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DL之LSTM之MvP:基于TF利用LSTM基于DIY时间训练csv文件数据预测后100个数据(多值预测)状态

發(fā)布時(shí)間:2025/3/21 编程问答 23 豆豆
生活随笔 收集整理的這篇文章主要介紹了 DL之LSTM之MvP:基于TF利用LSTM基于DIY时间训练csv文件数据预测后100个数据(多值预测)状态 小編覺得挺不錯(cuò)的,現(xiàn)在分享給大家,幫大家做個(gè)參考.

DL之LSTM之MvP:基于TF利用LSTM基于DIY時(shí)間訓(xùn)練csv文件數(shù)據(jù)預(yù)測后100個(gè)數(shù)據(jù)(多值預(yù)測)狀態(tài)

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目錄

數(shù)據(jù)集csv文件內(nèi)容

輸出結(jié)果

設(shè)計(jì)思路

訓(xùn)練記錄全過程


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數(shù)據(jù)集csv文件內(nèi)容

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輸出結(jié)果

設(shè)計(jì)思路

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訓(xùn)練記錄全過程

2018-10-17 14:33:28.811258: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce 940MX, pci bus id: 0000:01:00.0, compute capability: 5.0) INFO:tensorflow:Saving checkpoints for 1 into C:\Users\……\AppData\Local\Temp\tmpxvos_wek\model.ckpt. INFO:tensorflow:loss = 1.99025, step = 1 INFO:tensorflow:global_step/sec: 12.7154 INFO:tensorflow:loss = 0.407616, step = 101 (7.870 sec) INFO:tensorflow:Saving checkpoints for 200 into C:\Users\……\AppData\Local\Temp\tmpxvos_wek\model.ckpt. INFO:tensorflow:Loss for final step: 0.159871. INFO:tensorflow:Starting evaluation at 2018-10-17-06:33:55 2018-10-17 14:33:55.520513: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce 940MX, pci bus id: 0000:01:00.0, compute capability: 5.0) INFO:tensorflow:Restoring parameters from C:\Users\……\AppData\Local\Temp\tmpxvos_wek\model.ckpt-200 INFO:tensorflow:Evaluation [1/1] INFO:tensorflow:Finished evaluation at 2018-10-17-06:33:56 INFO:tensorflow:Saving dict for global step 200: global_step = 200, loss = 0.0914701, mean = [[[-0.02258123 1.20125902 2.46149969 3.74098039 5.00599146][-0.72656935 1.46578288 2.55133963 3.57579684 4.71380329][-0.93369555 1.27410793 2.461622 3.36797333 4.47852659][-0.28303617 1.04424524 2.28791738 3.17969871 4.3186183 ][ 0.03985038 0.77593756 2.13191533 3.18373418 4.19481421][-0.59239888 0.47297943 1.80378556 3.25553274 4.16365004][-0.78655541 0.5069496 1.60384321 3.120368 4.42847204][ 0.16859503 0.73337585 1.61688042 3.07779312 4.62821817][ 0.75624537 1.12221634 1.78613925 3.33996463 4.76050758][-0.18138258 1.6589669 2.04715395 3.553339 4.89331532][-0.85793096 1.92421985 2.32753062 3.51988888 5.09496164][ 0.27542502 2.20485401 2.57294631 3.66244674 5.32275152][ 1.0331111 2.32110286 2.92849159 3.74277306 5.4806776 ][-0.31996989 2.0762732 3.00064945 3.91731429 5.53373528][-1.13102674 1.54052997 3.18407869 4.14603806 5.69867373][ 0.28646153 1.02832162 3.37013149 4.43634033 5.75095129][ 1.00686896 0.58188593 3.53338814 4.49843788 5.85889435][-0.51223803 0.2763325 3.41038799 4.54861832 5.83758831][-1.0338639 0.21294475 3.2338388 4.72177982 5.83597088][ 0.26228762 0.40723181 3.15446091 4.76411152 5.85220051][ 0.76278716 0.66311061 3.03175783 4.69197798 5.87075472][-0.45436215 1.13117456 2.76854038 4.61343575 5.85332823][-0.87863731 1.54986215 2.33939052 4.57823992 5.82480431][ 0.39277369 1.8990984 2.10363054 4.42317438 5.8106041 ][ 0.99085194 2.13706136 