Execution Time2.27s

Test: TMVA-DNN-CNN-Pred-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
Testing CNN Prediction:
Test1, identity output function
added Conv layer 12 x 31 x 31
added Conv layer 6 x 29 x 29
added MaxPool layer 6 x 27 x 27
8.12094 -5.81114 
9.23314 -7.54128 
12.194 -10.5282 
12.1381 -7.46714 
8.78329 -5.42479 
12.9442 -4.58808 
6.9942 -6.25703 
8.5624 -7.7796 
7.99166 -7.94955 
7.02196 -5.40326 
11.199 -4.83721 
11.1642 -9.30724 
12.365 -0.347678 
8.07236 -6.8325 
7.35887 -7.56643 
6.81246 -12.8862 
8.63607 -2.06437 
9.44412 -8.62589 
13.1354 -1.40715 
10.6535 -6.5144 
11.6557 -6.95592 
7.89356 -6.90549 
12.6319 -7.65938 
9.91005 -3.32728 
11.6012 -7.35695 
8.44628 -10.6607 
10.8307 -4.96925 
9.86718 -4.51703 
8.14429 -1.38774 
10.752 -6.68505 
11.5748 -4.77793 
7.91967 -4.81173 
7.5874 -7.44905 
9.85492 -6.55386 
7.06141 -5.27193 
12.3145 -1.75557 
12.2948 -1.23662 
10.6997 -11.1074 
8.64629 -8.19018 
10.3391 -11.8062 
12.5082 -5.85866 
12.5004 -5.96386 
13.5094 -4.6502 
11.2093 -8.79699 
7.03269 -11.1952 
9.45942 -11.7147 
11.0775 -8.72302 
9.77701 -3.98945 
11.5798 -8.66706 
12.8562 -4.65334 
Test2, sigmoid output function
added Conv layer 12 x 31 x 31
added Conv layer 6 x 29 x 29
added MaxPool layer 6 x 27 x 27
0.691536 0.979327 
0.0130705 0.95859 
0.142498 0.999433 
0.240526 0.999851 
0.233999 0.97016 
0.915437 0.999592 
0.436101 0.983833 
0.596865 0.704017 
0.91557 0.995735 
0.1698 0.994338 
0.773073 0.999935 
0.0435695 0.929572 
0.769583 0.998764 
0.00771199 0.99846 
0.0631447 0.999913 
0.14409 0.999912 
0.824916 0.819065 
0.996739 0.999799 
0.00385919 0.97738 
0.217443 0.997604 
0.0545471 0.995129 
0.37059 0.991392 
0.991526 0.987761 
0.000886195 0.993143 
0.205884 0.998665 
0.000253049 0.68195 
0.99528 0.993285 
0.948309 0.998418 
0.00829288 0.998721 
0.169685 0.997231 
0.083398 0.996254 
0.266263 0.71672 
0.130391 0.995893 
0.276246 0.977561 
0.0556407 0.998972 
0.00337639 0.991437 
0.887852 0.81856 
0.45274 0.998782 
0.123812 0.996586 
0.12815 0.984809 
0.372747 0.966338 
0.395129 0.999842 
0.0871054 0.999962 
0.50781 0.986026 
0.299951 0.996623 
0.0878024 0.782465 
0.838789 0.998774 
0.48407 0.998698 
0.402621 0.999391 
0.0188531 0.992091 
Test3, softmax output function
added Conv layer 12 x 31 x 31
added Conv layer 6 x 29 x 29
added MaxPool layer 6 x 27 x 27
0.989125 0.0108754 
1 4.77653e-08 
0.999969 3.12336e-05 
0.999385 0.000615327 
0.998721 0.00127873 
0.999974 2.61408e-05 
0.999978 2.15295e-05 
0.999982 1.779e-05 
0.999999 7.1032e-07 
0.999984 1.624e-05 
0.996382 0.00361819 
1 1.43466e-07 
0.999564 0.00043611 
0.999851 0.000149379 
0.999775 0.000225295 
0.999996 3.65403e-06 
0.987007 0.0129935 
0.998178 0.0018225 
0.999999 1.05653e-06 
0.999702 0.000297936 
0.999827 0.000172705 
1 2.38277e-07 
0.999998 1.66708e-06 
0.999936 6.39811e-05 
0.999946 5.42217e-05 
0.999975 2.54774e-05 
0.999845 0.00015498 
0.999985 1.48289e-05 
0.998702 0.00129826 
0.999999 5.21133e-07 
0.99999 9.54413e-06 
0.999965 3.49975e-05 
0.999999 1.05167e-06 
0.999961 3.91458e-05 
0.999894 0.000106059 
0.999713 0.000286852 
0.999887 0.000113197 
0.999956 4.36223e-05 
0.95248 0.0475197 
1 1.38755e-08 
0.999919 8.11487e-05 
0.971884 0.028116 
0.999984 1.59056e-05 
0.999326 0.000674392 
0.999929 7.14649e-05 
0.999933 6.68477e-05 
0.993988 0.00601181 
0.998766 0.00123425 
0.989273 0.0107269 
0.999645 0.000355494