CPU info:
    CPU Model Name: Intel(R) Xeon(R) CPU E5-2690 v3 @ 2.60GHz
    Hardware threads: 6
    Total Memory: 58719796 kB
-------------------------------------------------------------------
=== Running c:\local\msmpi-7.0.12437.6\Bin/mpiexec.exe -n 2 C:\jenkins\workspace\CNTK-Test-Windows-W1\x64\release\cntk.exe configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation/cntkcv.cntk currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data RunDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation OutputDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu DeviceId=0 timestamping=true numCPUThreads=3 shareNodeValueMatrices=true stderr=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr
CNTK 2.3.1+ (HEAD db192c, Jan 10 2018 22:59:43) at 2018/01/11 08:54:28

C:\jenkins\workspace\CNTK-Test-Windows-W1\x64\release\cntk.exe  configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation/cntkcv.cntk  currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  RunDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation  OutputDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DeviceId=0  timestamping=true  numCPUThreads=3  shareNodeValueMatrices=true  stderr=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr
Changed current directory to C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data
ping [requestnodes (before change)]: 2 nodes pinging each other
CNTK 2.3.1+ (HEAD db192c, Jan 10 2018 22:59:43) at 2018/01/11 08:54:28

C:\jenkins\workspace\CNTK-Test-Windows-W1\x64\release\cntk.exe  configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation/cntkcv.cntk  currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  RunDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation  OutputDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DeviceId=0  timestamping=true  numCPUThreads=3  shareNodeValueMatrices=true  stderr=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr
Changed current directory to C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data
ping [requestnodes (before change)]: 2 nodes pinging each other
ping [requestnodes (after change)]: 2 nodes pinging each other
ping [requestnodes (after change)]: 2 nodes pinging each other
requestnodes [MPIWrapperMpi]: using 2 out of 2 MPI nodes on a single host (2 requested); we (0) are in (participating)
requestnodes [MPIWrapperMpi]: using 2 out of 2 MPI nodes on a single host (2 requested); we (1) are in (participating)
ping [mpihelper]: 2 nodes pinging each other
ping [mpihelper]: 2 nodes pinging each other
MPI Rank 0: 01/11/2018 08:54:29: Redirecting stderr to file C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr_speechTrain.logrank0
MPI Rank 0: CNTK 2.3.1+ (HEAD db192c, Jan 10 2018 22:59:43) at 2018/01/11 08:54:28
MPI Rank 0: 
MPI Rank 0: C:\jenkins\workspace\CNTK-Test-Windows-W1\x64\release\cntk.exe  configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation/cntkcv.cntk  currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  RunDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation  OutputDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DeviceId=0  timestamping=true  numCPUThreads=3  shareNodeValueMatrices=true  stderr=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr
MPI Rank 0: -------------------------------------------------------------------
MPI Rank 0: Build info: 
MPI Rank 0: 
MPI Rank 0: 		Built time: Jan 10 2018 22:47:38
MPI Rank 0: 		Last modified date: Wed Jan 10 22:18:32 2018
MPI Rank 0: 		Build type: Release
MPI Rank 0: 		Build target: GPU
MPI Rank 0: 		With ASGD: yes
MPI Rank 0: 		Math lib: mkl
MPI Rank 0: 		CUDA version: 9.0.0
MPI Rank 0: 		CUDNN version: 7.0.5
MPI Rank 0: 		Build Branch: HEAD
MPI Rank 0: 		Build SHA1: db192cd3cb9ac688cae719c41e5930a4e3f628ea
MPI Rank 0: 		MPI distribution: Microsoft MPI
MPI Rank 0: 		MPI version: 7.0.12437.6
MPI Rank 0: -------------------------------------------------------------------
MPI Rank 0: -------------------------------------------------------------------
MPI Rank 0: GPU info:
MPI Rank 0: 
MPI Rank 0: 		Device[0]: cores = 3072; computeCapability = 5.2; type = "Tesla M60"; total memory = 8124 MB; free memory = 8001 MB
MPI Rank 0: -------------------------------------------------------------------
MPI Rank 0: 01/11/2018 08:54:29: Using 3 CPU threads.
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: ##############################################################################
MPI Rank 0: 01/11/2018 08:54:29: #                                                                            #
MPI Rank 0: 01/11/2018 08:54:29: # speechTrain command (train action)                                         #
MPI Rank 0: 01/11/2018 08:54:29: #                                                                            #
MPI Rank 0: 01/11/2018 08:54:29: ##############################################################################
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: 
MPI Rank 0: Creating virgin network.
MPI Rank 0: SimpleNetworkBuilder Using GPU 0
MPI Rank 0: Reading script file glob_0000.scp ... 948 entries
MPI Rank 0: HTKDeserializer: selected '948' utterances grouped into '3' chunks, average chunk size: 316.0 utterances, 84244.7 frames (for I/O: 316.0 utterances, 84244.7 frames)
MPI Rank 0: HTKDeserializer: determined feature kind as '33'-dimensional 'USER' with frame shift 10.0 ms
MPI Rank 0: Total (133) state names in state list 'C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data/state.list'
MPI Rank 0: MLFDeserializer: '948' utterances with '252734' frames
MPI Rank 0: Reading script file glob_0000.cv.scp ... 300 entries
MPI Rank 0: HTKDeserializer: selected '300' utterances grouped into '1' chunks, average chunk size: 300.0 utterances, 83050.0 frames (for I/O: 300.0 utterances, 83050.0 frames)
MPI Rank 0: HTKDeserializer: determined feature kind as '33'-dimensional 'USER' with frame shift 10.0 ms
MPI Rank 0: Total (133) state names in state list 'C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data/state.list'
MPI Rank 0: MLFDeserializer: '948' utterances with '252734' frames
MPI Rank 0: 01/11/2018 08:54:29: 
MPI Rank 0: Model has 25 nodes. Using GPU 0.