1.87079835 4.18970537 5.8008256 ][-0.52076232 2.05188704 1.74643803 4.05304956 5.72936773][-0.97566265 1.69756258 1.62115216 3.93999577 5.57423878][ 0.43046591 1.39184296 1.65154696 3.71441293 5.45222044][ 0.88588709 1.04985034 1.66515064 3.51741457 5.32099676][-0.72021019 0.54022431 1.68251848 3.34307003 5.02586746][-0.99685818 0.29293615 1.81516552 3.04635096 4.92267561][ 0.44880253 0.35789663 2.05799055 2.88136172 4.85719347][ 0.79797494 0.61584455 2.40396357 2.89541912 4.63176489][-0.65483415 0.94648749 2.64026642 2.83008909 4.46917629][-0.80363208 1.36413217 2.76368833 2.73575735 4.34707785][ 0.62078804 1.82089138 2.99507046 2.72794437 4.23858547][ 0.76629472 2.19677806 3.32607484 2.82271099 4.09487867][-0.78800523 2.26259255 3.48484802 2.91107988 3.99762201][-0.75864941 2.10827589 3.51060867 2.99060631 4.02838755][ 0.78492832 1.87137747 3.5965333 3.09973478 4.06794024][ 0.6314953 1.40174592 3.51098204 3.28556228 3.97504044][-0.83633691 0.80587745 3.15457964 3.51566696 4.00417137][-0.6733321 0.45035005 2.85752249 3.7064538 4.15681696][ 0.68248016 0.20115876 2.60771561 3.91507864 4.24229527][ 0.62391466 0.21057343 2.31893015 4.1396451 4.15356827][-0.80487281 0.54158294 2.04153323 4.40795135 4.19229746][-0.69418651 1.03371727 1.8360095 4.52020407 4.39075708][ 0.78446406 1.38377047 1.67458987 4.57382059 4.57684278][ 0.55859393 1.90988648 1.54792333 4.67716694 4.6954608 ][-0.97675616 2.15290236 1.39113235 4.73126888 4.91898394][-0.54306972 2.15442061 1.46775818 4.77496624 5.09109259][ 0.76895946 2.07765841 1.506634 4.75528717 5.2398057 ][ 0.34301981 1.68889821 1.67374158 4.69288206 5.39653444][-0.91761684 1.13869679 1.91118884 4.60692167 5.49643993][-0.47333306 0.69090563 2.23274636 4.49918842 5.56999016][ 0.80657309 0.3588593 2.67364287 4.30588436 5.63451719][ 0.52129406 0.28135842 3.03734875 4.08425713 5.72058821][-0.87032658 0.30913079 3.13875175 3.87309504 5.82510281][-0.38541344 0.58203012 3.22977924 3.70223856 5.87730312][ 0.92312407 0.97287679 3.4374516 3.46826148 5.92560816][ 0.38667771 1.57088554 3.57924008 3.18373251 5.97714472][-0.96847367 1.95864582 3.46318865 2.99153256 5.9243679 ][-0.29042897 2.15955973 3.28767014 2.92731619 5.80609179][ 1.05476689 2.23997283 3.10138607 2.74227214 5.72408485][ 0.26864958 1.96871543 2.81539583 2.67804813 5.64276505][-1.11794412 1.45112896 2.54433537 2.77567339 5.55643272][-0.26396298 0.96271485 2.42007947 2.90135527 5.47261381][ 1.02105784 0.71554309 2.19740963 2.93254256 5.33089495][ 0.08677568 0.34677446 1.87187743 3.03682566 5.10183382][-1.11194074 0.15401816 1.66281927 3.15410566 4.97747374][-0.12272341 0.30180877 1.52159286 3.18472672 4.94240236][ 0.98251247 0.69807512 1.54382443 3.46032691 4.70980072][ 0.04094632 1.22731531 1.67413783 3.83074236 4.43305254][-1.00694048 1.65609658 1.762411 4.03825426 4.34276962][-0.05897149 2.0092473 1.91996717 4.16084623 4.32943392][ 0.91650641 2.22678471 2.12102604 4.30212688 4.19473886][-0.03337113 2.1746881 2.37334609 4.39889717 4.02976465][-1.0127815 1.92308354 2.61303473 4.56022596 3.94330001][ 0.01059423 1.54359317 2.90251637 4.71572495 3.96141529][ 1.03956962 1.11690688 