CPU info:
    CPU Model Name: Intel(R) Xeon(R) CPU W3565 @ 3.20GHz
    Hardware threads: 8
    Total Memory: 12580436 kB
-------------------------------------------------------------------
=== Running /cygdrive/c/jenkins/workspace/CNTK-Test-Windows-W1/x64/release/cntk.exe configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU\Config/rnnlu.cntk currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU RunDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU\Config OutputDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu DeviceId=-1 timestamping=true NdlDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU ExpDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu OutDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu
CNTK 2.0.beta6.0+ (HEAD 5f1fab, Dec 15 2016 06:29:34) on cntk-muc01 at 2016/12/15 08:34:39

C:\jenkins\workspace\CNTK-Test-Windows-W1\x64\release\cntk.exe  configFile=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU\Config/rnnlu.cntk  currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU  RunDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu  DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU  ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU\Config  OutputDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu  DeviceId=-1  timestamping=true  NdlDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU  ExpDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu  OutDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu
Changed current directory to C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU
12/15/2016 08:34:39: -------------------------------------------------------------------
12/15/2016 08:34:39: Build info: 

12/15/2016 08:34:39: 		Built time: Dec 15 2016 06:29:34
12/15/2016 08:34:39: 		Last modified date: Wed Dec 14 12:53:20 2016
12/15/2016 08:34:39: 		Build type: Release
12/15/2016 08:34:39: 		Build target: GPU
12/15/2016 08:34:39: 		With ASGD: yes
12/15/2016 08:34:39: 		Math lib: mkl
12/15/2016 08:34:39: 		CUDA_PATH: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v8.0
12/15/2016 08:34:39: 		CUB_PATH: c:\src\cub-1.4.1
12/15/2016 08:34:39: 		CUDNN_PATH: C:\local\cudnn-8.0-windows10-x64-v5.1
12/15/2016 08:34:39: 		Build Branch: HEAD
12/15/2016 08:34:39: 		Build SHA1: 5f1fabfe95e68af0787193f8849159f824d914d5 (modified)
12/15/2016 08:34:39: 		Built by svcphil on liana-08-w
12/15/2016 08:34:39: 		Build Path: C:\jenkins\workspace\CNTK-Build-Windows\Source\CNTK\
12/15/2016 08:34:39: -------------------------------------------------------------------
12/15/2016 08:34:39: -------------------------------------------------------------------
12/15/2016 08:34:39: GPU info:

12/15/2016 08:34:39: 		Device[0]: cores = 2496; computeCapability = 5.2; type = "Quadro M4000"; memory = 8192 MB
12/15/2016 08:34:39: -------------------------------------------------------------------

Configuration After Processing and Variable Resolution:

