Execution Time5.06s

Test: TMVA-DNN-CNN-MethodDL-CPU (Passed)
Build: PR-4624-x86_64-mac1014-clang100-opt (macphsft17.dyndns.cern.ch) on 2019-11-14 19:01:56

Test Timing: Passed
Processors1

Show Command Line
Display graphs:

Test output
Testing Method DL for CPU backend: 
******************************************************************************
*Tree    :sgn       : sgn                                                    *
*Entries :     2000 : Total =          514306 bytes  File  Size =     463562 *
*        :          : Tree compression factor =   1.10                       *
******************************************************************************
*Br    0 :ximage    : ximage[64]/F                                           *
*Entries :     2000 : Total  Size=     514013 bytes  File Size  =     463562 *
*Baskets :       16 : Basket Size=      32000 bytes  Compression=   1.10     *
*............................................................................*
******************************************************************************
*Tree    :bkg       : bkg                                                    *
*Entries :     2000 : Total =          514306 bytes  File  Size =     458118 *
*        :          : Tree compression factor =   1.11                       *
******************************************************************************
*Br    0 :ximage    : ximage[64]/F                                           *
*Entries :     2000 : Total  Size=     514013 bytes  File Size  =     458118 *
*Baskets :       16 : Basket Size=      32000 bytes  Compression=   1.11     *
*............................................................................*
create data set info dataset
DataSetInfo              : [dataset] : Added class "Signal"
                         : Add Tree sgn of type Signal with 2000 events
DataSetInfo              : [dataset] : Added class "Background"
                         : Add Tree bkg of type Background with 2000 events
Factory                  : You are running ROOT Version: 6.19/01, May 29, 2019
                         : 
                         : _/_/_/_/_/ _|      _|  _|      _|    _|_|   
                         :    _/      _|_|  _|_|  _|      _|  _|    _| 
                         :   _/       _|  _|  _|  _|      _|  _|_|_|_| 
                         :  _/        _|      _|    _|  _|    _|    _| 
                         : _/         _|      _|      _|      _|    _| 
                         : 
                         : ___________TMVA Version 4.2.1, Feb 5, 2015
                         : 
Factory                  : Booking method: [NON-XML-CHAR-0x1B][1mDL_CNN_CPU[NON-XML-CHAR-0x1B][0m
                         : 
                         : Parsing option string: 
                         : ... "!H:V:ErrorStrategy=CROSSENTROPY:WeightInitialization=XAVIERUNIFORM:InputLayout=1|8|8:BatchLayout=256|1|64:Layout=CONV|6|3|3|1|1|0|0|TANH,MAXPOOL|2|2|2|2,RESHAPE|FLAT,DENSE|10|TANH,DENSE|2|LINEAR:TrainingStrategy=LearningRate=1e-1,Optimizer=SGD,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=10,WeightDecay=1e-4,Regularization=L2,MaxEpochs=40DropConfig=0.0+0.5+0.5+0.5|LearningRate=1e-2,Optimizer=SGD,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=5,WeightDecay=1e-4,Regularization=L2,MaxEpochs=20DropConfig=0.0+0.0+0.0+0.0|LearningRate=1e-3,Optimizer=SGD,Momentum=0.0,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=5,WeightDecay=1e-4,Regularization=L2,MaxEpochs=20DropConfig=0.0+0.0+0.0+0.0:Architecture=CPU"
                         : The following options are set:
                         : - By User:
                         :     <none>
                         : - Default:
                         :     Boost_num: "0" [Number of times the classifier will be boosted]
                         : Parsing option string: 
                         : ... "!H:V:ErrorStrategy=CROSSENTROPY:WeightInitialization=XAVIERUNIFORM:InputLayout=1|8|8:BatchLayout=256|1|64:Layout=CONV|6|3|3|1|1|0|0|TANH,MAXPOOL|2|2|2|2,RESHAPE|FLAT,DENSE|10|TANH,DENSE|2|LINEAR:TrainingStrategy=LearningRate=1e-1,Optimizer=SGD,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=10,WeightDecay=1e-4,Regularization=L2,MaxEpochs=40DropConfig=0.0+0.5+0.5+0.5|LearningRate=1e-2,Optimizer=SGD,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=5,WeightDecay=1e-4,Regularization=L2,MaxEpochs=20DropConfig=0.0+0.0+0.0+0.0|LearningRate=1e-3,Optimizer=SGD,Momentum=0.0,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=5,WeightDecay=1e-4,Regularization=L2,MaxEpochs=20DropConfig=0.0+0.0+0.0+0.0:Architecture=CPU"
                         : The following options are set:
                         : - By User:
                         :     V: "True" [Verbose output (short form of "VerbosityLevel" below - overrides the latter one)]
                         :     H: "False" [Print method-specific help message]
                         :     InputLayout: "1|8|8" [The Layout of the input]
                         :     BatchLayout: "256|1|64" [The Layout of the batch]
                         :     Layout: "CONV|6|3|3|1|1|0|0|TANH,MAXPOOL|2|2|2|2,RESHAPE|FLAT,DENSE|10|TANH,DENSE|2|LINEAR" [Layout of the network.]