3.25370812 4.86467266 3.97466874][ 0.09197591 0.67883945 3.38240027 4.86860847 3.96421003][-0.84794611 0.28496414 3.42090082 4.82572269 4.04805946][ 0.21027137 0.17020655 3.4868753 4.69520617 4.18217802][ 1.01854718 0.26949811 3.63699007 4.57096434 4.17454147][-0.22191104 0.68545365 3.378582 4.41910028 4.15620136][-0.97954774 1.18409562 3.06682301 4.31807613 4.28068304][ 0.37906742 1.62706232 2.79079866 4.16520739 4.43478918][ 1.10579622 2.03329659 2.54347825 3.92974758 4.61650276][-0.28453454 2.20910454 2.19329453 3.73508215 4.73528385][-1.03763247 2.18529534 1.81834531 3.66158772 4.93438673][ 0.22151242 1.97848916 1.63359141 3.46144772 5.14855433][ 0.96506304 1.52342212 1.46656311 3.22499657 5.37121248][-0.28004175 0.94278771 1.38676071 3.07118821 5.54157686][-0.78861243 0.53288817 1.50251698 2.868891 5.65895605][ 0.37555215 0.3845585 1.7211839 2.72783947 5.80253601][ 0.71072179 0.35191894 1.86516833 2.74501562 5.87327385][-0.66796905 0.4802804 2.06942296 2.74930239 5.83967638][-0.91003895 0.74719334 2.2557373 2.69235229 5.83291674][ 0.46069285 1.3816551 2.70611811 2.81655002 5.91043425][ 0.89528 1.958776 3.00707531 2.85689092 5.92750597]]], observed = [[[ 0.92690629 1.99107242 2.56546235 3.07914758 4.04839039][ 0.10801 1.4164536 2.16868401 2.94963956 4.1263504 ][-0.80056763 1.01721334 1.96434748 2.99885345 4.04300499][ 0.06070429 0.71954006 1.97650123 2.89265585 4.09510136][ 0.93371218 0.28052121 1.41018558 2.69232607 4.06481171][-0.17173065 0.26005441 1.48770821 2.6219914 4.4457283 ][-1.00180161 0.33304515 1.5000639 2.88888311 4.24755859][ 0.05800619 0.68892938 1.56543458 2.99840355 4.52726889][ 0.76413947 1.24704874 1.77649283 3.13578606 4.63238907][-0.23033187 1.47904003 2.03547549 3.20624042 4.77979994][-1.03846049 2.01132989 2.3197751 3.67951536 5.09716797][ 0.18864359 2.23285341 2.6833849 3.49817157 5.24928236][ 0.91207302 2.24244452 2.71362615 3.96332598 5.37802267][-0.29658866 2.02594638 3.07733917 3.99698329 5.56365919][-0.95996147 1.45078635 3.18996429 4.37630606 5.65356016][ 0.4631353 1.01141441 3.4980216 4.20224905 5.88842249][ 0.92935413 0.62663531 3.70508265 4.51791573 5.73945951][-0.51911074 0.26924923 3.39866829 4.46801996 5.82768154][-0.92433101 0.34960285 3.21762419 4.72803593 5.94918919][ 0.25323939 0.34515801 3.1107142 4.79311562 5.94892597][ 0.63740838 0.69899666 3.25232482 4.73814726 5.96120119][-0.40739685 1.17456341 2.49526834 4.59323406 5.82501698][-0.96748543 1.66655934 2.47284603 4.5831604 5.88721418][ 0.47448087 1.95018554 2.0228951 4.48651123 5.82559443][ 1.04309654 2.23519897 1.91924131 4.19094658 5.87457371][-0.51786149 2.12501979 1.70266616 4.05280876 5.72160912][-0.94530159 1.65464652 1.8156718 3.92309856 5.58270502][ 0.50115389 1.40600765 1.53991389 3.72853255 5.60168982][ 0.9728595 1.00344324 1.5175643 3.64092374 5.10567713][-0.70553404 0.46530625 1.70385408 3.33236861 5.09182501][-0.94609362 0.2945393 1.88052821 2.93011498 4.97354937][ 0.47922122 0.30846587 2.03445888 2.90772891 4.8624177 ][ 0.75402999 0.54975224 2.46115804 2.95063353 4.71834612][-0.64875948 0.89461547 2.59224629 2.8126986 4.4348011 ][-0.75782996 