configparameters: rnnlu.cntk:command=LSTM:LSTMTest
configparameters: rnnlu.cntk:ConfigDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU\Config
configparameters: rnnlu.cntk:currentDirectory=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU
configparameters: rnnlu.cntk:DataDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU
configparameters: rnnlu.cntk:deviceId=-1
configparameters: rnnlu.cntk:ExpDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu
configparameters: rnnlu.cntk:LSTM=[
    action=train
	makeMode=true
    modelPath=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn
    SimpleNetworkBuilder=[
        rnnType=LSTM
        layerSizes=2832:50:300:300:300:127
        lookupTableOrder=3
        recurrentLayer=2:3:4
        defaultHiddenActivity=0.1
        initValueScale=6.0
        trainingCriterion=crossentropywithsoftmax
        evalCriterion=crossentropywithsoftmax
    ]
    SGD=[
maxEpochs=100   
epochSize=71524     
        minibatchSize=10000
        learningRatesPerSample=0.1
        momentumAsTimeConstant=1000
        gradientClippingWithTruncation=true
        clippingThresholdPerSample=15.0
        numMBsToShowResult=50
        loadBestModel=true
        AutoAdjust=[
            autoAdjustLR=adjustafterepoch
            reduceLearnRateIfImproveLessThan=0
            increaseLearnRateIfImproveMoreThan=1000000000
            learnRateDecreaseFactor=0.5
            learnRateIncreaseFactor=1.382
        ]
    ]
    reader=[
        readerType=LUSequenceReader
        wordContext=0:1:2
        randomize=None
nbruttsineachrecurrentiter=10  
        equalLength = false
        wfile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sequenceSentence.bin
        wsize=256
        wrecords=1000
        windowSize=10000
        unk="<unk>"
          wordmap=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/inputmap.txt
          file=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/atis.train.apos.pred.pos.head.IOB.simple
          features=[
            dim=0
            sectionType=data
          ]
          sequence=[
            dim=1
            wrecords=2
            sectionType=data
          ]
          labelIn=[
            dim=1
            usewordmap=true
            labelDim=10000
            labelMappingFile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sentenceLabels.txt
            labelType=Category
            beginSequence="BOS"
            endSequence="EOS"
            usewordmap=true
            token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/input.txt
            elementSize=4
            sectionType=labels
            mapping=[
              wrecords=11
              elementSize=10
              sectionType=labelMapping
            ]
            category=[
              dim=11
              sectionType=categoryLabels
            ]
          ]
          labels=[
            dim=1
            labelType=Category
            token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/output.txt
            labelMappingFile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sentenceLabels.out.txt
            sectionType=labels
            mapping=[
              sectionType=labelMapping
            ]
            category=[
              sectionType=categoryLabels
            ]
          ]
    ]
    cvReader=[
      readerType=LUSequenceReader
      randomize=None
      wordContext=0:1:2
      nbruttsineachrecurrentiter=200
      equalLength = false
      wfile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sequenceSentence.valid.bin
      wsize=256
      wrecords=1000
      windowSize=10000
      unk="<unk>"
      wordmap=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/inputmap.txt
      file=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/atis.dev.IOB.simple
      features=[
        dim=0
        sectionType=data
      ]
      sequence=[
        dim=1
        wrecords=2
        sectionType=data
      ]
      labelIn=[
        dim=1
        labelDim=10000
        labelMappingFile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sentenceLabels.in.txt
        labelType=Category
        beginSequence="BOS"
        endSequence="EOS"
        usewordmap=true
        token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/input.txt
        elementSize=4
        sectionType=labels
        mapping=[
          wrecords=11
          elementSize=10
          sectionType=labelMapping
        ]
        category=[
          dim=11
          sectionType=categoryLabels
        ]
      ]
      labels=[
        dim=1
        labelType=Category
        token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/output.txt
        labelDim=10000
        labelMappingFile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sentenceLabels.out.txt
        elementSize=4
        sectionType=labels
        mapping=[
          wrecords=3
          elementSize=10
          sectionType=labelMapping
        ]
        category=[
          dim=3
          sectionType=categoryLabels
        ]
      ]
    ]
]

configparameters: rnnlu.cntk:LSTMTest=[
    action=write
    epochSize=4430000
    defaultHiddenActivity=0.1
    modelPath=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn
    outputNodeNames=outputs:labels
    reader=[
      readerType=LUSequenceReader
      randomize=None
      wordContext=0:1:2
      unk="<unk>"
      wordmap=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/inputmap.txt
      file=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/atis.test.apos.pred.pos.head.IOB.simple
      wfile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sequenceSentence.bin
      wsize=256
      wrecords=1000
      windowSize=10000
      features=[
        dim=0 
        sectionType=data
      ]
      sequence=[
        dim=1
        wrecords=2
        sectionType=data
      ]
      labelIn=[
        dim=1
        labelDim=10000
        labelMappingFile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sentenceLabels.txt
        labelType=Category
        beginSequence="BOS"
        endSequence="EOS"
        usewordmap=true
        token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/input.txt
        elementSize=4
        sectionType=labels
        mapping=[
          wrecords=11
          elementSize=10
          sectionType=labelMapping
        ]
        category=[
          dim=11
          sectionType=categoryLabels
        ]
      ]
      labels=[
        dim=1
        labelType=Category
        beginSequence="BOS"
        endSequence="EOS"
        token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/output.txt
        labelDim=127
        labelMappingFile=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/sentenceLabels.out.txt
        elementSize=4
        sectionType=labels
        mapping=[
          wrecords=3
          elementSize=10
          sectionType=labelMapping
        ]
        category=[
          dim=3
          sectionType=categoryLabels
        ]
      ]
    ]
    writer=[
        writerType=LUSequenceWriter
        outputs=[
            file=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/output.rec.txt
            token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/output.txt
        ]
        labels=[
            file=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/output.lbl.txt
            token=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/output.txt
        ]
    ]
]