                         :     ErrorStrategy: "CROSSENTROPY" [Loss function: Mean squared error (regression) or cross entropy (binary classification).]
                         :     WeightInitialization: "XAVIERUNIFORM" [Weight initialization strategy]
                         :     Architecture: "CPU" [Which architecture to perform the training on.]
                         :     TrainingStrategy: "LearningRate=1e-1,Optimizer=SGD,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=10,WeightDecay=1e-4,Regularization=L2,MaxEpochs=40DropConfig=0.0+0.5+0.5+0.5|LearningRate=1e-2,Optimizer=SGD,Momentum=0.9,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=5,WeightDecay=1e-4,Regularization=L2,MaxEpochs=20DropConfig=0.0+0.0+0.0+0.0|LearningRate=1e-3,Optimizer=SGD,Momentum=0.0,Repetitions=1,ConvergenceSteps=20,BatchSize=256,TestRepetitions=5,WeightDecay=1e-4,Regularization=L2,MaxEpochs=20DropConfig=0.0+0.0+0.0+0.0" [Defines the training strategies.]
                         : - Default:
                         :     VerbosityLevel: "Default" [Verbosity level]
                         :     VarTransform: "None" [List of variable transformations performed before training, e.g., "D_Background,P_Signal,G,N_AllClasses" for: "Decorrelation, PCA-transformation, Gaussianisation, Normalisation, each for the given class of events ('AllClasses' denotes all events of all classes, if no class indication is given, 'All' is assumed)"]
                         :     CreateMVAPdfs: "False" [Create PDFs for classifier outputs (signal and background)]
                         :     IgnoreNegWeightsInTraining: "False" [Events with negative weights are ignored in the training (but are included for testing and performance evaluation)]
                         :     RandomSeed: "0" [Random seed used for weight initialization and batch shuffling]
                         :     ValidationSize: "20%" [Part of the training data to use for validation. Specify as 0.2 or 20% to use a fifth of the data set as validation set. Specify as 100 to use exactly 100 events. (Default: 20%)]
                         : Will use now the CPU architecture !