1.39123917 2.6925807 2.61834836 4.36580038][ 0.56565332 1.72360027 2.97794914 2.80403829 4.27327251][ 0.8674401 2.21100736 3.38648081 2.84057522 4.12210178][-0.89456779 2.17549109 3.45532489 2.90446019 4.00251722][-0.71544236 2.15105391 3.52041793 3.03650403 4.12809229][ 0.80671704 1.8150456 3.60463333 3.007478 3.98440766][ 0.52701479 1.31803513 3.43842196 3.33325958 4.03232384][-0.79593688 0.84780914 3.09875131 3.52863145 3.94883919][-0.61024582 0.42553043 2.9258194 3.77238727 4.27287245][ 0.61166227 0.17843205 2.48128223 3.73212099 4.17319012][ 0.65086657 0.22034165 2.41694641 4.26091003 4.27271652][-0.77415699 0.6326676 2.05474353 4.32889223 4.18029737][-0.71405846 0.92456239 1.75706136 4.52492714 4.39726782][ 0.88962728 1.46207964 1.78299356 4.64466715 4.56317902][ 0.52014065 1.89963341 1.4137764 4.48899078 4.78805065][-1.03816938 2.08997011 1.51218379 4.84167767 4.93026066][-0.40772951 2.30878973 1.44144416 4.76854467 5.01538467][ 0.79273069 1.91367054 1.58887386 4.71739388 5.25690031][ 0.37131187 1.67565084 1.81688559 4.60353088 5.44265842][-0.81439805 1.13374639 1.8032881 4.72264242 5.5267477 ][-0.46901795 0.60124415 2.29690886 4.4985919 5.54126167][ 0.8710444 0.4075976 2.74991131 4.19060659 5.57693768][ 0.52376491 0.24770519 3.09002066 4.02095509 5.80510378][-0.88132638 0.31513104 3.11358213 3.96079111 5.81000662][-0.35792804 0.48616391 3.17884564 3.72634983 5.85693645][ 0.85303879 1.0421809 3.45835376 3.36703968 5.95859861][ 0.43531153 1.5971508 3.63313341 3.11276722 5.93643808][-1.02703714 1.92205834 3.47606111 3.06247163 6.02106667][-0.24666132 2.14653802 3.29446316 2.89936256 5.67531538][ 1.02554739 2.25943732 3.07031584 2.78176212 5.78206348][ 0.33781448 2.07589149 2.80356216 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0.15530205 3.4977951 4.64605665 4.15571308][ 1.03531492 0.35970277 3.48807263 4.4816761 4.21134567][-0.26123458 0.71387774 3.42756438 4.42644405 4.25208282][-1.0357244 1.25001109 2.96908331 4.25500917 4.25723028][ 0.38003427 1.70543361 2.73605943 4.16703415 4.6370039 ][ 1.03734875 1.97544408 2.55586576 3.84976673 4.55282879][-0.17734425 2.22614527 2.09565854 3.77378106 4.82577419][-0.97682154 2.18385077 1.78522289 3.67768216 5.06302452][ 0.26482049 1.8698194 1.50048399 3.436198 5.0565176 ][ 1.05642343 1.47568643 1.51347673 3.20898509 5.50149059][-0.31160742 1.0422647 1.52089655 3.0229187 5.48890448][-0.72428578 0.55305231 1.48573565 2.7365973 5.72549152][ 0.51985919 0.22652063 1.61543727 2.84102082 5.69330645][ 1.03231955 0.26087323 1.8191303 2.83951139 5.90325022][-0.53285682 0.38769552 1.70935607 2.57977057 5.7957921 ][-0.975128 0.92094874 2.51292634 2.71004605 5.87016487][ 0.54024678 1.36445475 2.6194942 2.98482561 6.02447653][ 0.987764 1.85581994 2.84685707 2.94760203 6.02121496]]], start_tuple = (array([99], dtype=int64), array([[ 1.90218008, 1.28345549, 0.72423571, -1.54894197, 2.17917752]], dtype=float32), [array([[ -2.22468042e+00, -3.22739661e-01, -6.18114322e-02,4.74002242e-01, -5.23656420e-02, -2.63940424e-01,2.80045718e-02, 2.22113937e-01, 7.31745809e-02,-2.33156943e+00, -1.49744606e+00, 