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Itaicaspi/episode reset refactoring (#105)

* reordering of the episode reset operation and allowing to store episodes only when they are terminated

* reordering of the episode reset operation and allowing to store episodes only when they are terminated

* revert tensorflow-gpu to 1.9.0 + bug fix in should_train()

* tests readme file and refactoring of policy optimization agent train function

* Update README.md

* Update README.md

* additional policy optimization train function simplifications

* Updated the traces after the reordering of the environment reset

* docker and jenkins files

* updated the traces to the ones from within the docker container

* updated traces and added control suite to the docker

* updated jenkins file with the intel proxy + updated doom basic a3c test params

* updated line breaks in jenkins file

* added a missing line break in jenkins file

* refining trace tests ignored presets + adding a configurable beta entropy value

* switch the order of trace and golden tests in jenkins + fix golden tests processes not killed issue

* updated benchmarks for dueling ddqn breakout and pong

* allowing dynamic updates to the loss weights + bug fix in episode.update_returns

* remove docker and jenkins file
This commit is contained in:
Itai Caspi
2018-09-04 15:07:54 +03:00
committed by GitHub
parent 7086492127
commit 72a1d9d426
92 changed files with 9803 additions and 9740 deletions

View File

@@ -3,29 +3,19 @@ Episode #,Training Iter,In Heatup,ER #Transitions,ER #Episodes,Episode Length,To
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28,1083.0,0.0,5387.0,5387.0,140.0,5387.0,0.9961030000001284,1.0,20.0,0.0,,,,0.004326820851253745,0.0064877273362216065,0.015882819890975952,0.00010518966882955284,0.0001,1.3552527156068802e-20,0.0001,0.0001,0.027057504,0.023942256000000002,0.07126255,0.006638075699999999,,,,
29,1131.0,0.0,5581.0,5581.0,194.0,5581.0,0.9959284000001339,4.0,60.0,0.0,,,,0.008834963679722327,0.008607911806343238,0.03031262755393982,0.000106745348602999,0.0001,0.0,0.0001,0.0001,0.045785952000000005,0.027331235,0.11430588,0.0062478506,,,,
30,1236.0,0.0,6002.0,6002.0,421.0,6002.0,0.9955495000001464,8.0,125.0,0.0,,,,0.006107945965985503,0.007809515316612659,0.03002355806529522,0.00015217895270325243,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.035095777,0.025743425,0.101090685,0.008217704499999999,,,,
5,51.0,0.0,1260.0,1260.0,203.0,1260.0,0.999817300000006,5.0,55.0,0.0,,,,0.011153367854907023,0.015027035375515356,0.0589878261089325,8.134254312608391e-05,0.00010000000000000002,1.3552527156068802e-20,0.0001,0.0001,0.04883443,0.041394312,0.19476563,0.006623836700000001,,,,
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1 Episode # Training Iter In Heatup ER #Transitions ER #Episodes Episode Length Total steps Epsilon Shaped Training Reward Training Reward Update Target Network Evaluation Reward Shaped Evaluation Reward Success Rate Loss/Mean Loss/Stdev Loss/Max Loss/Min Learning Rate/Mean Learning Rate/Stdev Learning Rate/Max Learning Rate/Min Grads (unclipped)/Mean Grads (unclipped)/Stdev Grads (unclipped)/Max Grads (unclipped)/Min Q/Mean Q/Stdev Q/Max Q/Min
3 2 0.0 1.0 573.0 573.0 87.0 573.0 1.0 0.0
4 3 0.0 1.0 722.0 722.0 149.0 722.0 1.0 0.0
5 4 0.0 1.0 1057.0 1057.0 335.0 1057.0 1.0 0.0