configparameters: rnnlu.cntk:NdlDir=C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Examples\Text\Miscellaneous\SLU
configparameters: rnnlu.cntk:OutDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu
configparameters: rnnlu.cntk:OutputDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu
configparameters: rnnlu.cntk:precision=float
configparameters: rnnlu.cntk:RunDir=C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu
configparameters: rnnlu.cntk:timestamping=true
configparameters: rnnlu.cntk:traceLevel=1
12/15/2016 08:34:39: Commands: LSTM LSTMTest
12/15/2016 08:34:39: precision = "float"

12/15/2016 08:34:39: ##############################################################################
12/15/2016 08:34:39: #                                                                            #
12/15/2016 08:34:39: # LSTM command (train action)                                                #
12/15/2016 08:34:39: #                                                                            #
12/15/2016 08:34:39: ##############################################################################

12/15/2016 08:34:39: 
Creating virgin network.
SimpleNetworkBuilder Using CPU
BatchLUSequenceReader: Input file is C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/atis.train.apos.pred.pos.head.IOB.simple
BatchLUSequenceReader: Input file is C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/atis.dev.IOB.simple
12/15/2016 08:34:40: 
Model has 168 nodes. Using CPU.

12/15/2016 08:34:40: Training criterion:   CrossEntropyWithSoftmax = CrossEntropyWithSoftmax


Allocating matrices for forward and/or backward propagation.

Memory Sharing: Out of 332 matrices, 201 are shared as 85, and 131 are not shared.