Factory                  : [NON-XML-CHAR-0x1B][1mTrain all methods[NON-XML-CHAR-0x1B][0m
                         : Building event vectors for type 2 Signal
                         : Dataset[dataset] :  create input formulas for tree sgn
                         : Using variable ximage[0] from array expression ximage of size 64
                         : Building event vectors for type 2 Background
                         : Dataset[dataset] :  create input formulas for tree bkg
                         : Using variable ximage[0] from array expression ximage of size 64
DataSetFactory           : [dataset] : Number of events in input trees
                         : 
                         : 
                         : Number of training and testing events
                         : ---------------------------------------------------------------------------
                         : Signal     -- training events            : 1000
                         : Signal     -- testing events             : 1000
                         : Signal     -- training and testing events: 2000
                         : Background -- training events            : 1000
                         : Background -- testing events             : 1000
                         : Background -- training and testing events: 2000
                         : 
Factory                  : Train method: DL_CNN_CPU for Classification
                         : 
                         : Start of deep neural network training on CPU using (for ROOT-IMT) nthreads = 1
                         : 
                         : *****   Deep Learning Network *****
DEEP NEURAL NETWORK:   Depth = 5  Input = ( 1, 8, 8 )  Batch size = 256  Loss function = C
	Layer 0	 CONV LAYER: 	( W = 6 ,  H = 6 ,  D = 6 ) 	 Filter ( W = 3 ,  H = 3 ) 	Output = ( 256 , 6 , 36 ) 	 Activation Function = Tanh
	Layer 1	 POOL Layer: 	( W = 3 ,  H = 3 ,  D = 6 ) 	 Filter ( W = 2 ,  H = 2 ) 	Output = ( 256 , 6 , 9 ) 
	Layer 2	 RESHAPE Layer 	 Input = ( 6 , 3 , 3 ) 	Output = ( 1 , 256 , 54 ) 
	Layer 3	 DENSE Layer: 	 ( Input =    54 , Width =    10 ) 	Output = (  1 ,   256 ,    10 ) 	 Activation Function = Tanh
	Layer 4	 DENSE Layer: 	 ( Input =    10 , Width =     2 ) 	Output = (  1 ,   256 ,     2 ) 	 Activation Function = Identity
                         : Using 1600 events for training and 400 for testing
                         : Training phase 1 of 3:  Optimizer SGD Learning rate = 0.1 regularization 2 minimum error = 0.683546
                         : --------------------------------------------------------------
                         :      Epoch |   Train Err.   Val. Err.  t(s)/epoch   t(s)/Loss   nEvents/s Conv. Steps
                         : --------------------------------------------------------------
                         :         10 |     0.706761    0.696802   0.0168933    0.009263     96198.4          10
                         :         20 |     0.700775     0.70227   0.0180595    0.015596     93091.5          20
                         :         30 |     0.700831    0.699562   0.0168595    0.009344     96451.5          30
                         : 
                         : Using 1600 events for training and 400 for testing
                         : Training phase 2 of 3:  Optimizer SGD Learning rate = 0.01 regularization 2 minimum error = 0.693146
                         : --------------------------------------------------------------
                         :      Epoch |   Train Err.   Val. Err.  t(s)/epoch   t(s)/Loss   nEvents/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |     0.693103    0.693437    0.018052    0.009429     95013.1           5
                         :         10 |     0.693083    0.693713     0.01781    0.009439     96469.1          10
                         :         15 |     0.693064    0.693947   0.0174908    0.009321     98293.9          15
                         :         20 |     0.693092    0.694184   0.0177902    0.009113     96194.8          20
                         : 
                         : Using 1600 events for training and 400 for testing
                         : Training phase 3 of 3:  Optimizer SGD Learning rate = 0.001 regularization 2 minimum error = 0.693146
                         : --------------------------------------------------------------
                         :      Epoch |   Train Err.   Val. Err.  t(s)/epoch   t(s)/Loss   nEvents/s Conv. Steps
                         : --------------------------------------------------------------
                         :          5 |     0.693146    0.693149    0.017687    0.009131     96842.5           5
                         :         10 |      0.69315    0.693157   0.0180144    0.009375     95170.8          10
                         :         15 |     0.693144    0.693158   0.0175294    0.009412     98165.8          15
                         :         20 |     0.693149    0.693166    0.017757    0.009502     96868.2          20
                         : 
                         : Elapsed time for training with 2000 events: 1.25 sec         
                         : Evaluate deep neural network on CPU using batches with size = 256
                         : 
DL_CNN_CPU               : [dataset] : Evaluation of DL_CNN_CPU on training sample (2000 events)
                         : Elapsed time for evaluation of 2000 events: 0.0122 sec       
                         : Creating xml weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVAClassification_DL_CNN_CPU.weights.xml[NON-XML-CHAR-0x1B][0m
                         : Creating standalone class: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVAClassification_DL_CNN_CPU.class.C[NON-XML-CHAR-0x1B][0m
Factory                  : Training finished
                         : 
                         : Ranking input variables (method specific)...