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: Training criterion:   CrossEntropyWithSoftmax = CrossEntropyWithSoftmax
MPI Rank 0: 01/11/2018 08:54:29: Evaluation criterion: EvalClassificationError = ClassificationError
MPI Rank 0: 
MPI Rank 0: 
MPI Rank 0: Allocating matrices for forward and/or backward propagation.
MPI Rank 0: 
MPI Rank 0: Gradient Memory Aliasing: 4 are aliased.
MPI Rank 0: 	W1*H1 (gradient) reuses W1*H1+B1 (gradient)
MPI Rank 0: 	W2*H1 (gradient) reuses HLast (gradient)
MPI Rank 0: 
MPI Rank 0: Memory Sharing: Out of 40 matrices, 20 are shared as 5, and 20 are not shared.
MPI Rank 0: 
MPI Rank 0: Here are the ones that share memory:
MPI Rank 0: 	{ PosteriorProb : [132 x 1 x *]
MPI Rank 0: 	  ScaledLogLikelihood : [132 x 1 x *] }
MPI Rank 0: 	{ H2 : [512 x 1 x *]
MPI Rank 0: 	  W0*features+B0 : [512 x 1 x *]
MPI Rank 0: 	  W1 : [512 x 512] (gradient)
MPI Rank 0: 	  W1*H1 : [512 x 1 x *] }
MPI Rank 0: 	{ HLast : [132 x 1 x *] (gradient)
MPI Rank 0: 	  W0*features+B0 : [512 x 1 x *] (gradient)
MPI Rank 0: 	  W1*H1 : [512 x 1 x *] (gradient)
MPI Rank 0: 	  W1*H1+B1 : [512 x 1 x *] (gradient)
MPI Rank 0: 	  W2*H1 : [132 x 1 x *]
MPI Rank 0: 	  W2*H1 : [132 x 1 x *] (gradient) }
MPI Rank 0: 	{ H1 : [512 x 1 x *] (gradient)
MPI Rank 0: 	  H2 : [512 x 1 x *] (gradient)
MPI Rank 0: 	  HLast : [132 x 1 x *]
MPI Rank 0: 	  W0*features : [512 x *] (gradient)
MPI Rank 0: 	  W1*H1+B1 : [512 x 1 x *] }
MPI Rank 0: 	{ H1 : [512 x 1 x *]
MPI Rank 0: 	  W0 : [512 x 363] (gradient)
MPI Rank 0: 	  W0*features : [512 x *] }
MPI Rank 0: 
MPI Rank 0: Here are the ones that don't share memory:
MPI Rank 0: 	{features : [363 x *]}
MPI Rank 0: 	{MeanOfFeatures : [363]}
MPI Rank 0: 	{InvStdOfFeatures : [363]}
MPI Rank 0: 	{B0 : [512 x 1]}
MPI Rank 0: 	{B1 : [512 x 1]}
MPI Rank 0: 	{labels : [132 x *]}
MPI Rank 0: 	{Prior : [132]}
MPI Rank 0: 	{EvalClassificationError : [1]}
MPI Rank 0: 	{B2 : [132 x 1]}
MPI Rank 0: 	{W2 : [132 x 512]}
MPI Rank 0: 	{W0 : [512 x 363]}
MPI Rank 0: 	{W1 : [512 x 512]}
MPI Rank 0: 	{B2 : [132 x 1] (gradient)}
MPI Rank 0: 	{LogOfPrior : [132]}
MPI Rank 0: 	{B0 : [512 x 1] (gradient)}
MPI Rank 0: 	{CrossEntropyWithSoftmax : [1] (gradient)}
MPI Rank 0: 	{W2 : [132 x 512] (gradient)}
MPI Rank 0: 	{B1 : [512 x 1] (gradient)}
MPI Rank 0: 	{MVNormalizedFeatures : [363 x *]}
MPI Rank 0: 	{CrossEntropyWithSoftmax : [1]}
MPI Rank 0: 
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: Training 516740 parameters in 6 out of 6 parameter tensors and 15 nodes with gradient:
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: 	Node 'B0' (LearnableParameter operation) : [512 x 1]
MPI Rank 0: 01/11/2018 08:54:29: 	Node 'B1' (LearnableParameter operation) : [512 x 1]
MPI Rank 0: 01/11/2018 08:54:29: 	Node 'B2' (LearnableParameter operation) : [132 x 1]
MPI Rank 0: 01/11/2018 08:54:29: 	Node 'W0' (LearnableParameter operation) : [512 x 363]
MPI Rank 0: 01/11/2018 08:54:29: 	Node 'W1' (LearnableParameter operation) : [512 x 512]
MPI Rank 0: 01/11/2018 08:54:29: 	Node 'W2' (LearnableParameter operation) : [132 x 512]
MPI Rank 0: 
MPI Rank 0: Initializing dataParallelSGD with FP64 aggregation.
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: Precomputing --> 3 PreCompute nodes found.
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:29: 	MeanOfFeatures = Mean()
MPI Rank 0: 01/11/2018 08:54:29: 	InvStdOfFeatures = InvStdDev()
MPI Rank 0: 01/11/2018 08:54:29: 	Prior = Mean()
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:32: Precomputing --> Completed.
MPI Rank 0: 
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:34: Starting Epoch 1: learning rate per sample = 0.015625  effective momentum = 0.900000  momentum as time constant = 607.4 samples
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:34: Starting minibatch loop, DataParallelSGD training (myRank = 0, numNodes = 2, numGradientBits = 64), distributed reading is ENABLED.
