZSAtLWhpZGRlbl9zaXplICVoaWRkZW5… </td></tr><tr><td> experiment_name</td><td>mnist_cpu </td></tr><tr><td> mem_gb</td><td>5 </td></tr><tr><td> parameter</td><td>[['epochs', 'range', '10', '200', 'int', 'false'], ['lr', 'range', '0.0001', '0.1', 'float', 'false'], ['batch_size', 'range', '8', '4096', 'int', </td></tr><tr><td></td><td>'false'], ['hidden_size', 'range', '8', '8192', 'int', 'false'], ['dropout', 'range', '0', '0.5', 'float', 'false'], ['activation', 'fixed', </td></tr><tr><td></td><td>'leaky_relu'], ['num_dense_layers', 'range', '1', '4', 'int', 'false'], ['init', 'fixed', 'normal'], ['weight_decay', 'range', '0', '1', 'float', </td></tr><tr><td></td><td>'false']] </td></tr><tr><td> continue_previous_job</td><td>None </td></tr><tr><td> experiment_constraints</td><td>None </td></tr><tr><td> run_dir</td><td>runs </td></tr><tr><td> seed</td><td>None </td></tr><tr><td> verbose_tqdm</td><td>False </td></tr><tr><td> model</td><td>BOTORCH_MODULAR </td></tr><tr><td> gridsearch</td><td>False </td></tr><tr><td> occ</td><td>False </td></tr><tr><td> show_sixel_scatter</td><td>False </td></tr><tr><td> show_sixel_general</td><td>False </td></tr><tr><td> show_sixel_trial_index_result</td><td>False </td></tr><tr><td> follow</td><td>True </td></tr><tr><td> send_anonymized_usage_stats</td><td>True </td></tr><tr><td> ui_url</td><td>aHR0cHM6Ly9pbWFnZXNlZy5zY2Fkcy5kZS9vbW5pYXgvZ3VpP3BhcnRpdGlvbj1iYXJuYXJkJmV4cGVyaW1lbnRfbmFtZT1tbmlzdF9jcHUmcmVzZXJ2YXRpb249JmFjY291bnQ9Jm1lbV9nYj01JnR… </td></tr><tr><td> root_venv_dir</td><td>/home/pwinkler </td></tr><tr><td> exclude</td><td>None </td></tr><tr><td> main_process_gb</td><td>8 </td></tr><tr><td> max_nr_of_zero_results</td><td>50 </td></tr><tr><td> abbreviate_job_names</td><td>False </td></tr><tr><td> orchestrator_file</td><td>None </td></tr><tr><td> checkout_to_latest_tested_version</td><td>False </td></tr><tr><td> live_share</td><td>True </td></tr><tr><td> disable_tqdm</td><td>False </td></tr><tr><td> disable_previous_job_constraint</td><td>False </td></tr><tr><td> workdir</td><td></td></tr><tr><td> occ_type</td><td>euclid </td></tr><tr><td> result_names</td><td>['VAL_ACC=max'] </td></tr><tr><td> minkowski_p</td><td>2 </td></tr><tr><td> signed_weighted_euclidean_weights</td><td></td></tr><tr><td> generation_strategy</td><td>None </td></tr><tr><td> generate_all_jobs_at_once</td><td>True </td></tr><tr><td> revert_to_random_when_seemingly_exhausted</td><td>True </td></tr><tr><td> load_data_from_existing_jobs</td><td>[] </td></tr><tr><td> n_estimators_randomforest</td><td>100 </td></tr><tr><td> max_attempts_for_generation</td><td>20 </td></tr><tr><td> external_generator</td><td>None </td></tr><tr><td> username</td><td>None </td></tr><tr><td> max_failed_jobs</td><td>0 </td></tr><tr><td> num_cpus_main_job</td><td>None </td></tr><tr><td> calculate_pareto_front_of_job</td><td>[] </td></tr><tr><td> show_generate_time_table</td><td>False </td></tr><tr><td> force_choice_for_ranges</td><td>False </td></tr><tr><td> max_abandoned_retrial</td><td>20 </td></tr><tr><td> share_password</td><td>None </td></tr><tr><td> dryrun</td><td>False </td></tr><tr><td> db_url</td><td>None </td></tr><tr><td> dont_warm_start_refitting</td><td>False </td></tr><tr><td> refit_on_cv</td><td>False </td></tr><tr><td> fit_out_of_design</td><td>False </td></tr><tr><td> fit_abandoned</td><td>False </td></tr><tr><td> dont_jit_compile</td><td>False </td></tr><tr><td> num_restarts</td><td>20 </td></tr><tr><td> raw_samples</td><td>1024 </td></tr><tr><td> max_num_of_parallel_sruns</td><td>16 </td></tr><tr><td> no_transform_inputs</td><td>False </td></tr><tr><td> no_normalize_y</td><td>False </td></tr><tr><td> transforms</td><td>[] </td></tr><tr><td> num_parallel_jobs</td><td>50 </td></tr><tr><td> worker_timeout</td><td>60 </td></tr><tr><td> slurm_use_srun</td><td>False </td></tr><tr><td> time</td><td>2400 </td></tr><tr><td> partition</td><td>barnard </td></tr><tr><td> reservation</td><td>None </td></tr><tr><td> force_local_execution</td><td>False </td></tr><tr><td> slurm_signal_delay_s</td><td>0 </td></tr><tr><td> nodes_per_job</td><td>1 </td></tr><tr><td> cpus_per_task</td><td>1 </td></tr><tr><td> account</td><td>None </td></tr><tr><td> gpus</td><td>0 </td></tr><tr><td> run_mode</td><td>local </td></tr><tr><td> verbose</td><td>False </td></tr><tr><td> verbose_break_run_search_table</td><td>False </td></tr><tr><td> debug</td><td>False </td></tr><tr><td> flame_graph</td><td>False </td></tr><tr><td> no_sleep</td><td>False </td></tr><tr><td> tests</td><td>False </td></tr><tr><td> show_worker_percentage_table_at_end</td><td>False </td></tr><tr><td> auto_exclude_defective_hosts</td><td>False </td></tr><tr><td> run_tests_that_fail_on_taurus</td><td>False </td></tr><tr><td> raise_in_eval</td><td>False </td></tr><tr><td> show_ram_every_n_seconds</td><td>0 </td></tr><tr><td> show_generation_and_submission_sixel</td><td>False </td></tr><tr><td> just_return_defaults</td><td>False </td></tr><tr><td> prettyprint</td><td>False </td></tr></tbody></table>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' /> Worker-Usage</h1>
<div class='invert_in_dark_mode' id='workerUsagePlot'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download »worker_usage.csv« as file</button>
<pre id="pre_tab_worker_usage">1753189707.2124057,50,0,0
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1753243800.6363833,50,16,32
1753243800.6639497,50,16,32
1753243800.8167684,50,16,32
1753243801.5309062,50,16,32
1753243801.8210936,50,16,32
1753243801.8814478,50,16,32
1753243801.9467032,50,16,32
1753244201.2256777,50,0,0
1753244203.2482765,50,0,0
1753244203.4380264,50,0,0
1753244203.5206378,50,0,0
1753244203.5614247,50,0,0
1753244205.4917586,50,0,0
1753244206.322332,50,0,0
1753244206.528631,50,0,0
1753244207.2872674,50,0,0
1753244207.4731157,50,0,0
1753244209.3836005,50,0,0
1753244560.4650116,50,0,0
1753244582.4864013,50,0,0
1753244585.0565531,50,2,4
1753244587.3163657,50,4,8
1753244587.9642837,50,4,8
1753244588.0085242,50,4,8
1753244588.4278438,50,4,8
1753244590.016429,50,5,10
1753244593.77197,50,7,14
1753244593.9185736,50,8,16
1753244593.9923942,50,8,16
1753244594.8766806,50,8,16
1753244596.016529,50,11,22
1753244597.588887,50,11,22
1753244597.618876,50,11,22
1753244598.2115161,50,11,22
1753244978.934369,50,1,2
1753244983.843162,50,2,4
1753244984.5725515,50,2,4
1753245002.739217,50,3,6
1753245002.9699576,50,3,6
1753245005.9298363,50,3,6
1753245338.8232055,50,0,0
1753245349.2607732,50,1,2
1753245357.485024,50,1,2
1753245412.551866,50,0,0
1753245413.3318467,50,0,0
1753245414.972508,50,0,0
1753245415.8318574,50,0,0
1753245416.496686,50,0,0
1753245416.8413494,50,0,0
1753245418.569276,50,0,0
1753245419.0646846,50,0,0
1753245420.125194,50,0,0
1753245421.5894685,50,0,0
1753245421.6955495,50,0,0
1753245746.435867,50,1,2
1753245748.1340683,50,1,2
1753245758.385189,50,2,4
1753245764.9085038,50,2,4
1753245806.1928625,50,2,4
1753245812.0363007,50,5,10
1753245812.7743294,50,6,12
1753245814.2872515,50,7,14
1753245814.6185372,50,7,14
1753245815.3762465,50,7,14
1753245817.9262893,50,9,18
1753245820.373474,50,12,24
1753245821.1370947,50,13,26
1753245821.1942582,50,13,26
1753245821.6129506,50,13,26
