CPU info:
    CPU Model Name: Intel(R) Core(TM) i7-6820HQ CPU @ 2.70GHz
    Hardware threads: 8
    Total Memory: 33417320 kB
-------------------------------------------------------------------
+ [[ -z C:\CNTKTestData ]]
+ [[ ! -d C:\CNTKTestData ]]
+ '[' Windows_NT == Windows_NT ']'
++ cygpath -au 'C:\CNTKTestData'
+ TestDataDir=/cygdrive/c/CNTKTestData
+ ImageDir=/cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image
+ MnistDir=/cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST
+ DataDir=/cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Data
+ ConfigDir=/cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Config
+ OutputDir=/cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Output
+ cp /cygdrive/c/CNTKTestData/Image/MNIST/v0/Train-28x28_cntk_text.txt /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Data
+ '[' -d /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Output ']'
+ '[' -d /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Output/Models ']'
+ rm -rf /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Output/Models
+ DeleteModelsAfterTest=0
+ '[' -f /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Config/01_OneHidden.cntk ']'
+ cntkrun 01_OneHidden.cntk 'stderr=- command=trainNetwork trainNetwork=[SGD=[maxEpochs=1]]'
+ configFileName=01_OneHidden.cntk
+ additionalCNTKArgs='stderr=- command=trainNetwork trainNetwork=[SGD=[maxEpochs=1]]'
+ '[' Windows_NT == Windows_NT ']'
++ cygpath -aw /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Config
+ ConfigDir='C:\repos\cntk\Examples\Image\MNIST\Config'
++ cygpath -aw /tmp/cntk-test-20160923130058.478063/EvalClientTests_CPPEvalClientTest@release_cpu
+ RunDir='C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu'
++ cygpath -aw /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Data
+ DataDir='C:\repos\cntk\Examples\Image\MNIST\Data'
++ cygpath -aw /cygdrive/c/repos/cntk/Tests/EndToEndTests/../../Examples/Image/MNIST/Output
+ OutputDir='C:\repos\cntk\Examples\Image\MNIST\Output'
+ CNTKArgs='configFile=C:\repos\cntk\Examples\Image\MNIST\Config/01_OneHidden.cntk currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu DataDir=C:\repos\cntk\Examples\Image\MNIST\Data ConfigDir=C:\repos\cntk\Examples\Image\MNIST\Config OutputDir=C:\repos\cntk\Examples\Image\MNIST\Output DeviceId=-1 timestamping=true stderr=- command=trainNetwork trainNetwork=[SGD=[maxEpochs=1]]'
+ '[' '' '!=' '' ']'
+ modelsDir=/tmp/cntk-test-20160923130058.478063/EvalClientTests_CPPEvalClientTest@release_cpu/Models
+ [[ 1 == 1 ]]
+ '[' -d /tmp/cntk-test-20160923130058.478063/EvalClientTests_CPPEvalClientTest@release_cpu/Models ']'
+ mkdir -p /tmp/cntk-test-20160923130058.478063/EvalClientTests_CPPEvalClientTest@release_cpu/Models
+ [[ 0 == 0 ]]
+ run /cygdrive/c/repos/cntk/x64/release_CpuOnly/cntk.exe 'configFile=C:\repos\cntk\Examples\Image\MNIST\Config/01_OneHidden.cntk' 'currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data' 'RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu' 'DataDir=C:\repos\cntk\Examples\Image\MNIST\Data' 'ConfigDir=C:\repos\cntk\Examples\Image\MNIST\Config' 'OutputDir=C:\repos\cntk\Examples\Image\MNIST\Output' DeviceId=-1 timestamping=true stderr=- command=trainNetwork 'trainNetwork=[SGD=[maxEpochs=1]]'
+ cmd=/cygdrive/c/repos/cntk/x64/release_CpuOnly/cntk.exe
+ shift
+ '[' '' == 1 ']'
+ echo === Running /cygdrive/c/repos/cntk/x64/release_CpuOnly/cntk.exe 'configFile=C:\repos\cntk\Examples\Image\MNIST\Config/01_OneHidden.cntk' 'currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data' 'RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu' 'DataDir=C:\repos\cntk\Examples\Image\MNIST\Data' 'ConfigDir=C:\repos\cntk\Examples\Image\MNIST\Config' 'OutputDir=C:\repos\cntk\Examples\Image\MNIST\Output' DeviceId=-1 timestamping=true stderr=- command=trainNetwork 'trainNetwork=[SGD=[maxEpochs=1]]'
=== Running /cygdrive/c/repos/cntk/x64/release_CpuOnly/cntk.exe configFile=C:\repos\cntk\Examples\Image\MNIST\Config/01_OneHidden.cntk currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu DataDir=C:\repos\cntk\Examples\Image\MNIST\Data ConfigDir=C:\repos\cntk\Examples\Image\MNIST\Config OutputDir=C:\repos\cntk\Examples\Image\MNIST\Output DeviceId=-1 timestamping=true stderr=- command=trainNetwork trainNetwork=[SGD=[maxEpochs=1]]
+ /cygdrive/c/repos/cntk/x64/release_CpuOnly/cntk.exe 'configFile=C:\repos\cntk\Examples\Image\MNIST\Config/01_OneHidden.cntk' 'currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data' 'RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu' 'DataDir=C:\repos\cntk\Examples\Image\MNIST\Data' 'ConfigDir=C:\repos\cntk\Examples\Image\MNIST\Config' 'OutputDir=C:\repos\cntk\Examples\Image\MNIST\Output' DeviceId=-1 timestamping=true stderr=- command=trainNetwork 'trainNetwork=[SGD=[maxEpochs=1]]'
CNTK 1.7+ (zhouwang/add-e2etests 0c25b6, Sep 23 2016 12:56:13) on zhouwang4 at 2016/09/23 12:00:59