	{ AutoName21 : [300 x 1 x *] (gradient)
	  AutoName43 : [300 x 1 x *] }
	{ AutoName16 : [300 x 1 x *] (gradient)
	  AutoName44 : [300 x 1 x *] }
	{ AutoName3 : [300 x 1 x *]
	  WXC0 : [300 x 150] (gradient) }
	{ AutoName28 : [300 x 1 x *] (gradient)
	  AutoName40 : [300 x 1 x *] }
	{ AutoName39 : [300 x 1 x *]
	  WHI0 : [300 x 300] (gradient) }
	{ AutoName31 : [300 x 1 x *] (gradient)
	  AutoName42 : [300 x 1 x *] }
	{ AutoName41 : [300 x 1 x *]
	  WXC2 : [300 x 300] (gradient) }
	{ AutoName17 : [300 x *] (gradient)
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	  bi0 : [300 x 1] (gradient) }
	{ AutoName109 : [300 x 1 x *] (gradient)
	  AutoName67 : [300 x 1 x *] (gradient) }
	{ AutoName51 : [300 x 1 x *] (gradient)
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	  WHF0 : [300 x 300] (gradient) }
	{ AutoName43 : [300 x 1 x *] (gradient)
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	{ AutoName58 : [300 x 1 x *] (gradient)
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	{ AutoName35 : [300 x 1 x *] (gradient)
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	  AutoName84 : [300 x 1 x *] (gradient) }
	{ AutoName101 : [300 x 1 x *] (gradient)
	  AutoName55 : [300 x 1 x *] (gradient)
	  bi2 : [300 x 1] (gradient) }
	{ AutoName29 : [300 x 1 x *] (gradient)
	  AutoName71 : [300 x 1 x *] (gradient)
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	{ AutoName45 : [300 x 1 x *] (gradient)
	  AutoName5 : [300 x 1 x *] (gradient)
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	{ AutoName102 : [300 x 1 x *] (gradient)
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	{ AutoName1 : [300 x 1 x *] (gradient)
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	  AutoName77 : [300 x 1 x *] (gradient) }
	{ AutoName100 : [300 x 1 x *] (gradient)
	  AutoName73 : [300 x 1 x *] (gradient) }
	{ AutoName93 : [300 x 1 x *] (gradient)
	  bi3 : [300 x 1] (gradient) }
	{ AutoName89 : [300 x 1 x *] (gradient)
	  WHF2 : [300 x 300] (gradient) }
	{ AutoName72 : [300 x 1 x *] (gradient)
	  AutoName87 : [300 x 1 x *] (gradient)
	  WCO0 : [300 x 1] (gradient) }
	{ AutoName53 : [300 x 1 x *] (gradient)
	  AutoName82 : [300 x 1 x *] (gradient) }
	{ AutoName104 : [300 x 1 x *] (gradient)
	  AutoName47 : [300 x 1 x *] (gradient)
	  AutoName7 : [300 x 1 x *] (gradient) }
	{ AutoName80 : [300 x 1 x *] (gradient)
	  WHO2 : [300 x 300] (gradient) }
	{ AutoName57 : [300 x 1 x *] (gradient)
	  AutoName98 : [300 x 1 x *] (gradient) }
	{ AutoName81 : [300 x 1 x *] (gradient)
	  WHC0 : [300 x 300] (gradient) }
	{ AutoName76 : [300 x 1 x *] (gradient)
	  AutoName79 : [300 x 1 x *] (gradient) }
	{ AutoName110 : [300 x 1 x *] (gradient)
	  WCO2 : [300 x 1] (gradient) }
	{ AutoName86 : [300 x 1 x *]
	  AutoName99 : [300 x 1 x *] (gradient)
	  bo3 : [300 x 1] (gradient) }
	{ AutoName86 : [300 x 1 x *] (gradient)
	  AutoName93 : [300 x 1 x *]
	  bf3 : [300 x 1] (gradient) }
	{ AutoName109 : [300 x 1 x *]
	  WXO3 : [300 x 300] (gradient) }
	{ AutoName20 : [300 x 1 x *] (gradient)
	  AutoName40 : [300 x 1 x *] (gradient)
	  AutoName90 : [300 x 1 x *] }
	{ AutoName38 : [300 x 1 x *] (gradient)
	  AutoName41 : [300 x 1 x *] (gradient)
	  AutoName91 : [300 x 1 x *] }
	{ AutoName3 : [300 x 1 x *] (gradient)
	  AutoName53 : [300 x 1 x *]
	  LookupTable : [150 x *] (gradient) }
	{ AutoName112 : [300 x 1 x *] (gradient)
	  AutoName115 : [127 x 1 x *] }
	{ AutoName64 : [300 x 1 x *] (gradient)
	  AutoName8 : [300 x 1 x *] (gradient)
	  AutoName88 : [300 x 1 x *] }
	{ AutoName104 : [300 x 1 x *]
	  AutoName34 : [300 x 1 x *] (gradient)
	  AutoName49 : [300 x 1 x *] (gradient) }
	{ AutoName113 : [300 x 1 x *] (gradient)
	  AutoName115 : [127 x 1 x *] (gradient) }