6 5 51.0 0.0 1260.0 1260.0 203.0 1260.0 0.999817300000006 3.0 5.0 30.0 55.0 0.0 0.009654946979186634 0.011153367854907023 0.013951627370580843 0.015027035375515356 0.04929021373391152 0.0589878261089325 0.0001001853379420936 8.134254312608391e-05 0.00010000000000000002 1.3552527156068802e-20 0.0001 0.0001 0.042711925 0.04883443 0.038432162 0.041394312 0.14662997 0.19476563 0.008449959 0.006623836700000001
7 6 116.0 70.0 0.0 1519.0 1335.0 1519.0 1335.0 259.0 75.0 1519.0 1335.0 0.9995842000000136 0.9997498000000082 3.0 2.0 30.0 15.0 0.0 0.009395824597763398 0.01147703626683276 0.010559114500164793 0.011325970191239728 0.04425281286239624 0.030307751148939133 0.0001856916933320463 0.0004829707322642207 0.00010000000000000002 0.0001 1.3552527156068802e-20 0.0 0.0001 0.0001 0.046624955 0.056145836 0.030083885 0.026853915 0.14953406 0.10600656 0.013629041000000001 0.024553476
8 7 154.0 91.0 0.0 1673.0 1422.0 1673.0 1422.0 154.0 87.0 1673.0 1422.0 0.9994456000000184 0.9996715000000108 0.0 1.0 0.0 15.0 0.0 0.006763404418483046 0.011548659179381849 0.007932211375540843 0.013730809899124057 0.02884973213076592 0.043242335319519036 0.00011230179370613767 0.0003053410327993333 9.999999999999998e-05 0.0001 2.7105054312137605e-20 1.3552527156068802e-20 0.0001 0.0001 0.03772134 0.059877775999999994 0.024497243 0.03687902 0.086253904 0.13717306 0.008246866 0.020375967
9 8 188.0 159.0 0.0 1809.0 1693.0 1809.0 1693.0 136.0 271.0 1809.0 1693.0 0.9993232000000224 0.9994276000000188 0.0 5.0 0.0 55.0 0.0 0.00579419282696429 0.008716323934434634 0.009409663949944837 0.010617909178954029 0.03068150021135807 0.0430009663105011 0.00011524958244990556 0.00019797885033767668 0.0001 0.00010000000000000003 1.3552527156068802e-20 2.7105054312137605e-20 0.0001 0.0001 0.033371154 0.04758673 0.03126849 0.03171387 0.13397211 0.13769212 0.010591073000000001 0.011469088999999998
10 9 218.0 201.0 0.0 1927.0 1861.0 1927.0 1861.0 118.0 168.0 1927.0 1861.0 0.9992170000000258 0.9992764000000238 4.0 3.0 50.0 0.0 0.005470155894242149 0.005772166230252921 0.008703123279081676 0.009313748713790294 0.02919070795178413 0.04269432276487351 7.498881313949823e-05 0.0001282592274947092 9.999999999999998e-05 0.00010000000000000002 2.7105054312137605e-20 1.3552527156068802e-20 0.0001 0.0001 0.03059395 0.034678657 0.028292075 0.027940277000000003 0.10207387 0.1290576 0.006532367 0.008978493
11 10 239.0 279.0 0.0 2013.0 2172.0 2013.0 2172.0 86.0 311.0 2013.0 2172.0 0.9991396000000284 0.9989965000000329 1.0 4.0 25.0 65.0 0.0 0.007070470374726158 0.00966654376334657 0.01125100662056102 0.012455670221574441 0.04263514280319214 0.05754233151674271 9.615141607355326e-05 6.935953570064156e-05 0.0001 0.00010000000000000003 1.3552527156068802e-20 4.0657581468206416e-20 0.0001 0.0001 0.038667627 0.048503987 0.033031862 0.037041757 0.13103388 0.1568195 0.009553337 0.006075088
12 11 285.0 406.0 0.0 2197.0 2681.0 2197.0 2681.0 184.0 509.0 2197.0 2681.0 0.9989740000000338 0.998538400000048 5.0 9.0 75.0 320.0 0.0 0.004922990176767243 0.008286195846002249 0.009157177817938416 0.010238034143861922 0.0440991148352623 0.044422760605812066 5.839417281094938e-05 0.00014633702812716365 0.00010000000000000003 0.0001 2.7105054312137605e-20 1.3552527156068802e-20 0.0001 0.0001 0.02870986 0.04592845 0.029140014 0.030503508 0.12825716 0.14186455 0.005925636999999999 0.0110354535 0.03322521 0.015940087 0.056609314 0.0076417234
13 12 309.0 471.0 0.0 2293.0 2941.0 2293.0 2941.0 96.0 260.0 2293.0 2941.0 0.9988876000000366 0.9983044000000558 2.0 7.0 15.0 110.0 0.0 0.004973496080917054 0.009545503650756123 0.007834190985915203 0.012811965745234155 0.027832549065351486 0.05728550255298615 0.00011880028614541516 0.00014954243670217693 0.0001 0.00010000000000000002 0.0 1.3552527156068802e-20 0.0001 0.0001 0.029258594 0.04835386 0.024372704 0.03174918 0.0919232 0.15212412 0.009084637 0.012202092
