Execution Time0.27s

Test: TMVA-DNN-RNN-FullRNN-Cpu (Passed)
Build: master-x86_64-centos7-gcc62-opt-no-rt-cxxmodules (olsnba08.cern.ch) on 2019-11-14 01:02:24
Repository revision: 32b17abcda23e44b64218a42d0ca69cb30cda7e0

Test Timing: Passed
Processors1

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Test output
Training RNN to identity firstCopying output into input
Copying output into input
loss: 1.27238
loss: 0.689634
loss: 0.428276
loss: 0.302825
loss: 0.239016
loss: 0.204414
loss: 0.184094
loss: 0.170958
loss: 0.161555
loss: 0.154171
loss: 0.147943
loss: 0.142424
loss: 0.137383
loss: 0.132691
loss: 0.128277
loss: 0.124098
loss: 0.120126
loss: 0.116341
loss: 0.112728
loss: 0.109275
loss: 0.105971
loss: 0.102808
loss: 0.0997775
loss: 0.0968712
loss: 0.0940824
loss: 0.0914049
loss: 0.0888326
loss: 0.0863599
loss: 0.0839818
loss: 0.0816933
loss: 0.0794899
loss: 0.0773675
loss: 0.0753219
loss: 0.0733496
loss: 0.0714471
loss: 0.0696109
loss: 0.0678382
loss: 0.0661259
loss: 0.0644713
loss: 0.0628719
loss: 0.0613252
loss: 0.0598289
loss: 0.0583808
loss: 0.056979
loss: 0.0556213
loss: 0.0543061
loss: 0.0530315
loss: 0.0517959
loss: 0.0505978
loss: 0.0494356
Training RNN to simple time dependent data iter = 1 loss: 0.649175
iter = 2 loss: 0.563761
iter = 3 loss: 0.530521
iter = 4 loss: 0.499577
iter = 5 loss: 0.46887
iter = 6 loss: 0.438109
iter = 7 loss: 0.407889
iter = 8 loss: 0.379265
iter = 9 loss: 0.352929
iter = 10 loss: 0.329013
iter = 11 loss: 0.307374
iter = 12 loss: 0.287784
iter = 13 loss: 0.270007
iter = 14 loss: 0.253827
iter = 15 loss: 0.239054
iter = 16 loss: 0.225525
iter = 17 loss: 0.213102
iter = 18 loss: 0.201665
iter = 19 loss: 0.191111
iter = 20 loss: 0.181351
iter = 21 loss: 0.172309
iter = 22 loss: 0.163917
iter = 23 loss: 0.156117
iter = 24 loss: 0.14886
iter = 25 loss: 0.142099
iter = 26 loss: 0.135795
iter = 27 loss: 0.129913
iter = 28 loss: 0.12442
iter = 29 loss: 0.119286
iter = 30 loss: 0.114486
iter = 31 loss: 0.109993
iter = 32 loss: 0.105784
iter = 33 loss: 0.101838
iter = 34 loss: 0.0981351
iter = 35 loss: 0.094656
iter = 36 loss: 0.0913841
iter = 37 loss: 0.0883038
iter = 38 loss: 0.0854008
iter = 39 loss: 0.0826623
iter = 40 loss: 0.0800764
iter = 41 loss: 0.0776322
iter = 42 loss: 0.0753199
iter = 43 loss: 0.0731301
iter = 44 loss: 0.0710546
iter = 45 loss: 0.0690855
iter = 46 loss: 0.0672154
iter = 47 loss: 0.0654377
iter = 48 loss: 0.0637462
iter = 49 loss: 0.0621349
iter = 50 loss: 0.0605985

2x64 matrix is as follows

     |       0    |       1    |       2    |       3    |       4    |
----------------------------------------------------------------------
   0 |          1           1           0           1           0 
   1 |     0.9574      0.8747     0.03109      0.9534     0.05336 


     |       5    |       6    |       7    |       8    |       9    |
----------------------------------------------------------------------
   0 |          1           0           1           1           1 
   1 |     0.9464     0.04249       0.956      0.9497      0.9302 


     |      10    |      11    |      12    |      13    |      14    |
----------------------------------------------------------------------
   0 |          1           1           0           1           1 
   1 |     0.9328      0.9523     0.02461      0.9366      0.9422 


     |      15    |      16    |      17    |      18    |      19    |
----------------------------------------------------------------------
   0 |          1           0           1           0           0 
   1 |     0.9579     0.06984      0.9505     0.02986      0.1769 


     |      20    |      21    |      22    |      23    |      24    |
----------------------------------------------------------------------
   0 |          1           0           0           0           1 
   1 |      0.921     0.01892     0.04605     0.05565      0.9573 


     |      25    |      26    |      27    |      28    |      29    |
----------------------------------------------------------------------
   0 |          1           1           0           0           1 
   1 |     0.8962      0.9453     0.04663     0.02907      0.9504 


     |      30    |      31    |      32    |      33    |      34    |
----------------------------------------------------------------------
   0 |          1           0           0           0           0 
   1 |     0.9391     0.04001     0.04008     0.05186     0.05276 


     |      35    |      36    |      37    |      38    |      39    |
----------------------------------------------------------------------
   0 |          1           0           0           1           0 
   1 |     0.9407     0.06837     0.04195      0.9586     0.04059 


     |      40    |      41    |      42    |      43    |      44    |
----------------------------------------------------------------------
   0 |          0           1           1           1           1 
   1 |    0.04961      0.8817      0.9426      0.9556      0.9499 


     |      45    |      46    |      47    |      48    |      49    |
----------------------------------------------------------------------
   0 |          1           0           0           1           0 
   1 |      0.923     0.05676     0.03771       0.908     0.04053 


     |      50    |      51    |      52    |      53    |      54    |
----------------------------------------------------------------------
   0 |          0           0           1           1           0 
   1 |    0.03526      0.1271      0.9306      0.9506     0.04072 


     |      55    |      56    |      57    |      58    |      59    |
----------------------------------------------------------------------
   0 |          1           1           0           1           0 
   1 |     0.9489      0.9465     0.05229      0.9341      0.0351 


     |      60    |      61    |      62    |      63    |
----------------------------------------------------------------------
   0 |          0           1           1           1 
   1 |    0.07046      0.9411      0.9485      0.9448 

ROC integral is 0.453247
Test full RNN passed : Efficiencies are 0 and 1