	{ AutoName107 : [300 x 1 x *]
	  AutoName68 : [300 x 1 x *] (gradient) }
	{ AutoName33 : [300 x 1 x *] (gradient)
	  AutoName52 : [300 x 1 x *] (gradient)
	  AutoName98 : [300 x 1 x *] }
	{ AutoName108 : [300 x 1 x *] (gradient)
	  AutoName75 : [300 x 1 x *] (gradient)
	  AutoName99 : [300 x 1 x *] }
	{ AutoName102 : [300 x 1 x *]
	  AutoName25 : [300 x 1 x *] (gradient)
	  AutoName50 : [300 x 1 x *] (gradient) }
	{ AutoName101 : [300 x 1 x *]
	  AutoName56 : [300 x 1 x *] (gradient) }
	{ AutoName108 : [300 x 1 x *]
	  AutoName74 : [300 x 1 x *] (gradient) }
	{ AutoName100 : [300 x 1 x *]
	  WXF3 : [300 x 300] (gradient) }
	{ AutoName42 : [300 x 1 x *] (gradient)
	  AutoName97 : [300 x 1 x *]
	  WHO0 : [300 x 300] (gradient) }
	{ AutoName103 : [300 x 1 x *]
	  WCF0 : [300 x 1] (gradient) }
	{ AutoName65 : [300 x 1 x *] (gradient)
	  AutoName85 : [300 x 1 x *] }
	{ AutoName87 : [300 x 1 x *]
	  WXI3 : [300 x 300] (gradient) }
	{ AutoName19 : [300 x 1 x *] (gradient)
	  AutoName60 : [300 x 1 x *] (gradient)
	  AutoName89 : [300 x 1 x *] }
	{ AutoName15 : [300 x 1 x *] (gradient)
	  AutoName44 : [300 x 1 x *] (gradient)
	  AutoName84 : [300 x 1 x *] }
	{ AutoName54 : [300 x 1 x *] (gradient)
	  AutoName82 : [300 x 1 x *] }
	{ AutoName83 : [300 x 1 x *]
	  WCI2 : [300 x 1] (gradient) }
	{ AutoName66 : [300 x 1 x *] (gradient)
	  AutoName78 : [300 x 1 x *]
	  AutoName9 : [300 x 1 x *] (gradient) }
	{ AutoName79 : [300 x 1 x *]
	  WXC3 : [300 x 300] (gradient) }
	{ AutoName69 : [300 x 1 x *] (gradient)
	  AutoName80 : [300 x 1 x *] }
	{ AutoName45 : [300 x 1 x *]
	  WCI0 : [300 x 1] (gradient) }
	{ AutoName77 : [300 x 1 x *]
	  WHI2 : [300 x 300] (gradient) }
	{ AutoName13 : [300 x 1 x *] (gradient)
	  AutoName59 : [300 x 1 x *] (gradient)
	  AutoName81 : [300 x 1 x *] }
	{ AutoName10 : [300 x *]
	  AutoName23 : [300 x *] (gradient)
	  bo0 : [300 x 1] (gradient) }
	{ AutoName33 : [300 x 1 x *]
	  WXO0 : [300 x 150] (gradient) }
	{ AutoName36 : [300 x 1 x *] (gradient)
	  AutoName70 : [300 x 1 x *] }
	{ AutoName71 : [300 x 1 x *]
	  WXO2 : [300 x 300] (gradient) }
	{ AutoName48 : [300 x 1 x *]
	  AutoName61 : [300 x 1 x *] (gradient)
	  bo2 : [300 x 1] (gradient) }
	{ AutoName14 : [300 x 1 x *] (gradient)
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	{ AutoName4 : [300 x 1 x *] (gradient)
	  AutoName59 : [300 x 1 x *] }
	{ AutoName37 : [300 x 1 x *] (gradient)
	  AutoName61 : [300 x 1 x *]
	  AutoName70 : [300 x 1 x *] (gradient) }
	{ AutoName49 : [300 x 1 x *]
	  WXI2 : [300 x 300] (gradient) }
	{ AutoName12 : [300 x 1 x *] (gradient)
	  AutoName64 : [300 x 1 x *] }
	{ AutoName23 : [300 x *]
	  AutoName32 : [300 x *] (gradient) }
	{ AutoName27 : [300 x 1 x *] (gradient)
	  AutoName47 : [300 x 1 x *] }
	{ AutoName26 : [300 x 1 x *] (gradient)
	  AutoName50 : [300 x 1 x *] }
	{ AutoName22 : [300 x 1 x *] (gradient)
	  AutoName51 : [300 x 1 x *] }
	{ AutoName48 : [300 x 1 x *] (gradient)
	  AutoName55 : [300 x 1 x *]
	  bf2 : [300 x 1] (gradient) }
	{ AutoName32 : [300 x *]
	  E0 : [50 x 944] (gradient) }
	{ AutoName24 : [300 x 1 x *]
	  WXF0 : [300 x 150] (gradient) }
	{ AutoName62 : [300 x 1 x *]
	  WXF2 : [300 x 300] (gradient) }
	{ AutoName11 : [300 x 1 x *]
	  WXI0 : [300 x 150] (gradient) }
	{ AutoName30 : [300 x 1 x *] (gradient)
	  AutoName69 : [300 x 1 x *] }
	{ AutoName18 : [300 x 1 x *] (gradient)
	  AutoName63 : [300 x 1 x *] }
	{ AutoName11 : [300 x 1 x *] (gradient)
	  AutoName66 : [300 x 1 x *] }
	{ AutoName2 : [300 x 1 x *] (gradient)
	  AutoName52 : [300 x 1 x *] }
	{ AutoName46 : [300 x 1 x *]
	  AutoName6 : [300 x 1 x *] (gradient) }
	{ AutoName10 : [300 x *] (gradient)
	  AutoName17 : [300 x *]
	  bf0 : [300 x 1] (gradient) }