14 13 353.0 506.0 0.0 2467.0 3082.0 2467.0 3082.0 174.0 141.0 2467.0 3082.0 0.9987310000000418 0.99817750000006 2.0 0.0 35.0 0.0 0.0 0.0045068665432071685 0.007986091597038987 0.007321273060575792 0.010227653459912332 0.02869480662047863 0.029147621244192123 6.573591963388026e-05 0.00018407590687274933 0.00010000000000000003 0.0001 2.7105054312137605e-20 1.3552527156068802e-20 0.0001 0.0001 0.027796077000000002 0.043641995999999995 0.025970899 0.03191385 0.09446095 0.11431264 0.0046847034 0.012298575
15 14 400.0 569.0 0.0 2658.0 3331.0 2658.0 3331.0 191.0 249.0 2658.0 3331.0 0.9985591000000474 0.9979534000000674 1.0 7.0 25.0 110.0 0.0 0.00977239356019554 0.007928447468833427 0.010343679461906952 0.009549152818479286 0.030321182683110237 0.04228781163692474 0.00018286058912053704 0.00013459150795824826 0.00010000000000000003 4.0657581468206416e-20 2.7105054312137605e-20 0.0001 0.0001 0.048518963 0.04425544 0.02922272 0.03010041 0.11681272 0.13962811 0.009786125 0.0104794 0.050078813 0.025057722 0.08571987 0.020499324
16 15 420.0 655.0 0.0 2737.0 3677.0 2737.0 3677.0 79.0 346.0 2737.0 3677.0 0.9984880000000498 0.9976420000000776 3.0 0.0 30.0 0.0 0.0 0.008876862422766862 0.009116127458434866 0.009404707731271193 0.010233341520914018 0.028901334851980213 0.03874828293919563 0.00018610457482282072 0.00016095259343273938 0.0001 9.999999999999998e-05 0.0 2.7105054312137605e-20 0.0001 0.0001 0.04794182599999999 0.05015296 0.029056482 0.030124526000000002 0.12552716 0.13494284 0.015941316 0.012318888 0.036954846 0.016541163 0.06137629 0.0047242693
17 16 441.0 674.0 0.0 2822.0 3753.0 2822.0 3753.0 85.0 76.0 2822.0 3753.0 0.9984115000000524 0.99757360000008 1.0 20.0 10.0 0.0 0.011170348666685944 0.005457259488665793 0.009764524297967085 0.006725242317819629 0.030193831771612167 0.015414755791425703 0.0002611538511700928 0.00018984619237016886 0.0001 1.3552527156068802e-20 0.0 0.0001 0.0001 0.05474482 0.036532152000000005 0.031951982999999996 0.022897648 0.13531010000000002 0.06911852 0.01605481 0.013080008999999998
18 17 529.0 723.0 0.0 3174.0 3948.0 3174.0 3948.0 352.0 195.0 3174.0 3948.0 0.9980947000000628 0.9973981000000856 6.0 0.0 105.0 0.0 0.0 0.008561450651871961 0.006345583730150366 0.010388056521305884 0.01018264769961162 0.04236683994531632 0.0397307351231575 0.00017452481552027166 9.957021393347532e-05 0.00010000000000000003 0.00010000000000000002 2.7105054312137605e-20 1.3552527156068802e-20 0.0001 0.0001 0.044565108 0.03886488 0.029229562999999997 0.038184277999999995 0.12811051 0.14176919 0.012664802 0.006970413000000001
19 18 618.0 754.0 0.0 3527.0 4073.0 3527.0 4073.0 353.0 125.0 3527.0 4073.0 0.9977770000000732 0.9972856000000894 4.0 2.0 80.0 15.0 0.0 0.007443786804798762 0.006026781925503465 0.010177603763426246 0.007350232007724398 0.04463248327374458 0.026275455951690674 6.0651469539152465e-05 0.00017769451369531453 0.00010000000000000002 9.999999999999996e-05 1.3552527156068802e-20 4.0657581468206416e-20 0.0001 0.0001 0.03917629 0.043348733 0.02873507 0.027256972999999997 0.13048278 0.12586276 0.0059215119999999994 0.011062483 0.026613249 0.008946453 0.04138826 0.013779217