MPI Rank 0: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[   1-  10, 3.13%]: CrossEntropyWithSoftmax = 4.62512789 * 640; EvalClassificationError = 0.94062500 * 640; time = 0.0846s; samplesPerSecond = 7569.4
MPI Rank 0: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  11-  20, 6.25%]: CrossEntropyWithSoftmax = 4.35619366 * 640; EvalClassificationError = 0.92343750 * 640; time = 0.0661s; samplesPerSecond = 9678.6
MPI Rank 0: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  21-  30, 9.38%]: CrossEntropyWithSoftmax = 3.97911998 * 640; EvalClassificationError = 0.89531250 * 640; time = 0.0669s; samplesPerSecond = 9561.8
MPI Rank 0: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  31-  40, 12.50%]: CrossEntropyWithSoftmax = 3.73643568 * 640; EvalClassificationError = 0.84531250 * 640; time = 0.0675s; samplesPerSecond = 9485.1
MPI Rank 0: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  41-  50, 15.63%]: CrossEntropyWithSoftmax = 3.83079081 * 640; EvalClassificationError = 0.88281250 * 640; time = 0.0658s; samplesPerSecond = 9723.0
MPI Rank 0: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  51-  60, 18.75%]: CrossEntropyWithSoftmax = 3.71437690 * 640; EvalClassificationError = 0.86875000 * 640; time = 0.0646s; samplesPerSecond = 9914.6
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  61-  70, 21.88%]: CrossEntropyWithSoftmax = 3.42186231 * 640; EvalClassificationError = 0.79062500 * 640; time = 0.0651s; samplesPerSecond = 9833.1
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  71-  80, 25.00%]: CrossEntropyWithSoftmax = 3.53658053 * 640; EvalClassificationError = 0.82031250 * 640; time = 0.0692s; samplesPerSecond = 9250.3
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  81-  90, 28.13%]: CrossEntropyWithSoftmax = 3.49758018 * 640; EvalClassificationError = 0.81718750 * 640; time = 0.0673s; samplesPerSecond = 9502.9
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  91- 100, 31.25%]: CrossEntropyWithSoftmax = 3.39996308 * 640; EvalClassificationError = 0.80468750 * 640; time = 0.0681s; samplesPerSecond = 9396.6
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 101- 110, 34.38%]: CrossEntropyWithSoftmax = 3.49445773 * 640; EvalClassificationError = 0.82500000 * 640; time = 0.0684s; samplesPerSecond = 9363.0
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 111- 120, 37.50%]: CrossEntropyWithSoftmax = 3.26676999 * 640; EvalClassificationError = 0.79218750 * 640; time = 0.0650s; samplesPerSecond = 9850.2
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 121- 130, 40.63%]: CrossEntropyWithSoftmax = 3.18870174 * 640; EvalClassificationError = 0.78906250 * 640; time = 0.0644s; samplesPerSecond = 9938.5
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 131- 140, 43.75%]: CrossEntropyWithSoftmax = 3.05687264 * 640; EvalClassificationError = 0.74687500 * 640; time = 0.0667s; samplesPerSecond = 9592.7
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 141- 150, 46.88%]: CrossEntropyWithSoftmax = 2.95594570 * 640; EvalClassificationError = 0.71875000 * 640; time = 0.0665s; samplesPerSecond = 9616.8
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 151- 160, 50.00%]: CrossEntropyWithSoftmax = 3.10219605 * 640; EvalClassificationError = 0.74062500 * 640; time = 0.0693s; samplesPerSecond = 9234.7
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 161- 170, 53.13%]: CrossEntropyWithSoftmax = 2.80745016 * 640; EvalClassificationError = 0.70625000 * 640; time = 0.0662s; samplesPerSecond = 9667.0
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 171- 180, 56.25%]: CrossEntropyWithSoftmax = 2.72061843 * 640; EvalClassificationError = 0.65468750 * 640; time = 0.0654s; samplesPerSecond = 9787.5
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 181- 190, 59.38%]: CrossEntropyWithSoftmax = 2.80425748 * 640; EvalClassificationError = 0.71718750 * 640; time = 0.0654s; samplesPerSecond = 9789.8
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 191- 200, 62.50%]: CrossEntropyWithSoftmax = 2.71253069 * 640; EvalClassificationError = 0.67812500 * 640; time = 0.0658s; samplesPerSecond = 9729.2
MPI Rank 0: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 201- 210, 65.63%]: CrossEntropyWithSoftmax = 2.59360400 * 640; EvalClassificationError = 0.66093750 * 640; time = 0.0667s; samplesPerSecond = 9595.5
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 211- 220, 68.75%]: CrossEntropyWithSoftmax = 2.60386650 * 640; EvalClassificationError = 0.65625000 * 640; time = 0.0670s; samplesPerSecond = 9551.1
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 221- 230, 71.88%]: CrossEntropyWithSoftmax = 2.53706679 * 640; EvalClassificationError = 0.65625000 * 640; time = 0.0691s; samplesPerSecond = 9257.9
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 231- 240, 75.00%]: CrossEntropyWithSoftmax = 2.56177344 * 640; EvalClassificationError = 0.65625000 * 640; time = 0.0648s; samplesPerSecond = 9873.5
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 241- 250, 78.13%]: CrossEntropyWithSoftmax = 2.50118792 * 640; EvalClassificationError = 0.64218750 * 640; time = 0.0650s; samplesPerSecond = 9846.3
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 251- 260, 81.25%]: CrossEntropyWithSoftmax = 2.40119789 * 640; EvalClassificationError = 0.62500000 * 640; time = 0.0664s; samplesPerSecond = 9638.7
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 261- 270, 84.38%]: CrossEntropyWithSoftmax = 2.27491504 * 640; EvalClassificationError = 0.58906250 * 640; time = 0.0665s; samplesPerSecond = 9629.7
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 271- 280, 87.50%]: CrossEntropyWithSoftmax = 2.51724208 * 640; EvalClassificationError = 0.65781250 * 640; time = 0.0670s; samplesPerSecond = 9550.3
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 281- 290, 90.63%]: CrossEntropyWithSoftmax = 2.27797543 * 640; EvalClassificationError = 0.59687500 * 640; time = 0.0704s; samplesPerSecond = 9089.7
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 291- 300, 93.75%]: CrossEntropyWithSoftmax = 2.26017741 * 640; EvalClassificationError = 0.60937500 * 640; time = 0.0689s; samplesPerSecond = 9286.6
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 301- 310, 96.88%]: CrossEntropyWithSoftmax = 2.24735343 * 640; EvalClassificationError = 0.58437500 * 640; time = 0.0668s; samplesPerSecond = 9587.8
MPI Rank 0: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 311- 320, 100.00%]: CrossEntropyWithSoftmax = 2.23665382 * 640; EvalClassificationError = 0.60625000 * 640; time = 0.0646s; samplesPerSecond = 9906.9
MPI Rank 0: 01/11/2018 08:54:36: Finished Epoch[ 1 of 3]: [Training] CrossEntropyWithSoftmax = 3.03815142 * 20480; EvalClassificationError = 0.73432617 * 20480; totalSamplesSeen = 20480; learningRatePerSample = 0.015625; epochTime=2.1648s
MPI Rank 0: 01/11/2018 08:54:38: Final Results: Minibatch[1-1299]: CrossEntropyWithSoftmax = 2.24821048 * 83050; perplexity = 9.47077252; EvalClassificationError = 0.61623119 * 83050
MPI Rank 0: 01/11/2018 08:54:38: Finished Epoch[ 1 of 3]: [Validate] CrossEntropyWithSoftmax = 2.24821048 * 83050; EvalClassificationError = 0.61623119 * 83050
MPI Rank 0: 01/11/2018 08:54:38: SGD: Saving checkpoint model 'C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/models/cntkSpeech.dnn.1'
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:38: Starting Epoch 2: learning rate per sample = 0.001953  effective momentum = 0.656119  momentum as time constant = 607.5 samples
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:38: Starting minibatch loop, DataParallelSGD training (myRank = 0, numNodes = 2, numGradientBits = 64), distributed reading is ENABLED.