12/15/2016 08:34:40: Training 2071600 parameters in 47 out of 47 parameter tensors and 164 nodes with gradient:

12/15/2016 08:34:40: 	Node 'E0' (LearnableParameter operation) : [50 x 944]
12/15/2016 08:34:40: 	Node 'W4' (LearnableParameter operation) : [127 x 300]
12/15/2016 08:34:40: 	Node 'WCF0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCF2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCF3' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCI0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCI2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCI3' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCO0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCO2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WCO3' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'WHC0' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHC2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHC3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHF0' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHF2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHF3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHI0' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHI2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHI3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHO0' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHO2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WHO3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXC0' (LearnableParameter operation) : [300 x 150]
12/15/2016 08:34:40: 	Node 'WXC2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXC3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXF0' (LearnableParameter operation) : [300 x 150]
12/15/2016 08:34:40: 	Node 'WXF2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXF3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXI0' (LearnableParameter operation) : [300 x 150]
12/15/2016 08:34:40: 	Node 'WXI2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXI3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXO0' (LearnableParameter operation) : [300 x 150]
12/15/2016 08:34:40: 	Node 'WXO2' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'WXO3' (LearnableParameter operation) : [300 x 300]
12/15/2016 08:34:40: 	Node 'bc0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bc2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bc3' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bf0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bf2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bf3' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bi0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bi2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bi3' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bo0' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bo2' (LearnableParameter operation) : [300 x 1]
12/15/2016 08:34:40: 	Node 'bo3' (LearnableParameter operation) : [300 x 1]

12/15/2016 08:34:40: No PreCompute nodes found, or all already computed. Skipping pre-computation step.

12/15/2016 08:34:40: Starting Epoch 1: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:40: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:40: Finished Epoch[ 1 of 100]: [Training] CrossEntropyWithSoftmax = 4.84228101 * 81; totalSamplesSeen = 81; learningRatePerSample = 0.1; epochTime=0.162684s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:40: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 4.80622129 * 81; perplexity = 122.26872555
12/15/2016 08:34:40: Finished Epoch[ 1 of 100]: [Validate] CrossEntropyWithSoftmax = 4.80622129 * 81
12/15/2016 08:34:40: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.1'

12/15/2016 08:34:40: Starting Epoch 2: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:40: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:40: Finished Epoch[ 2 of 100]: [Training] CrossEntropyWithSoftmax = 4.80622129 * 81; totalSamplesSeen = 162; learningRatePerSample = 0.1; epochTime=0.112604s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:40: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 4.73773306 * 81; perplexity = 114.17508047
12/15/2016 08:34:40: Finished Epoch[ 2 of 100]: [Validate] CrossEntropyWithSoftmax = 4.73773306 * 81
12/15/2016 08:34:41: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.2'