C:\repos\cntk\x64\release_CpuOnly\cntk.exe  configFile=C:\repos\cntk\Examples\Image\MNIST\Config/01_OneHidden.cntk  currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data  RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu  DataDir=C:\repos\cntk\Examples\Image\MNIST\Data  ConfigDir=C:\repos\cntk\Examples\Image\MNIST\Config  OutputDir=C:\repos\cntk\Examples\Image\MNIST\Output  DeviceId=-1  timestamping=true  stderr=-  command=trainNetwork  trainNetwork=[SGD=[maxEpochs=1]]
Changed current directory to C:\repos\cntk\Examples\Image\MNIST\Data
09/23/2016 12:00:59: Redirecting stderr to file -_trainNetwork.log
09/23/2016 12:00:59: -------------------------------------------------------------------
09/23/2016 12:00:59: Build info: 

09/23/2016 12:00:59: 		Built time: Sep 23 2016 12:56:13
09/23/2016 12:00:59: 		Last modified date: Fri Sep 23 11:28:25 2016
09/23/2016 12:00:59: 		Build type: Release
09/23/2016 12:00:59: 		Build target: CPU-only
09/23/2016 12:00:59: 		Math lib: mkl
09/23/2016 12:00:59: 		Build Branch: zhouwang/add-e2etests
09/23/2016 12:00:59: 		Build SHA1: 0c25b63da32c14869deb9232a6257daef6f9d285 (modified)
09/23/2016 12:00:59: 		Built by zhouwang on zhouwang4
09/23/2016 12:00:59: 		Build Path: C:\repos\cntk\Source\CNTK\
09/23/2016 12:00:59: -------------------------------------------------------------------

Configuration After Processing and Variable Resolution:

configparameters: 01_OneHidden.cntk:command=trainNetwork
configparameters: 01_OneHidden.cntk:configDir=C:\repos\cntk\Examples\Image\MNIST\Config
configparameters: 01_OneHidden.cntk:currentDirectory=C:\repos\cntk\Examples\Image\MNIST\Data
configparameters: 01_OneHidden.cntk:dataDir=C:\repos\cntk\Examples\Image\MNIST\Data
configparameters: 01_OneHidden.cntk:deviceId=-1
configparameters: 01_OneHidden.cntk:modelPath=C:\repos\cntk\Examples\Image\MNIST\Output/Models/01_OneHidden
configparameters: 01_OneHidden.cntk:outputDir=C:\repos\cntk\Examples\Image\MNIST\Output
configparameters: 01_OneHidden.cntk:precision=float
configparameters: 01_OneHidden.cntk:rootDir=..
configparameters: 01_OneHidden.cntk:RunDir=C:\cygwin64\tmp\cntk-test-20160923130058.478063\EvalClientTests_CPPEvalClientTest@release_cpu
configparameters: 01_OneHidden.cntk:stderr=-
configparameters: 01_OneHidden.cntk:testNetwork={
    action = "test"
minibatchSize = 1024    
    reader = {
        readerType = "CNTKTextFormatReader"
        file = "C:\repos\cntk\Examples\Image\MNIST\Data/Test-28x28_cntk_text.txt"
        input = {
            features = { dim = 784 ; format = "dense" }
            labels =   { dim = 10  ; format = "dense" }
        }
    }
}