MPI Rank 0: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[   1-  10, 12.50%]: CrossEntropyWithSoftmax = 2.13894071 * 2560; EvalClassificationError = 0.56992188 * 2560; time = 0.1772s; samplesPerSecond = 14448.9
MPI Rank 0: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  11-  20, 25.00%]: CrossEntropyWithSoftmax = 2.06106261 * 2560; EvalClassificationError = 0.55664063 * 2560; time = 0.1268s; samplesPerSecond = 20188.5
MPI Rank 0: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  21-  30, 37.50%]: CrossEntropyWithSoftmax = 2.04459475 * 2560; EvalClassificationError = 0.55039063 * 2560; time = 0.1236s; samplesPerSecond = 20704.3
MPI Rank 0: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  31-  40, 50.00%]: CrossEntropyWithSoftmax = 2.03347291 * 2560; EvalClassificationError = 0.55742187 * 2560; time = 0.1259s; samplesPerSecond = 20329.1
MPI Rank 0: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  41-  50, 62.50%]: CrossEntropyWithSoftmax = 2.02079287 * 2560; EvalClassificationError = 0.54414063 * 2560; time = 0.1203s; samplesPerSecond = 21277.6
MPI Rank 0: 01/11/2018 08:54:39:  Epoch[ 2 of 3]-Minibatch[  51-  60, 75.00%]: CrossEntropyWithSoftmax = 1.96950012 * 2560; EvalClassificationError = 0.53085938 * 2560; time = 0.1272s; samplesPerSecond = 20127.9
MPI Rank 0: 01/11/2018 08:54:39:  Epoch[ 2 of 3]-Minibatch[  61-  70, 87.50%]: CrossEntropyWithSoftmax = 1.95934863 * 2560; EvalClassificationError = 0.52812500 * 2560; time = 0.1218s; samplesPerSecond = 21022.8
MPI Rank 0: 01/11/2018 08:54:39:  Epoch[ 2 of 3]-Minibatch[  71-  80, 100.00%]: CrossEntropyWithSoftmax = 1.94070839 * 2560; EvalClassificationError = 0.53125000 * 2560; time = 0.1203s; samplesPerSecond = 21271.3
MPI Rank 0: 01/11/2018 08:54:39: Finished Epoch[ 2 of 3]: [Training] CrossEntropyWithSoftmax = 2.02105263 * 20480; EvalClassificationError = 0.54609375 * 20480; totalSamplesSeen = 40960; learningRatePerSample = 0.001953125; epochTime=1.05056s
MPI Rank 0: 01/11/2018 08:54:40: Final Results: Minibatch[1-326]: CrossEntropyWithSoftmax = 1.92733488 * 83050; perplexity = 6.87117334; EvalClassificationError = 0.53122216 * 83050
MPI Rank 0: 01/11/2018 08:54:40: Finished Epoch[ 2 of 3]: [Validate] CrossEntropyWithSoftmax = 1.92733488 * 83050; EvalClassificationError = 0.53122216 * 83050
MPI Rank 0: 01/11/2018 08:54:40: SGD: Saving checkpoint model 'C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/models/cntkSpeech.dnn.2'
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:40: Starting Epoch 3: learning rate per sample = 0.000098  effective momentum = 0.656119  momentum as time constant = 2429.9 samples
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:40: Starting minibatch loop, DataParallelSGD training (myRank = 0, numNodes = 2, numGradientBits = 64), distributed reading is ENABLED.