                         : No variable ranking supplied by classifier: DL_CNN_CPU
Factory                  : === Destroy and recreate all methods via weight files for testing ===
                         : 
                         : Reading weight file: [NON-XML-CHAR-0x1B][0;36mdataset/weights/TMVAClassification_DL_CNN_CPU.weights.xml[NON-XML-CHAR-0x1B][0m
Factory                  : [NON-XML-CHAR-0x1B][1mTest all methods[NON-XML-CHAR-0x1B][0m
Factory                  : Test method: DL_CNN_CPU for Classification performance
                         : 
                         : Evaluate deep neural network on CPU using batches with size = 1000
                         : 
DL_CNN_CPU               : [dataset] : Evaluation of DL_CNN_CPU on testing sample (2000 events)
                         : Elapsed time for evaluation of 2000 events: 0.0106 sec       
Factory                  : [NON-XML-CHAR-0x1B][1mEvaluate all methods[NON-XML-CHAR-0x1B][0m
Factory                  : Evaluate classifier: DL_CNN_CPU
                         : 
DL_CNN_CPU               : [dataset] : Loop over test events and fill histograms with classifier response...
                         : 
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.005, fb=-0.005), refValue = 0.005
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.015, fb=-0.015), refValue = 0.015
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.025, fb=-0.025), refValue = 0.025
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.035, fb=-0.035), refValue = 0.035
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.045, fb=-0.045), refValue = 0.045
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.055, fb=-0.055), refValue = 0.055
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.065, fb=-0.065), refValue = 0.065
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.075, fb=-0.075), refValue = 0.075
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.085, fb=-0.085), refValue = 0.085
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.095, fb=-0.095), refValue = 0.095
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.105, fb=-0.105), refValue = 0.105
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.115, fb=-0.115), refValue = 0.115
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.125, fb=-0.125), refValue = 0.125
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.135, fb=-0.135), refValue = 0.135
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.145, fb=-0.145), refValue = 0.145
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.155, fb=-0.155), refValue = 0.155
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.165, fb=-0.165), refValue = 0.165
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.175, fb=-0.175), refValue = 0.175
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.185, fb=-0.185), refValue = 0.185
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.195, fb=-0.195), refValue = 0.195
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.205, fb=-0.205), refValue = 0.205
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.215, fb=-0.215), refValue = 0.215
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.225, fb=-0.225), refValue = 0.225
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.235, fb=-0.235), refValue = 0.235
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.245, fb=-0.245), refValue = 0.245
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.255, fb=-0.255), refValue = 0.255
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.265, fb=-0.265), refValue = 0.265
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.275, fb=-0.275), refValue = 0.275
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.285, fb=-0.285), refValue = 0.285
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.295, fb=-0.295), refValue = 0.295
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.305, fb=-0.305), refValue = 0.305
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.315, fb=-0.315), refValue = 0.315
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.325, fb=-0.325), refValue = 0.325
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.335, fb=-0.335), refValue = 0.335
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.345, fb=-0.345), refValue = 0.345
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.355, fb=-0.355), refValue = 0.355
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.365, fb=-0.365), refValue = 0.365
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.375, fb=-0.375), refValue = 0.375
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.385, fb=-0.385), refValue = 0.385
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.395, fb=-0.395), refValue = 0.395
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.405, fb=-0.405), refValue = 0.405
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.415, fb=-0.415), refValue = 0.415
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.425, fb=-0.425), refValue = 0.425
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.435, fb=-0.435), refValue = 0.435
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.445, fb=-0.445), refValue = 0.445
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.455, fb=-0.455), refValue = 0.455
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.465, fb=-0.465), refValue = 0.465
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.475, fb=-0.475), refValue = 0.475
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.485, fb=-0.485), refValue = 0.485
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.495, fb=-0.495), refValue = 0.495
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.505, fb=-0.505), refValue = 0.505
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.515, fb=-0.515), refValue = 0.515
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.525, fb=-0.525), refValue = 0.525
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.535, fb=-0.535), refValue = 0.535
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.545, fb=-0.545), refValue = 0.545
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.555, fb=-0.555), refValue = 0.555
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.565, fb=-0.565), refValue = 0.565
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.575, fb=-0.575), refValue = 0.575
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.585, fb=-0.585), refValue = 0.585
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.595, fb=-0.595), refValue = 0.595
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.605, fb=-0.605), refValue = 0.605
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.615, fb=-0.615), refValue = 0.615
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.625, fb=-0.625), refValue = 0.625
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.635, fb=-0.635), refValue = 0.635
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.645, fb=-0.645), refValue = 0.645