1753245822.9533806,50,13,26
1753246159.7724862,50,14,28
1753246175.139957,50,15,30
1753246177.3344767,50,15,30
1753246220.6876063,50,16,32
1753246344.4365404,50,1,2
1753246445.058827,50,0,0
1753246445.5209835,50,0,0
1753246446.4902442,50,0,0
1753246446.510269,50,0,0
1753246446.7309668,50,0,0
1753246446.972972,50,0,0
1753246446.9821444,50,0,0
1753246447.0191872,50,0,0
1753246447.0794492,50,0,0
1753246447.181185,50,0,0
1753246447.5709739,50,0,0
1753246447.6277475,50,0,0
1753246447.6626973,50,0,0
1753246447.7089224,50,0,0
1753246447.7532332,50,0,0
1753246448.0383291,50,0,0
1753246448.3236263,50,0,0
1753246448.7198951,50,0,0
1753246449.4492605,50,0,0
1753246449.6392298,50,0,0
1753246449.7015655,50,0,0
1753246449.7819946,50,0,0
1753246450.8475883,50,0,0
1753246451.448468,50,0,0
1753246451.4706817,50,0,0
1753246451.6932914,50,0,0
1753246452.3862379,50,0,0
1753246452.8344367,50,0,0
1753246453.0017567,50,0,0
1753246453.125861,50,0,0
1753246454.255837,50,0,0
1753246454.469984,50,0,0
1753247267.8856695,50,0,0
1753247269.7443807,50,0,0
1753247269.8116083,50,0,0
1753247270.1251733,50,0,0
1753247271.2784429,50,0,0
1753247272.7889194,50,0,0
1753247273.352608,50,0,0
1753247273.36104,50,0,0
1753247273.779862,50,0,0
1753247273.8090372,50,0,0
1753247280.2917678,50,0,0
1753247281.593822,50,0,0
1753247296.7244096,50,0,0
1753247296.978789,50,0,0
1753247297.2880907,50,0,0
1753247297.3868835,50,0,0
1753247297.419098,50,0,0
1753247297.5253851,50,0,0
1753247776.4311693,50,0,0
1753247812.7575724,50,0,0
1753247812.9249675,50,0,0
1753247815.3376403,50,0,0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download »worker_usage.csv« as file</button>
<h1><img class='invert_icon' src='i/cpu.svg' style='height: 1em' /> CPU/RAM-Usage (main)</h1>
<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download »cpu_ram_usage.csv« as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1753189697,646.7578125,26.2
1753189707,647.015625,25.1
1753189712,647.38671875,24.4
1753189712,647.38671875,18.5
1753189713,647.64453125,24.3
1753189713,647.64453125,25.0
1753189713,647.64453125,25.6
1753191773,731.7734375,29.4
1753191773,731.7734375,27.8
1753191774,731.7734375,23.4
1753191774,731.7734375,16.0
1753195160,797.4140625,16.1
1753195160,797.4140625,18.7
1753195160,797.4140625,14.8
1753195160,797.4140625,15.0
1753199334,828.75,15.2
1753199334,828.75,14.7
1753199334,828.75,14.9
1753199334,828.75,20.0
1753203520,856.85546875,14.9
1753203520,856.85546875,17.6
1753203521,856.85546875,14.2
1753203521,856.85546875,21.4
1753209737,859.828125,14.8
1753209737,859.828125,12.7
1753209737,859.828125,14.2
1753209737,859.828125,21.4
1753215819,914.84765625,14.8
1753215819,914.84765625,15.8
1753215819,914.84765625,14.3
1753215819,914.84765625,14.3
1753222643,974.59765625,14.8
1753222643,974.59765625,17.6
1753222643,974.59765625,14.3
1753230276,997.90234375,14.8
1753230276,997.90234375,15.8
1753230276,997.90234375,14.4
1753238536,1034.3828125,14.8
1753238536,1034.3828125,15.8
1753238536,1034.3828125,14.3
1753238536,1034.3828125,20.0
1753247812,1098.640625,14.8
1753247812,1098.640625,18.8
1753247812,1098.640625,14.3
1753247815,1090.8125,14.4
1753247815,1090.8125,20.0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download »cpu_ram_usage.csv« as file</button>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' /> Param-Distrib by Status</h1>
<div class='invert_in_dark_mode' id='parameter_by_status_distribution'></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' /> Timeline</h1>
<div class="invert_in_dark_mode" id="plot_timeline"></div>
</body>
</html>