MPI Rank 0: 01/11/2018 08:54:40:  Epoch[ 3 of 3]-Minibatch[   1-  10, 50.00%]: CrossEntropyWithSoftmax = 1.94336420 * 10240; EvalClassificationError = 0.53056641 * 10240; time = 0.3976s; samplesPerSecond = 25753.9
MPI Rank 0: 01/11/2018 08:54:41:  Epoch[ 3 of 3]-Minibatch[  11-  20, 100.00%]: CrossEntropyWithSoftmax = 1.96525554 * 10240; EvalClassificationError = 0.54873047 * 10240; time = 0.3544s; samplesPerSecond = 28897.5
MPI Rank 0: 01/11/2018 08:54:41: Finished Epoch[ 3 of 3]: [Training] CrossEntropyWithSoftmax = 1.95430987 * 20480; EvalClassificationError = 0.53964844 * 20480; totalSamplesSeen = 61440; learningRatePerSample = 9.7656251e-05; epochTime=0.759101s
MPI Rank 0: 01/11/2018 08:54:41: Final Results: Minibatch[1-83]: CrossEntropyWithSoftmax = 1.90639119 * 83050; perplexity = 6.72876211; EvalClassificationError = 0.52304636 * 83050
MPI Rank 0: 01/11/2018 08:54:41: Finished Epoch[ 3 of 3]: [Validate] CrossEntropyWithSoftmax = 1.90639119 * 83050; EvalClassificationError = 0.52304636 * 83050
MPI Rank 0: 01/11/2018 08:54:41: SGD: Saving checkpoint model 'C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/models/cntkSpeech.dnn'
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:42: Action "train" complete.
MPI Rank 0: 
MPI Rank 0: 01/11/2018 08:54:42: __COMPLETED__
MPI Rank 1: 01/11/2018 08:54:29: Redirecting stderr to file C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr_speechTrain.logrank1
MPI Rank 1: CNTK 2.3.1+ (HEAD db192c, Jan 10 2018 22:59:43) at 2018/01/11 08:54:28
MPI Rank 1: 
MPI Rank 1: C:\jenkins\workspace\CNTK-Test-Windows-W1\x64\release\cntk.exe  configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation/cntkcv.cntk  currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  RunDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data  ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\DNN\ParallelCrossValidation  OutputDir=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu  DeviceId=0  timestamping=true  numCPUThreads=3  shareNodeValueMatrices=true  stderr=C:\local\cygwin-2.8.2-x64\tmp\cntk-test-20180111085400.505371\Speech\DNN_ParallelCrossValidation@release_gpu/stderr
MPI Rank 1: -------------------------------------------------------------------
MPI Rank 1: Build info: 
MPI Rank 1: 
MPI Rank 1: 		Built time: Jan 10 2018 22:47:38
MPI Rank 1: 		Last modified date: Wed Jan 10 22:18:32 2018
MPI Rank 1: 		Build type: Release
MPI Rank 1: 		Build target: GPU
MPI Rank 1: 		With ASGD: yes
MPI Rank 1: 		Math lib: mkl
MPI Rank 1: 		CUDA version: 9.0.0
MPI Rank 1: 		CUDNN version: 7.0.5
MPI Rank 1: 		Build Branch: HEAD
MPI Rank 1: 		Build SHA1: db192cd3cb9ac688cae719c41e5930a4e3f628ea
MPI Rank 1: 		MPI distribution: Microsoft MPI
MPI Rank 1: 		MPI version: 7.0.12437.6
MPI Rank 1: -------------------------------------------------------------------
MPI Rank 1: -------------------------------------------------------------------
MPI Rank 1: GPU info:
MPI Rank 1: 
MPI Rank 1: 		Device[0]: cores = 3072; computeCapability = 5.2; type = "Tesla M60"; total memory = 8124 MB; free memory = 7906 MB
MPI Rank 1: -------------------------------------------------------------------
MPI Rank 1: 01/11/2018 08:54:29: Using 3 CPU threads.
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:29: ##############################################################################
MPI Rank 1: 01/11/2018 08:54:29: #                                                                            #
MPI Rank 1: 01/11/2018 08:54:29: # speechTrain command (train action)                                         #
MPI Rank 1: 01/11/2018 08:54:29: #                                                                            #
MPI Rank 1: 01/11/2018 08:54:29: ##############################################################################
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:29: 
MPI Rank 1: Creating virgin network.
MPI Rank 1: SimpleNetworkBuilder Using GPU 0
MPI Rank 1: Reading script file glob_0000.scp ... 948 entries
MPI Rank 1: HTKDeserializer: selected '948' utterances grouped into '3' chunks, average chunk size: 316.0 utterances, 84244.7 frames (for I/O: 316.0 utterances, 84244.7 frames)
MPI Rank 1: HTKDeserializer: determined feature kind as '33'-dimensional 'USER' with frame shift 10.0 ms
MPI Rank 1: Total (133) state names in state list 'C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data/state.list'
MPI Rank 1: MLFDeserializer: '948' utterances with '252734' frames
MPI Rank 1: Reading script file glob_0000.cv.scp ... 300 entries
MPI Rank 1: HTKDeserializer: selected '300' utterances grouped into '1' chunks, average chunk size: 300.0 utterances, 83050.0 frames (for I/O: 300.0 utterances, 83050.0 frames)
MPI Rank 1: HTKDeserializer: determined feature kind as '33'-dimensional 'USER' with frame shift 10.0 ms
MPI Rank 1: Total (133) state names in state list 'C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Speech\Data/state.list'
MPI Rank 1: MLFDeserializer: '948' utterances with '252734' frames
MPI Rank 1: 01/11/2018 08:54:30: 
MPI Rank 1: Model has 25 nodes. Using GPU 0.
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:30: Training criterion:   CrossEntropyWithSoftmax = CrossEntropyWithSoftmax
MPI Rank 1: 01/11/2018 08:54:30: Evaluation criterion: EvalClassificationError = ClassificationError
MPI Rank 1: 
MPI Rank 1: 
MPI Rank 1: Allocating matrices for forward and/or backward propagation.
MPI Rank 1: 
MPI Rank 1: Gradient Memory Aliasing: 4 are aliased.
MPI Rank 1: 	W1*H1 (gradient) reuses W1*H1+B1 (gradient)
MPI Rank 1: 	W2*H1 (gradient) reuses HLast (gradient)
MPI Rank 1: 
MPI Rank 1: Memory Sharing: Out of 40 matrices, 20 are shared as 5, and 20 are not shared.