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.655, fb=-0.655), refValue = 0.655
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.665, fb=-0.665), refValue = 0.665
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.675, fb=-0.675), refValue = 0.675
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.685, fb=-0.685), refValue = 0.685
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.695, fb=-0.695), refValue = 0.695
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.705, fb=-0.705), refValue = 0.705
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.715, fb=-0.715), refValue = 0.715
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.725, fb=-0.725), refValue = 0.725
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.735, fb=-0.735), refValue = 0.735
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.745, fb=-0.745), refValue = 0.745
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.755, fb=-0.755), refValue = 0.755
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.765, fb=-0.765), refValue = 0.765
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.775, fb=-0.775), refValue = 0.775
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.785, fb=-0.785), refValue = 0.785
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.795, fb=-0.795), refValue = 0.795
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.805, fb=-0.805), refValue = 0.805
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.815, fb=-0.815), refValue = 0.815
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.825, fb=-0.825), refValue = 0.825
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.835, fb=-0.835), refValue = 0.835
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.845, fb=-0.845), refValue = 0.845
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.855, fb=-0.855), refValue = 0.855
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.865, fb=-0.865), refValue = 0.865
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.875, fb=-0.875), refValue = 0.875
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.885, fb=-0.885), refValue = 0.885
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.895, fb=-0.895), refValue = 0.895
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.905, fb=-0.905), refValue = 0.905
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.915, fb=-0.915), refValue = 0.915
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.925, fb=-0.925), refValue = 0.925
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.935, fb=-0.935), refValue = 0.935
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.945, fb=-0.945), refValue = 0.945
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.955, fb=-0.955), refValue = 0.955
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.965, fb=-0.965), refValue = 0.965
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.975, fb=-0.975), refValue = 0.975
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.985, fb=-0.985), refValue = 0.985
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.995, fb=-0.995), refValue = 0.995
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.9999, fb=-0.9999), refValue = 0.9999
                         : Evaluate deep neural network on CPU using batches with size = 1000
                         : 
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.005, fb=-0.005), refValue = 0.005
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.015, fb=-0.015), refValue = 0.015
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.025, fb=-0.025), refValue = 0.025
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.035, fb=-0.035), refValue = 0.035
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.045, fb=-0.045), refValue = 0.045
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.055, fb=-0.055), refValue = 0.055
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.065, fb=-0.065), refValue = 0.065
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.075, fb=-0.075), refValue = 0.075
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.085, fb=-0.085), refValue = 0.085
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.095, fb=-0.095), refValue = 0.095
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.105, fb=-0.105), refValue = 0.105
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.115, fb=-0.115), refValue = 0.115
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.125, fb=-0.125), refValue = 0.125
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.135, fb=-0.135), refValue = 0.135
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.145, fb=-0.145), refValue = 0.145
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.155, fb=-0.155), refValue = 0.155
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.165, fb=-0.165), refValue = 0.165
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.175, fb=-0.175), refValue = 0.175
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.185, fb=-0.185), refValue = 0.185
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.195, fb=-0.195), refValue = 0.195
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.205, fb=-0.205), refValue = 0.205
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.215, fb=-0.215), refValue = 0.215
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.225, fb=-0.225), refValue = 0.225
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.235, fb=-0.235), refValue = 0.235
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.245, fb=-0.245), refValue = 0.245
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.255, fb=-0.255), refValue = 0.255
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.265, fb=-0.265), refValue = 0.265
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.275, fb=-0.275), refValue = 0.275
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.285, fb=-0.285), refValue = 0.285
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.295, fb=-0.295), refValue = 0.295
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.305, fb=-0.305), refValue = 0.305
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.315, fb=-0.315), refValue = 0.315
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.325, fb=-0.325), refValue = 0.325
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.335, fb=-0.335), refValue = 0.335
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.345, fb=-0.345), refValue = 0.345
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.355, fb=-0.355), refValue = 0.355
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.365, fb=-0.365), refValue = 0.365
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.375, fb=-0.375), refValue = 0.375
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.385, fb=-0.385), refValue = 0.385
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.395, fb=-0.395), refValue = 0.395
