Execution Time0.38s

Test: TMVA-DNN-RNN-FullRNN-Cpu (Passed)
Build: PR-4827-x86_64-fedora30-gcc9-opt (root-fedora30-1.cern.ch) on 2020-01-22 22:28:26

Test Timing: Passed
Processors1

Show Command Line
Display graphs:

Test output
Training RNN to identity firstCopying output into input
Error in <AddBasicRNNLayer>: Inconsistent time steps with input layout - it should be 1 instead of 1
iteration : 1  loss: 0.440256
iteration : 2  loss: 0.165867
iteration : 3  loss: 0.0674045
iteration : 4  loss: 0.0355376
iteration : 5  loss: 0.0259556
iteration : 6  loss: 0.0229688
iteration : 7  loss: 0.0217801
iteration : 8  loss: 0.0210674
iteration : 9  loss: 0.020487
iteration : 10  loss: 0.0199517
iteration : 11  loss: 0.0194394
iteration : 12  loss: 0.018944
iteration : 13  loss: 0.0184635
iteration : 14  loss: 0.017997
iteration : 15  loss: 0.0175438
iteration : 16  loss: 0.0171034
iteration : 17  loss: 0.0166753
iteration : 18  loss: 0.0162591
iteration : 19  loss: 0.0158543
iteration : 20  loss: 0.0154606
iteration : 21  loss: 0.0150774
iteration : 22  loss: 0.0147045
iteration : 23  loss: 0.0143415
iteration : 24  loss: 0.0139881
iteration : 25  loss: 0.013644
iteration : 26  loss: 0.0133088
iteration : 27  loss: 0.0129823
iteration : 28  loss: 0.0126642
iteration : 29  loss: 0.0123543
iteration : 30  loss: 0.0120522
iteration : 31  loss: 0.0117578
iteration : 32  loss: 0.0114709
iteration : 33  loss: 0.0111911
iteration : 34  loss: 0.0109183
iteration : 35  loss: 0.0106524
iteration : 36  loss: 0.010393
iteration : 37  loss: 0.0101401
iteration : 38  loss: 0.00989343
iteration : 39  loss: 0.00965284
iteration : 40  loss: 0.00941812
iteration : 41  loss: 0.00918918
iteration : 42  loss: 0.00896581
iteration : 43  loss: 0.0087479
iteration : 44  loss: 0.0085353
iteration : 45  loss: 0.00832785
iteration : 46  loss: 0.00812544
iteration : 47  loss: 0.00792793
iteration : 48  loss: 0.0077352
iteration : 49  loss: 0.00754711
iteration : 50  loss: 0.00736357
Error in <AddBasicRNNLayer>: Inconsistent time steps with input layout - it should be 5 instead of 5
Training RNN to simple time dependent data iter = 1 loss: 0.906372
iter = 2 loss: 0.755548
iter = 3 loss: 0.684581
iter = 4 loss: 0.673148
iter = 5 loss: 0.66626
iter = 6 loss: 0.658908
iter = 7 loss: 0.650532
iter = 8 loss: 0.64062
iter = 9 loss: 0.628804
iter = 10 loss: 0.614964
iter = 11 loss: 0.599067
iter = 12 loss: 0.580938
iter = 13 loss: 0.560726
iter = 14 loss: 0.539727
iter = 15 loss: 0.519034
iter = 16 loss: 0.497869
iter = 17 loss: 0.475575
iter = 18 loss: 0.452139
iter = 19 loss: 0.428877
iter = 20 loss: 0.407568
iter = 21 loss: 0.387641
iter = 22 loss: 0.368396
iter = 23 loss: 0.350238
iter = 24 loss: 0.337138
iter = 25 loss: 0.353681
iter = 26 loss: 0.444631
iter = 27 loss: 0.741745
iter = 28 loss: 0.378114
iter = 29 loss: 0.332139
iter = 30 loss: 0.294499
iter = 31 loss: 0.262487
iter = 32 loss: 0.236337
iter = 33 loss: 0.208131
iter = 34 loss: 0.253234
iter = 35 loss: 0.349432
iter = 36 loss: 0.554125
iter = 37 loss: 0.238686
iter = 38 loss: 0.203685
iter = 39 loss: 0.186
iter = 40 loss: 0.173064
iter = 41 loss: 0.162664
iter = 42 loss: 0.153672
iter = 43 loss: 0.145565
iter = 44 loss: 0.138142
iter = 45 loss: 0.131347
iter = 46 loss: 0.125152
iter = 47 loss: 0.119516
iter = 48 loss: 0.11438
iter = 49 loss: 0.10967
iter = 50 loss: 0.105309

2x64 matrix is as follows

     |       0    |       1    |       2    |       3    |       4    |
----------------------------------------------------------------------
   0 |          1           1           0           1           0 
   1 |     0.9496      0.8943      0.1265      0.9002      0.1139 


     |       5    |       6    |       7    |       8    |       9    |
----------------------------------------------------------------------
   0 |          1           0           1           1           1 
   1 |     0.9432      0.1517      0.9483      0.9526      0.9353 


     |      10    |      11    |      12    |      13    |      14    |
----------------------------------------------------------------------
   0 |          1           1           0           1           1 
   1 |     0.7564      0.9442     0.09524       0.901      0.9186 


     |      15    |      16    |      17    |      18    |      19    |
----------------------------------------------------------------------
   0 |          1           0           1           0           0 
   1 |     0.9464      0.1258       0.931      0.1031      0.1246 


     |      20    |      21    |      22    |      23    |      24    |
----------------------------------------------------------------------
   0 |          1           0           0           0           1 
   1 |     0.8527       0.087      0.0953      0.0997       0.938 


     |      25    |      26    |      27    |      28    |      29    |
----------------------------------------------------------------------
   0 |          1           1           0           0           1 
   1 |     0.8985      0.9304     0.09571     0.09091      0.9179 


     |      30    |      31    |      32    |      33    |      34    |
----------------------------------------------------------------------
   0 |          1           0           0           0           0 
   1 |     0.9426      0.1056     0.08995      0.1569     0.09572 


     |      35    |      36    |      37    |      38    |      39    |
----------------------------------------------------------------------
   0 |          1           0           0           1           0 
   1 |     0.9249      0.1226     0.09807      0.9487     0.09507 


     |      40    |      41    |      42    |      43    |      44    |
----------------------------------------------------------------------
   0 |          0           1           1           1           1 
   1 |    0.08195      0.8593      0.9194       0.943      0.9334 


     |      45    |      46    |      47    |      48    |      49    |
----------------------------------------------------------------------
   0 |          1           0           0           1           0 
   1 |     0.9328      0.1554     0.09626      0.9064      0.0901 


     |      50    |      51    |      52    |      53    |      54    |
----------------------------------------------------------------------
   0 |          0           0           1           1           0 
   1 |     0.1029      0.1623      0.8776      0.9235      0.1028 


     |      55    |      56    |      57    |      58    |      59    |
----------------------------------------------------------------------
   0 |          1           1           0           1           0 
   1 |      0.879      0.9344     0.09396      0.9376     0.09336 


     |      60    |      61    |      62    |      63    |
----------------------------------------------------------------------
   0 |          0           1           1           1 
   1 |      0.184      0.9318      0.9434      0.9257 

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