MPI Rank 1: 
MPI Rank 1: Here are the ones that share memory:
MPI Rank 1: 	{ PosteriorProb : [132 x 1 x *]
MPI Rank 1: 	  ScaledLogLikelihood : [132 x 1 x *] }
MPI Rank 1: 	{ H1 : [512 x 1 x *] (gradient)
MPI Rank 1: 	  H2 : [512 x 1 x *] (gradient)
MPI Rank 1: 	  HLast : [132 x 1 x *]
MPI Rank 1: 	  W0*features : [512 x *] (gradient)
MPI Rank 1: 	  W1*H1+B1 : [512 x 1 x *] }
MPI Rank 1: 	{ HLast : [132 x 1 x *] (gradient)
MPI Rank 1: 	  W0*features+B0 : [512 x 1 x *] (gradient)
MPI Rank 1: 	  W1*H1 : [512 x 1 x *] (gradient)
MPI Rank 1: 	  W1*H1+B1 : [512 x 1 x *] (gradient)
MPI Rank 1: 	  W2*H1 : [132 x 1 x *]
MPI Rank 1: 	  W2*H1 : [132 x 1 x *] (gradient) }
MPI Rank 1: 	{ H1 : [512 x 1 x *]
MPI Rank 1: 	  W0 : [512 x 363] (gradient)
MPI Rank 1: 	  W0*features : [512 x *] }
MPI Rank 1: 	{ H2 : [512 x 1 x *]
MPI Rank 1: 	  W0*features+B0 : [512 x 1 x *]
MPI Rank 1: 	  W1 : [512 x 512] (gradient)
MPI Rank 1: 	  W1*H1 : [512 x 1 x *] }
MPI Rank 1: 
MPI Rank 1: Here are the ones that don't share memory:
MPI Rank 1: 	{features : [363 x *]}
MPI Rank 1: 	{B2 : [132 x 1]}
MPI Rank 1: 	{labels : [132 x *]}
MPI Rank 1: 	{Prior : [132]}
MPI Rank 1: 	{EvalClassificationError : [1]}
MPI Rank 1: 	{InvStdOfFeatures : [363]}
MPI Rank 1: 	{MeanOfFeatures : [363]}
MPI Rank 1: 	{W0 : [512 x 363]}
MPI Rank 1: 	{W1 : [512 x 512]}
MPI Rank 1: 	{B1 : [512 x 1]}
MPI Rank 1: 	{W2 : [132 x 512]}
MPI Rank 1: 	{B0 : [512 x 1]}
MPI Rank 1: 	{B2 : [132 x 1] (gradient)}
MPI Rank 1: 	{CrossEntropyWithSoftmax : [1] (gradient)}
MPI Rank 1: 	{LogOfPrior : [132]}
MPI Rank 1: 	{W2 : [132 x 512] (gradient)}
MPI Rank 1: 	{CrossEntropyWithSoftmax : [1]}
MPI Rank 1: 	{B1 : [512 x 1] (gradient)}
MPI Rank 1: 	{B0 : [512 x 1] (gradient)}
MPI Rank 1: 	{MVNormalizedFeatures : [363 x *]}
MPI Rank 1: 
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:30: Training 516740 parameters in 6 out of 6 parameter tensors and 15 nodes with gradient:
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:30: 	Node 'B0' (LearnableParameter operation) : [512 x 1]
MPI Rank 1: 01/11/2018 08:54:30: 	Node 'B1' (LearnableParameter operation) : [512 x 1]
MPI Rank 1: 01/11/2018 08:54:30: 	Node 'B2' (LearnableParameter operation) : [132 x 1]
MPI Rank 1: 01/11/2018 08:54:30: 	Node 'W0' (LearnableParameter operation) : [512 x 363]
MPI Rank 1: 01/11/2018 08:54:30: 	Node 'W1' (LearnableParameter operation) : [512 x 512]
MPI Rank 1: 01/11/2018 08:54:30: 	Node 'W2' (LearnableParameter operation) : [132 x 512]
MPI Rank 1: 
MPI Rank 1: Initializing dataParallelSGD with FP64 aggregation.
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:30: Precomputing --> 3 PreCompute nodes found.
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:30: 	MeanOfFeatures = Mean()
MPI Rank 1: 01/11/2018 08:54:30: 	InvStdOfFeatures = InvStdDev()
MPI Rank 1: 01/11/2018 08:54:30: 	Prior = Mean()
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:34: Precomputing --> Completed.
MPI Rank 1: 
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:34: Starting Epoch 1: learning rate per sample = 0.015625  effective momentum = 0.900000  momentum as time constant = 607.4 samples
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:34: Starting minibatch loop, DataParallelSGD training (myRank = 1, numNodes = 2, numGradientBits = 64), distributed reading is ENABLED.