configparameters: 01_OneHidden.cntk:timestamping=true
configparameters: 01_OneHidden.cntk:traceLevel=1
configparameters: 01_OneHidden.cntk:trainNetwork={
    action = "train"
    BrainScriptNetworkBuilder = {
imageShape = 28:28:1                        
labelDim = 10                               
        featScale = 1/256     
        model(x) = {
            s1 = x * featScale
            h1 = DenseLayer {200, activation=Sigmoid} (s1)
            z = LinearLayer {labelDim} (h1)
        }
        features = Input {imageShape}
        labels = Input (labelDim)
        out = model (features)
        ce   = CrossEntropyWithSoftmax (labels, out.z)
        errs = ClassificationError (labels, out.z)
        featureNodes    = (features)
        labelNodes      = (labels)
        criterionNodes  = (ce)
        evaluationNodes = (errs)
        outputNodes     = (out.z)
    }
    SGD = {
        epochSize = 60000
        minibatchSize = 64
        maxEpochs = 30
        learningRatesPerSample = 0.01*5:0.005
        momentumAsTimeConstant = 0
        numMBsToShowResult = 500
    }
    reader = {
        readerType = "CNTKTextFormatReader"
        file = "C:\repos\cntk\Examples\Image\MNIST\Data/Train-28x28_cntk_text.txt"
        input = {
            features = { dim = 784 ; format = "dense" }
            labels =   { dim = 10  ; format = "dense" }
        }
    }   
} [SGD=[maxEpochs=1]]

09/23/2016 12:00:59: Commands: trainNetwork
09/23/2016 12:00:59: precision = "float"

09/23/2016 12:00:59: ##############################################################################
09/23/2016 12:00:59: #                                                                            #
09/23/2016 12:00:59: # trainNetwork command (train action)                                        #
09/23/2016 12:00:59: #                                                                            #
09/23/2016 12:00:59: ##############################################################################

09/23/2016 12:00:59: 
Creating virgin network.
Node '<placeholder>' (LearnableParameter operation): Initializating Parameter[10 x 0] as glorotUniform later when dimensions are fully known.
Node '<placeholder>' (LearnableParameter operation): Initializating Parameter[200 x 0] as glorotUniform later when dimensions are fully known.

Post-processing network...

3 roots:
	ce = CrossEntropyWithSoftmax()
	errs = ClassificationError()
	out.z = Plus()

Validating network. 15 nodes to process in pass 1.

Validating --> labels = InputValue() :  -> [10 x *]
Validating --> out.z.W = LearnableParameter() :  -> [10 x 0]
Validating --> out.h1.arrayOfFunctions[0].W = LearnableParameter() :  -> [200 x 0]
Validating --> features = InputValue() :  -> [28 x 28 x 1 x *]
Validating --> _out.s1 = LearnableParameter() :  -> [1]
Validating --> out.s1 = ElementTimes (features, _out.s1) : [28 x 28 x 1 x *], [1] -> [28 x 28 x 1 x *]
Node 'out.h1.arrayOfFunctions[0].W' (LearnableParameter operation) operation: Tensor shape was inferred as [200 x 28 x 28 x 1].
Node 'out.h1.arrayOfFunctions[0].W' (LearnableParameter operation): Initializing Parameter[200 x 28 x 28 x 1] <- glorotUniform(seed=2, init dims=[200 x 784], range=0.078087*1.000000, onCPU=true.
)Validating --> out.h1._.PlusArgs[0] = Times (out.h1.arrayOfFunctions[0].W, out.s1) : [200 x 28 x 28 x 1], [28 x 28 x 1 x *] -> [200 x *]
Validating --> out.h1.arrayOfFunctions[0].b = LearnableParameter() :  -> [200]
Validating --> out.h1._ = Plus (out.h1._.PlusArgs[0], out.h1.arrayOfFunctions[0].b) : [200 x *], [200] -> [200 x *]
Validating --> out.h1 = Sigmoid (out.h1._) : [200 x *] -> [200 x *]
Node 'out.z.W' (LearnableParameter operation) operation: Tensor shape was inferred as [10 x 200].
Node 'out.z.W' (LearnableParameter operation): Initializing Parameter[10 x 200] <- glorotUniform(seed=1, init dims=[10 x 200], range=0.169031*1.000000, onCPU=true.
)Validating --> out.z.PlusArgs[0] = Times (out.z.W, out.h1) : [10 x 200], [200 x *] -> [10 x *]
Validating --> out.z.b = LearnableParameter() :  -> [10]
Validating --> out.z = Plus (out.z.PlusArgs[0], out.z.b) : [10 x *], [10] -> [10 x *]
Validating --> ce = CrossEntropyWithSoftmax (labels, out.z) : [10 x *], [10 x *] -> [1]
Validating --> errs = ClassificationError (labels, out.z) : [10 x *], [10 x *] -> [1]