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.405, fb=-0.405), refValue = 0.405
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.415, fb=-0.415), refValue = 0.415
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.425, fb=-0.425), refValue = 0.425
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.435, fb=-0.435), refValue = 0.435
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.445, fb=-0.445), refValue = 0.445
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.455, fb=-0.455), refValue = 0.455
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.465, fb=-0.465), refValue = 0.465
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.475, fb=-0.475), refValue = 0.475
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.485, fb=-0.485), refValue = 0.485
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.495, fb=-0.495), refValue = 0.495
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.505, fb=-0.505), refValue = 0.505
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.515, fb=-0.515), refValue = 0.515
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.525, fb=-0.525), refValue = 0.525
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.535, fb=-0.535), refValue = 0.535
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.545, fb=-0.545), refValue = 0.545
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.555, fb=-0.555), refValue = 0.555
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.565, fb=-0.565), refValue = 0.565
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.575, fb=-0.575), refValue = 0.575
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.585, fb=-0.585), refValue = 0.585
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.595, fb=-0.595), refValue = 0.595
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.605, fb=-0.605), refValue = 0.605
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.615, fb=-0.615), refValue = 0.615
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.625, fb=-0.625), refValue = 0.625
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.635, fb=-0.635), refValue = 0.635
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.645, fb=-0.645), refValue = 0.645
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.655, fb=-0.655), refValue = 0.655
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.665, fb=-0.665), refValue = 0.665
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.675, fb=-0.675), refValue = 0.675
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.685, fb=-0.685), refValue = 0.685
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.695, fb=-0.695), refValue = 0.695
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.705, fb=-0.705), refValue = 0.705
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.715, fb=-0.715), refValue = 0.715
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.725, fb=-0.725), refValue = 0.725
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.735, fb=-0.735), refValue = 0.735
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.745, fb=-0.745), refValue = 0.745
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.755, fb=-0.755), refValue = 0.755
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.765, fb=-0.765), refValue = 0.765
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.775, fb=-0.775), refValue = 0.775
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.785, fb=-0.785), refValue = 0.785
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.795, fb=-0.795), refValue = 0.795
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.805, fb=-0.805), refValue = 0.805
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.815, fb=-0.815), refValue = 0.815
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.825, fb=-0.825), refValue = 0.825
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.835, fb=-0.835), refValue = 0.835
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.845, fb=-0.845), refValue = 0.845
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.855, fb=-0.855), refValue = 0.855
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.865, fb=-0.865), refValue = 0.865
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.875, fb=-0.875), refValue = 0.875
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.885, fb=-0.885), refValue = 0.885
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.895, fb=-0.895), refValue = 0.895
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.905, fb=-0.905), refValue = 0.905
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.915, fb=-0.915), refValue = 0.915
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.925, fb=-0.925), refValue = 0.925
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.935, fb=-0.935), refValue = 0.935
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.945, fb=-0.945), refValue = 0.945
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.955, fb=-0.955), refValue = 0.955
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.965, fb=-0.965), refValue = 0.965
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.975, fb=-0.975), refValue = 0.975
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.985, fb=-0.985), refValue = 0.985
<WARNING>                : <Root> initial interval w/o root: (a=0.5, b=0.5), (Eff_a=0, Eff_b=0), (fa=-0.995, fb=-0.995), refValue = 0.995
                         : 
                         : Evaluation results ranked by best signal efficiency and purity (area)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet       MVA                       
                         : Name:         Method:          ROC-integ
                         : dataset       DL_CNN_CPU     : 0.496
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
                         : Testing efficiency compared to training efficiency (overtraining check)
                         : -------------------------------------------------------------------------------------------------------------------
                         : DataSet              MVA              Signal efficiency: from test sample (from training sample) 
                         : Name:                Method:          @B=0.01             @B=0.10            @B=0.30   
                         : -------------------------------------------------------------------------------------------------------------------
                         : dataset              DL_CNN_CPU     : 0.000 (0.000)       0.000 (0.000)      0.000 (0.000)
                         : -------------------------------------------------------------------------------------------------------------------
                         : 
Factory                  : [NON-XML-CHAR-0x1B][1mThank you for using TMVA![NON-XML-CHAR-0x1B][0m
                         : [NON-XML-CHAR-0x1B][1mFor citation information, please visit: http://tmva.sf.net/citeTMVA.html[NON-XML-CHAR-0x1B][0m
==> TMVAClassification is done!