MPI Rank 1: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[   1-  10, 3.13%]: CrossEntropyWithSoftmax = 4.62512789 * 640; EvalClassificationError = 0.94062500 * 640; time = 0.0850s; samplesPerSecond = 7530.5
MPI Rank 1: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  11-  20, 6.25%]: CrossEntropyWithSoftmax = 4.35619366 * 640; EvalClassificationError = 0.92343750 * 640; time = 0.0661s; samplesPerSecond = 9676.3
MPI Rank 1: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  21-  30, 9.38%]: CrossEntropyWithSoftmax = 3.97911998 * 640; EvalClassificationError = 0.89531250 * 640; time = 0.0670s; samplesPerSecond = 9557.7
MPI Rank 1: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  31-  40, 12.50%]: CrossEntropyWithSoftmax = 3.73643568 * 640; EvalClassificationError = 0.84531250 * 640; time = 0.0663s; samplesPerSecond = 9652.3
MPI Rank 1: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  41-  50, 15.63%]: CrossEntropyWithSoftmax = 3.83079081 * 640; EvalClassificationError = 0.88281250 * 640; time = 0.0658s; samplesPerSecond = 9722.2
MPI Rank 1: 01/11/2018 08:54:34:  Epoch[ 1 of 3]-Minibatch[  51-  60, 18.75%]: CrossEntropyWithSoftmax = 3.71437690 * 640; EvalClassificationError = 0.86875000 * 640; time = 0.0646s; samplesPerSecond = 9914.3
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  61-  70, 21.88%]: CrossEntropyWithSoftmax = 3.42186231 * 640; EvalClassificationError = 0.79062500 * 640; time = 0.0660s; samplesPerSecond = 9702.9
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  71-  80, 25.00%]: CrossEntropyWithSoftmax = 3.53658053 * 640; EvalClassificationError = 0.82031250 * 640; time = 0.0692s; samplesPerSecond = 9248.4
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  81-  90, 28.13%]: CrossEntropyWithSoftmax = 3.49758018 * 640; EvalClassificationError = 0.81718750 * 640; time = 0.0674s; samplesPerSecond = 9502.5
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[  91- 100, 31.25%]: CrossEntropyWithSoftmax = 3.39996308 * 640; EvalClassificationError = 0.80468750 * 640; time = 0.0677s; samplesPerSecond = 9452.9
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 101- 110, 34.38%]: CrossEntropyWithSoftmax = 3.49445773 * 640; EvalClassificationError = 0.82500000 * 640; time = 0.0679s; samplesPerSecond = 9425.9
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 111- 120, 37.50%]: CrossEntropyWithSoftmax = 3.26676999 * 640; EvalClassificationError = 0.79218750 * 640; time = 0.0650s; samplesPerSecond = 9848.6
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 121- 130, 40.63%]: CrossEntropyWithSoftmax = 3.18870174 * 640; EvalClassificationError = 0.78906250 * 640; time = 0.0644s; samplesPerSecond = 9942.3
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 131- 140, 43.75%]: CrossEntropyWithSoftmax = 3.05687264 * 640; EvalClassificationError = 0.74687500 * 640; time = 0.0667s; samplesPerSecond = 9588.5
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 141- 150, 46.88%]: CrossEntropyWithSoftmax = 2.95594570 * 640; EvalClassificationError = 0.71875000 * 640; time = 0.0674s; samplesPerSecond = 9493.2
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 151- 160, 50.00%]: CrossEntropyWithSoftmax = 3.10219605 * 640; EvalClassificationError = 0.74062500 * 640; time = 0.0693s; samplesPerSecond = 9234.1
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 161- 170, 53.13%]: CrossEntropyWithSoftmax = 2.80745016 * 640; EvalClassificationError = 0.70625000 * 640; time = 0.0653s; samplesPerSecond = 9799.5
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 171- 180, 56.25%]: CrossEntropyWithSoftmax = 2.72061843 * 640; EvalClassificationError = 0.65468750 * 640; time = 0.0654s; samplesPerSecond = 9786.8
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 181- 190, 59.38%]: CrossEntropyWithSoftmax = 2.80425748 * 640; EvalClassificationError = 0.71718750 * 640; time = 0.0654s; samplesPerSecond = 9787.0
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 191- 200, 62.50%]: CrossEntropyWithSoftmax = 2.71253069 * 640; EvalClassificationError = 0.67812500 * 640; time = 0.0667s; samplesPerSecond = 9600.3
MPI Rank 1: 01/11/2018 08:54:35:  Epoch[ 1 of 3]-Minibatch[ 201- 210, 65.63%]: CrossEntropyWithSoftmax = 2.59360400 * 640; EvalClassificationError = 0.66093750 * 640; time = 0.0667s; samplesPerSecond = 9596.2
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 211- 220, 68.75%]: CrossEntropyWithSoftmax = 2.60386650 * 640; EvalClassificationError = 0.65625000 * 640; time = 0.0670s; samplesPerSecond = 9550.0
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 221- 230, 71.88%]: CrossEntropyWithSoftmax = 2.53706679 * 640; EvalClassificationError = 0.65625000 * 640; time = 0.0682s; samplesPerSecond = 9377.4
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 231- 240, 75.00%]: CrossEntropyWithSoftmax = 2.56177344 * 640; EvalClassificationError = 0.65625000 * 640; time = 0.0648s; samplesPerSecond = 9874.3
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 241- 250, 78.13%]: CrossEntropyWithSoftmax = 2.50118792 * 640; EvalClassificationError = 0.64218750 * 640; time = 0.0650s; samplesPerSecond = 9846.6
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 251- 260, 81.25%]: CrossEntropyWithSoftmax = 2.40119789 * 640; EvalClassificationError = 0.62500000 * 640; time = 0.0673s; samplesPerSecond = 9511.9
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 261- 270, 84.38%]: CrossEntropyWithSoftmax = 2.27491504 * 640; EvalClassificationError = 0.58906250 * 640; time = 0.0665s; samplesPerSecond = 9628.2
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 271- 280, 87.50%]: CrossEntropyWithSoftmax = 2.51724208 * 640; EvalClassificationError = 0.65781250 * 640; time = 0.0670s; samplesPerSecond = 9550.6
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 281- 290, 90.63%]: CrossEntropyWithSoftmax = 2.27797543 * 640; EvalClassificationError = 0.59687500 * 640; time = 0.0704s; samplesPerSecond = 9093.0
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 291- 300, 93.75%]: CrossEntropyWithSoftmax = 2.26017741 * 640; EvalClassificationError = 0.60937500 * 640; time = 0.0681s; samplesPerSecond = 9400.6
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 301- 310, 96.88%]: CrossEntropyWithSoftmax = 2.24735343 * 640; EvalClassificationError = 0.58437500 * 640; time = 0.0668s; samplesPerSecond = 9587.4
MPI Rank 1: 01/11/2018 08:54:36:  Epoch[ 1 of 3]-Minibatch[ 311- 320, 100.00%]: CrossEntropyWithSoftmax = 2.23665382 * 640; EvalClassificationError = 0.60625000 * 640; time = 0.0646s; samplesPerSecond = 9909.0
MPI Rank 1: 01/11/2018 08:54:36: Finished Epoch[ 1 of 3]: [Training] CrossEntropyWithSoftmax = 3.03815142 * 20480; EvalClassificationError = 0.73432617 * 20480; totalSamplesSeen = 20480; learningRatePerSample = 0.015625; epochTime=2.16519s
MPI Rank 1: 01/11/2018 08:54:38: Final Results: Minibatch[1-1299]: CrossEntropyWithSoftmax = 2.24821048 * 83050; perplexity = 9.47077252; EvalClassificationError = 0.61623119 * 83050
MPI Rank 1: 01/11/2018 08:54:38: Finished Epoch[ 1 of 3]: [Validate] CrossEntropyWithSoftmax = 2.24821048 * 83050; EvalClassificationError = 0.61623119 * 83050
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:38: Starting Epoch 2: learning rate per sample = 0.001953  effective momentum = 0.656119  momentum as time constant = 607.5 samples
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:38: Starting minibatch loop, DataParallelSGD training (myRank = 1, numNodes = 2, numGradientBits = 64), distributed reading is ENABLED.