Validating network. 8 nodes to process in pass 2.


Validating network, final pass.




Post-processing network complete.

09/23/2016 12:00:59: 
Model has 15 nodes. Using CPU.

09/23/2016 12:00:59: Training criterion:   ce = CrossEntropyWithSoftmax
09/23/2016 12:00:59: Evaluation criterion: errs = ClassificationError


Allocating matrices for forward and/or backward propagation.

Memory Sharing: Out of 25 matrices, 10 are shared as 5, and 15 are not shared.

	{ out.h1._ : [200 x *]
	  out.h1.arrayOfFunctions[0].W : [200 x 28 x 28 x 1] (gradient) }
	{ out.h1._ : [200 x *] (gradient)
	  out.z.PlusArgs[0] : [10 x *] }
	{ out.h1 : [200 x *] (gradient)
	  out.h1.arrayOfFunctions[0].b : [200] (gradient) }
	{ out.h1 : [200 x *]
	  out.h1._.PlusArgs[0] : [200 x *] (gradient) }
	{ out.z : [10 x *] (gradient)
	  out.z.W : [10 x 200] (gradient) }


09/23/2016 12:00:59: Training 159010 parameters in 4 out of 4 parameter tensors and 10 nodes with gradient:

09/23/2016 12:00:59: 	Node 'out.h1.arrayOfFunctions[0].W' (LearnableParameter operation) : [200 x 28 x 28 x 1]
09/23/2016 12:00:59: 	Node 'out.h1.arrayOfFunctions[0].b' (LearnableParameter operation) : [200]
09/23/2016 12:00:59: 	Node 'out.z.W' (LearnableParameter operation) : [10 x 200]
09/23/2016 12:00:59: 	Node 'out.z.b' (LearnableParameter operation) : [10]

09/23/2016 12:00:59: No PreCompute nodes found, or all already computed. Skipping pre-computation step.

09/23/2016 12:00:59: Starting Epoch 1: learning rate per sample = 0.010000  effective momentum = 0.000000  momentum as time constant = 0.0 samples

09/23/2016 12:00:59: Starting minibatch loop.
09/23/2016 12:01:01:  Epoch[ 1 of 1]-Minibatch[   1- 500, 53.33%]: ce = 0.51783240 * 32000; errs = 15.447% * 32000; time = 2.0583s; samplesPerSecond = 15547.1
09/23/2016 12:01:02: Finished Epoch[ 1 of 1]: [Training] ce = 0.40280387 * 60000; errs = 12.058% * 60000; totalSamplesSeen = 60000; learningRatePerSample = 0.0099999998; epochTime=3.01691s
09/23/2016 12:01:02: SGD: Saving checkpoint model 'C:\repos\cntk\Examples\Image\MNIST\Output/Models/01_OneHidden'

09/23/2016 12:01:02: Action "train" complete.

09/23/2016 12:01:02: __COMPLETED__
+ return 0
+ local ExitCode=0
+ [[ 0 == 1 ]]
+ return 0
+ '[' Windows_NT == Windows_NT ']'
+ /cygdrive/c/repos/cntk/x64/release_CpuOnly/CPPEvalClientTest.exe
Layer 'out.z' output:
0.919078
-6.916869
3.187339
5.794638
-2.549418
2.835959
-4.958842
-1.275766
1.812781
0.564827
Evaluation complete.
+ exit 0