Execution Time0.25s

Test: TMVA-DNN-RNN-FullRNN-Cpu (Passed)
Build: master-x86_64-centos7-clang100-opt-no-rt-cxxmodules (olsnba08.cern.ch) on 2019-11-14 01:39:53
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: 0.99243
loss: 0.418147
loss: 0.187519
loss: 0.0924738
loss: 0.0523351
loss: 0.0349868
loss: 0.0272993
loss: 0.0237868
loss: 0.0221138
loss: 0.0212674
loss: 0.0208002
loss: 0.0205104
loss: 0.0203055
loss: 0.0201419
loss: 0.0199987
loss: 0.0198658
loss: 0.0197382
loss: 0.0196134
loss: 0.01949
loss: 0.0193675
loss: 0.0192455
loss: 0.0191237
loss: 0.0190021
loss: 0.0188807
loss: 0.0187594
loss: 0.0186382
loss: 0.0185171
loss: 0.018396
loss: 0.0182751
loss: 0.0181542
loss: 0.0180334
loss: 0.0179127
loss: 0.017792
loss: 0.0176714
loss: 0.0175509
loss: 0.0174305
loss: 0.0173101
loss: 0.0171897
loss: 0.0170695
loss: 0.0169493
loss: 0.0168292
loss: 0.0167091
loss: 0.0165891
loss: 0.0164691
loss: 0.0163493
loss: 0.0162295
loss: 0.0161097
loss: 0.0159901
loss: 0.0158705
loss: 0.015751
Training RNN to simple time dependent data iter = 1 loss: 0.837452
iter = 2 loss: 0.636261
iter = 3 loss: 0.602048
iter = 4 loss: 0.558135
iter = 5 loss: 0.503775
iter = 6 loss: 0.472257
iter = 7 loss: 0.455956
iter = 8 loss: 0.451857
iter = 9 loss: 0.478904
iter = 10 loss: 0.456527
iter = 11 loss: 0.460798
iter = 12 loss: 0.39219
iter = 13 loss: 0.363813
iter = 14 loss: 0.337555
iter = 15 loss: 0.321618
iter = 16 loss: 0.301234
iter = 17 loss: 0.285676
iter = 18 loss: 0.268911
iter = 19 loss: 0.255726
iter = 20 loss: 0.243407
iter = 21 loss: 0.233142
iter = 22 loss: 0.223732
iter = 23 loss: 0.215288
iter = 24 loss: 0.207423
iter = 25 loss: 0.200098
iter = 26 loss: 0.193198
iter = 27 loss: 0.18668
iter = 28 loss: 0.180502
iter = 29 loss: 0.174635
iter = 30 loss: 0.169054
iter = 31 loss: 0.16374
iter = 32 loss: 0.158676
iter = 33 loss: 0.153846
iter = 34 loss: 0.149238
iter = 35 loss: 0.144837
iter = 36 loss: 0.140632
iter = 37 loss: 0.136612
iter = 38 loss: 0.132768
iter = 39 loss: 0.129088
iter = 40 loss: 0.125564
iter = 41 loss: 0.122189
iter = 42 loss: 0.118953
iter = 43 loss: 0.11585
iter = 44 loss: 0.112872
iter = 45 loss: 0.110013
iter = 46 loss: 0.107268
iter = 47 loss: 0.10463
iter = 48 loss: 0.102094
iter = 49 loss: 0.099654
iter = 50 loss: 0.0973065

2x64 matrix is as follows

     |       0    |       1    |       2    |       3    |       4    |
----------------------------------------------------------------------
   0 |          1           1           0           1           0 
   1 |      0.936       0.928      0.0464      0.9194     0.08807 


     |       5    |       6    |       7    |       8    |       9    |
----------------------------------------------------------------------
   0 |          1           0           1           1           1 
   1 |     0.9457      0.1757      0.9332      0.9512      0.9238 


     |      10    |      11    |      12    |      13    |      14    |
----------------------------------------------------------------------
   0 |          1           1           0           1           1 
   1 |      0.911      0.9429     0.06605      0.9452      0.9389 


     |      15    |      16    |      17    |      18    |      19    |
----------------------------------------------------------------------
   0 |          1           0           1           0           0 
   1 |     0.9473       0.159      0.9444     0.05006      0.3606 


     |      20    |      21    |      22    |      23    |      24    |
----------------------------------------------------------------------
   0 |          1           0           0           0           1 
   1 |     0.8396     0.05232      0.0506     0.07213      0.9358 


     |      25    |      26    |      27    |      28    |      29    |
----------------------------------------------------------------------
   0 |          1           1           0           0           1 
   1 |     0.7646      0.9416      0.0653     0.07317      0.9363 


     |      30    |      31    |      32    |      33    |      34    |
----------------------------------------------------------------------
   0 |          1           0           0           0           0 
   1 |     0.9226     0.05336     0.06225     0.05055     0.08061 


     |      35    |      36    |      37    |      38    |      39    |
----------------------------------------------------------------------
   0 |          1           0           0           1           0 
   1 |      0.924     0.09465     0.08347      0.9276     0.08392 


     |      40    |      41    |      42    |      43    |      44    |
----------------------------------------------------------------------
   0 |          0           1           1           1           1 
   1 |     0.1319      0.9149      0.9277      0.9288      0.9069 


     |      45    |      46    |      47    |      48    |      49    |
----------------------------------------------------------------------
   0 |          1           0           0           1           0 
   1 |     0.8434      0.2089     0.05715      0.9146      0.0746 


     |      50    |      51    |      52    |      53    |      54    |
----------------------------------------------------------------------
   0 |          0           0           1           1           0 
   1 |    0.05183      0.1152      0.8865      0.9346     0.06509 


     |      55    |      56    |      57    |      58    |      59    |
----------------------------------------------------------------------
   0 |          1           1           0           1           0 
   1 |     0.8983      0.9076     0.08017      0.9018     0.06511 


     |      60    |      61    |      62    |      63    |
----------------------------------------------------------------------
   0 |          0           1           1           1 
   1 |     0.1472      0.8785      0.9295      0.9364 

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