2.86370039e-01,3.30500484e-01, -1.84197664e-01, 5.84359467e-01,8.95263404e-02, 3.31098467e-01, -5.55595458e-02,2.19679937e-01, 4.66475964e-01, 1.00609207e+00,-6.80337191e-01, -9.78736401e+00, 1.32761359e+00,1.29839289e+00, 6.20648742e-01, 3.64024878e-01,-2.72545362e+00, -1.84842551e+00, 2.84402132e-01,-5.29527247e-01, 1.95285118e+00, 4.56424505e-01,-4.28236783e-01, 9.59175944e-01, 1.41466355e+00,2.62957931e-01, 1.93796530e-01, -9.76036131e-01,1.28407359e+00, -1.97707772e-01, 2.88512230e+00,8.32995594e-01, -5.32110453e-01, -2.57556462e+00,-1.12045264e+00, -4.03596491e-01, 3.89896929e-01,-3.27839553e-01, 7.90456533e-01, -2.83772707e-01,-8.22015524e-01, 6.61805272e-01, 2.09804267e-01,-4.07952458e-01, -2.95348197e-01, 4.17161107e-01,-9.93740320e-01, -1.18675083e-01, -8.23316276e-01,2.69034244e-02, -1.88849556e+00, 2.10833088e-01,5.37440538e+00, 7.85503864e-01, 7.81758651e-02,1.53081512e+00, -1.06369352e+00, -1.14959764e+00,1.57518709e+00, 4.10526514e-01, -1.17866611e+00,-1.43809450e+00, 3.01593304e-01, -8.29981342e-02,7.02795267e-01, -6.90528154e-01, -1.18140829e+00,6.85002446e-01, 3.61282468e-01, 1.17086756e+00,2.45300770e-01, -1.38156855e+00, 3.23621058e+00,1.34867221e-01, -3.19625527e-01, -3.63594890e-01,2.38367006e-01, 1.03092706e+00, -6.15495563e-01,5.68815589e-01, 4.03137016e+00, -3.29151098e-03,-1.63421535e+00, -1.16476044e-02, -4.56767917e-01,-1.25822902e+00, 4.02444005e-01, -3.32886696e-01,-7.10357428e-01, 1.81120062e+00, 8.15002382e-01,9.54707742e-01, 1.79125595e+00, -6.53005838e-01,-5.05221367e-01, 3.48849654e-01, 3.47478867e-01,1.50463963e+00, -1.60333365e-01, -1.44089317e+00,-5.46101689e-01, -1.77607924e-01, 1.74866974e+00,-6.25463724e-01, -2.33436361e-01, 5.01568556e-01,-6.51883841e-01, 1.31238520e-01, 5.75658679e-01,7.03148782e-01, 7.81953931e-01, -8.42900515e-01,-2.76643723e-01, 5.93519658e-02, 6.59166038e-01,-4.52019334e-01, -6.21397793e-01]], dtype=float32), array([[-0.82274085, -0.0831282 , -0.0401129 , 0.39383799, -0.02410484,-0.16524354, 0.01380365, 0.1165917 , 0.05850193, -0.69423026,-0.35230288, 0.23147044, 0.23356193, -0.13417032, 0.4211756 ,0.06820218, 0.29203904, -0.03941571, 0.16824852, 0.27811021,0.57919294, -0.44307229, -0.25352019, 0.64951479, 0.50807917,0.53396499, 0.33263975, -0.87917364, -0.66070503, 0.18152577,-0.28445041, 0.57785678, 0.22414218, -0.21887593, 0.55092806,0.57028347, 0.19546211, 0.10514873, -0.60573238, 0.57110918,-0.16360006, 0.85401636, 0.38677689, -0.30278051, -0.6265015 ,-0.49790761, -0.17754224, 0.15779942, -0.29400098, 0.31791395,-0.13823931, -0.38524339, 0.32180765, 0.12340824, -0.35963342,-0.12472892, 0.34280482, -0.42604545, -0.05306755, -0.50786221,0.00755332, -0.40128583, 0.14851592, 0.36195096, 0.24064459,0.0394078 , 0.27046308, -0.67985237, -0.60897684, 0.622244 ,0.18340507, -0.67110789, -0.58534211, 0.09149791, -0.06835601,0.3644565 , -0.42829639, -0.47942913, 0.30781382, 0.27426034,0.61893439, 0.19592988, -0.57712489, 0.77699608, 0.03725263,-0.22094995, -0.08114401, 0.1133056 , 0.68485337, -0.35594028,0.42454574, 0.58127284, -0.00092937, -0.79727775, -0.00490146,-0.31414184, -0.38323012, 0.21830694, -0.09383765, -0.39982662,0.6516341 , 0.40829551, 0.69027084, 0.74982709, -0.18299167,-0.21854903, 0.24806808, 0.10432597, 0.64028525, -0.10168972,-0.5904057 , -0.40424132, -0.12101817, 0.65570384, -0.27304602,-0.10488962, 0.37432173, -0.35630706, 0.05456828, 0.41641083,0.40720937, 0.34507042, -0.59877414, -0.13994519, 0.03818761,0.46776542, -0.23145574, -0.46315274]], dtype=float32)]), times = [[ 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 2324 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 4748 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 7172 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 9596 97 98 99]] WARNING:tensorflow:Skipping summary for mean, must be a float, np.float32, np.int64, np.int32 or int. WARNING:tensorflow:Skipping summary for observed, must be a float, np.float32, np.int64, np.int32 or int. WARNING:tensorflow:Skipping summary for start_tuple, must be a float, np.float32, np.int64, np.int32 or int. WARNING:tensorflow:Skipping summary for times, must be a float, np.float32, np.int64, np.int32 or int. WARNING:tensorflow:Input graph does not contain a QueueRunner. That means predict yields forever. This is probably a mistake. 2018-10-17 14:33:57.701743: I C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\common_runtime\gpu\gpu_device.cc:1120] Creating TensorFlow device (/device:GPU:0) -> (device: 0, name: GeForce 940MX, pci bus id: 0000:01:00.0, compute capability: 5.0) INFO:tensorflow:Restoring parameters from C:\Users\……\AppData\Local\Temp\tmpxvos_wek\model.ckpt-200 2018-10-17 14:33:58.032294: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.033565: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.034395: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.035351: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.036145: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.036830: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.037727: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.038556: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.039413: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.040245: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.041087: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.042030: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.043362: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.044424: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.045376: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.046395: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.047807: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.049811: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.050849: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]] 2018-10-17 14:33:58.051606: W C:\tf_jenkins\home\workspace\rel-win\M\windows-gpu\PY\36\tensorflow\core\framework\op_kernel.cc:1192] Out of range: Reached limit of 1[[Node: limit_epochs_2/CountUpTo = CountUpTo[T=DT_INT64, _class=["loc:@limit_epochs_2/epochs"], limit=1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](limit_epochs_2/epochs)]]

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