20 19 638.0 831.0 0.0 3610.0 4381.0 3610.0 4381.0 83.0 308.0 3610.0 4381.0 0.9977023000000756 0.9970084000000984 1.0 4.0 10.0 90.0 0.0 0.00947287489034352 0.006534161396810706 0.009120686342052368 0.009079722555863916 0.02835406921803952 0.039741791784763336 0.00023163050354924053 7.733125676168129e-05 0.0001 0.00010000000000000003 0.0 2.7105054312137605e-20 0.0001 0.0001 0.04728116 0.042101186 0.025211213 0.03250519 0.08812934 0.15925613 0.015696856999999998 0.0062198965000000005
21 20 674.0 933.0 0.0 3754.0 4789.0 3754.0 4789.0 144.0 408.0 3754.0 4789.0 0.99757270000008 0.9966412000001106 0.0 5.0 0.0 35.0 0.0 0.006512744492485783 0.007308699939826244 0.01084231610224011 0.009906021263269732 0.054297078400850296 0.05427439138293266 0.00013670953921973703 0.00011632483074208723 0.0001 1.3552527156068802e-20 0.0001 0.0001 0.039536193 0.04225955 0.03681436 0.031486627 0.19717765 0.17579086 0.009255781999999999 0.0077312537 0.029463767999999998 0.026419535 0.013992969 0.01425859 0.055506807000000005 0.05756532 0.011549842 0.014857713
21 703.0 0.0 3869.0 3869.0 115.0 3869.0 0.9974692000000832 4.0 55.0 0.0 0.007595785371638064 0.01278862092663838 0.0568322204053402 0.00016743995365686717 9.999999999999998e-05 2.7105054312137605e-20 0.0001 0.0001 0.038325354 0.03308432 0.14259322 0.008637958000000001
22 724.0 0.0 3953.0 3953.0 84.0 3953.0 0.9973936000000858 2.0 50.0 0.0 0.0057669557267910855 0.009239934908058463 0.02947502583265305 0.00018409341282676905 0.0001 1.3552527156068802e-20 0.0001 0.0001 0.03457182 0.026093084 0.09026415 0.0123431515
23 784.0 0.0 4192.0 4192.0 239.0 4192.0 0.9971785000000928 5.0 75.0 0.0 0.00809967934183078 0.01036380041696798 0.041483376175165176 0.00016024033538997173 0.00010000000000000003 2.7105054312137605e-20 0.0001 0.0001 0.04329346 0.031746197000000004 0.14067882 0.009837331999999999
24 831.0 0.0 4380.0 4380.0 188.0 4380.0 0.9970093000000984 0.0 0.0 0.0 0.006891696457813018 0.007546929211673221 0.029366210103034977 0.0002085421874653548 0.00010000000000000003 4.0657581468206416e-20 0.0001 0.0001 0.040272716 0.023695845 0.08822828 0.010775305
25 906.0 0.0 4681.0 4681.0 301.0 4681.0 0.9967384000001074 7.0 80.0 0.0 0.007030442795269968 0.008971783795469862 0.029756365343928337 9.572327689966188e-05 0.00010000000000000003 2.7105054312137605e-20 0.0001 0.0001 0.040413715 0.029355139 0.10548375 0.0072385157 0.041193675 0.02736831 0.07621856 0.00037608482000000003
26 959.0 0.0 4893.0 4893.0 212.0 4893.0 0.9965476000001136 3.0 30.0 0.0 0.007057454745765151 0.009452664953293057 0.030209349468350414 0.00010792172543006018 0.00010000000000000003 2.7105054312137605e-20 0.0001 0.0001 0.039197296 0.027908783 0.104838766 0.008230781
27 1048.0 0.0 5247.0 5247.0 354.0 5247.0 0.9962290000001242 5.0 75.0 0.0 0.008188762073535891 0.009436714275711092 0.04216104745864868 0.00015023039304651317 0.00010000000000000002 1.3552527156068802e-20 0.0001 0.0001 0.044641394 0.028307599999999995 0.12660655 0.00902969
28 1083.0 0.0 5387.0 5387.0 140.0 5387.0 0.9961030000001284 1.0 20.0 0.0 0.004326820851253745 0.0064877273362216065 0.015882819890975952 0.00010518966882955284 0.0001 1.3552527156068802e-20 0.0001 0.0001 0.027057504 0.023942256000000002 0.07126255 0.006638075699999999
29 1131.0 0.0 5581.0 5581.0 194.0 5581.0 0.9959284000001339 4.0 60.0 0.0 0.008834963679722327 0.008607911806343238 0.03031262755393982 0.000106745348602999 0.0001 0.0 0.0001 0.0001 0.045785952000000005 0.027331235 0.11430588 0.0062478506
30 1236.0 0.0 6002.0 6002.0 421.0 6002.0 0.9955495000001464 8.0 125.0 0.0 0.006107945965985503 0.007809515316612659 0.03002355806529522 0.00015217895270325243 0.00010000000000000002 1.3552527156068802e-20 0.0001 0.0001 0.035095777 0.025743425 0.101090685 0.008217704499999999