MPI Rank 1: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[   1-  10, 12.50%]: CrossEntropyWithSoftmax = 2.13894071 * 2560; EvalClassificationError = 0.56992188 * 2560; time = 0.1771s; samplesPerSecond = 14459.2
MPI Rank 1: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  11-  20, 25.00%]: CrossEntropyWithSoftmax = 2.06106261 * 2560; EvalClassificationError = 0.55664063 * 2560; time = 0.1268s; samplesPerSecond = 20190.0
MPI Rank 1: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  21-  30, 37.50%]: CrossEntropyWithSoftmax = 2.04459475 * 2560; EvalClassificationError = 0.55039063 * 2560; time = 0.1236s; samplesPerSecond = 20705.3
MPI Rank 1: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  31-  40, 50.00%]: CrossEntropyWithSoftmax = 2.03347291 * 2560; EvalClassificationError = 0.55742187 * 2560; time = 0.1259s; samplesPerSecond = 20330.0
MPI Rank 1: 01/11/2018 08:54:38:  Epoch[ 2 of 3]-Minibatch[  41-  50, 62.50%]: CrossEntropyWithSoftmax = 2.02079287 * 2560; EvalClassificationError = 0.54414063 * 2560; time = 0.1203s; samplesPerSecond = 21279.8
MPI Rank 1: 01/11/2018 08:54:39:  Epoch[ 2 of 3]-Minibatch[  51-  60, 75.00%]: CrossEntropyWithSoftmax = 1.96950012 * 2560; EvalClassificationError = 0.53085938 * 2560; time = 0.1272s; samplesPerSecond = 20129.1
MPI Rank 1: 01/11/2018 08:54:39:  Epoch[ 2 of 3]-Minibatch[  61-  70, 87.50%]: CrossEntropyWithSoftmax = 1.95934863 * 2560; EvalClassificationError = 0.52812500 * 2560; time = 0.1218s; samplesPerSecond = 21024.2
MPI Rank 1: 01/11/2018 08:54:39:  Epoch[ 2 of 3]-Minibatch[  71-  80, 100.00%]: CrossEntropyWithSoftmax = 1.94070839 * 2560; EvalClassificationError = 0.53125000 * 2560; time = 0.1203s; samplesPerSecond = 21273.1
MPI Rank 1: 01/11/2018 08:54:39: Finished Epoch[ 2 of 3]: [Training] CrossEntropyWithSoftmax = 2.02105263 * 20480; EvalClassificationError = 0.54609375 * 20480; totalSamplesSeen = 40960; learningRatePerSample = 0.001953125; epochTime=1.05046s
MPI Rank 1: 01/11/2018 08:54:40: Final Results: Minibatch[1-326]: CrossEntropyWithSoftmax = 1.92733488 * 83050; perplexity = 6.87117334; EvalClassificationError = 0.53122216 * 83050
MPI Rank 1: 01/11/2018 08:54:40: Finished Epoch[ 2 of 3]: [Validate] CrossEntropyWithSoftmax = 1.92733488 * 83050; EvalClassificationError = 0.53122216 * 83050
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:40: Starting Epoch 3: learning rate per sample = 0.000098  effective momentum = 0.656119  momentum as time constant = 2429.9 samples
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:40: Starting minibatch loop, DataParallelSGD training (myRank = 1, numNodes = 2, numGradientBits = 64), distributed reading is ENABLED.
MPI Rank 1: 01/11/2018 08:54:40:  Epoch[ 3 of 3]-Minibatch[   1-  10, 50.00%]: CrossEntropyWithSoftmax = 1.94336420 * 10240; EvalClassificationError = 0.53056641 * 10240; time = 0.3979s; samplesPerSecond = 25731.9
MPI Rank 1: 01/11/2018 08:54:41:  Epoch[ 3 of 3]-Minibatch[  11-  20, 100.00%]: CrossEntropyWithSoftmax = 1.96525554 * 10240; EvalClassificationError = 0.54873047 * 10240; time = 0.3543s; samplesPerSecond = 28904.0
MPI Rank 1: 01/11/2018 08:54:41: Finished Epoch[ 3 of 3]: [Training] CrossEntropyWithSoftmax = 1.95430987 * 20480; EvalClassificationError = 0.53964844 * 20480; totalSamplesSeen = 61440; learningRatePerSample = 9.7656251e-05; epochTime=0.75898s
MPI Rank 1: 01/11/2018 08:54:41: Final Results: Minibatch[1-83]: CrossEntropyWithSoftmax = 1.90639119 * 83050; perplexity = 6.72876211; EvalClassificationError = 0.52304636 * 83050
MPI Rank 1: 01/11/2018 08:54:41: Finished Epoch[ 3 of 3]: [Validate] CrossEntropyWithSoftmax = 1.90639119 * 83050; EvalClassificationError = 0.52304636 * 83050
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:42: Action "train" complete.
MPI Rank 1: 
MPI Rank 1: 01/11/2018 08:54:42: __COMPLETED__