12/15/2016 08:34:41: Starting Epoch 3: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:41: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:41: Finished Epoch[ 3 of 100]: [Training] CrossEntropyWithSoftmax = 4.73773306 * 81; totalSamplesSeen = 243; learningRatePerSample = 0.1; epochTime=0.106558s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:41: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 4.63757400 * 81; perplexity = 103.29345301
12/15/2016 08:34:41: Finished Epoch[ 3 of 100]: [Validate] CrossEntropyWithSoftmax = 4.63757400 * 81
12/15/2016 08:34:41: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.3'

12/15/2016 08:34:41: Starting Epoch 4: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:41: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:42: Finished Epoch[ 4 of 100]: [Training] CrossEntropyWithSoftmax = 4.63757400 * 81; totalSamplesSeen = 324; learningRatePerSample = 0.1; epochTime=0.11701s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:42: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 4.50063145 * 81; perplexity = 90.07399058
12/15/2016 08:34:42: Finished Epoch[ 4 of 100]: [Validate] CrossEntropyWithSoftmax = 4.50063145 * 81
12/15/2016 08:34:42: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.4'

12/15/2016 08:34:42: Starting Epoch 5: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:42: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:42: Finished Epoch[ 5 of 100]: [Training] CrossEntropyWithSoftmax = 4.50063145 * 81; totalSamplesSeen = 405; learningRatePerSample = 0.1; epochTime=0.102725s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:42: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 4.31237944 * 81; perplexity = 74.61782627
12/15/2016 08:34:42: Finished Epoch[ 5 of 100]: [Validate] CrossEntropyWithSoftmax = 4.31237944 * 81
12/15/2016 08:34:42: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.5'

12/15/2016 08:34:42: Starting Epoch 6: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:42: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:42: Finished Epoch[ 6 of 100]: [Training] CrossEntropyWithSoftmax = 4.31237944 * 81; totalSamplesSeen = 486; learningRatePerSample = 0.1; epochTime=0.102014s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:42: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 4.04505336 * 81; perplexity = 57.11423381
12/15/2016 08:34:42: Finished Epoch[ 6 of 100]: [Validate] CrossEntropyWithSoftmax = 4.04505336 * 81
12/15/2016 08:34:43: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.6'

12/15/2016 08:34:43: Starting Epoch 7: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:43: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:43: Finished Epoch[ 7 of 100]: [Training] CrossEntropyWithSoftmax = 4.04505336 * 81; totalSamplesSeen = 567; learningRatePerSample = 0.1; epochTime=0.105734s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:43: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 3.65496525 * 81; perplexity = 38.66617735
12/15/2016 08:34:43: Finished Epoch[ 7 of 100]: [Validate] CrossEntropyWithSoftmax = 3.65496525 * 81
12/15/2016 08:34:43: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.7'

12/15/2016 08:34:43: Starting Epoch 8: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:43: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:43: Finished Epoch[ 8 of 100]: [Training] CrossEntropyWithSoftmax = 3.65496525 * 81; totalSamplesSeen = 648; learningRatePerSample = 0.1; epochTime=0.103891s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:43: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 3.09647285 * 81; perplexity = 22.11979361
12/15/2016 08:34:43: Finished Epoch[ 8 of 100]: [Validate] CrossEntropyWithSoftmax = 3.09647285 * 81
12/15/2016 08:34:43: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.8'

12/15/2016 08:34:43: Starting Epoch 9: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:43: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:44: Finished Epoch[ 9 of 100]: [Training] CrossEntropyWithSoftmax = 3.09647285 * 81; totalSamplesSeen = 729; learningRatePerSample = 0.1; epochTime=0.106536s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:44: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.47900353 * 81; perplexity = 11.92937123
12/15/2016 08:34:44: Finished Epoch[ 9 of 100]: [Validate] CrossEntropyWithSoftmax = 2.47900353 * 81
12/15/2016 08:34:44: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.9'

12/15/2016 08:34:44: Starting Epoch 10: learning rate per sample = 0.100000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:44: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:44: Finished Epoch[10 of 100]: [Training] CrossEntropyWithSoftmax = 2.47900353 * 81; totalSamplesSeen = 810; learningRatePerSample = 0.1; epochTime=0.105275s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:44: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.48163049 * 81; perplexity = 11.96075041
12/15/2016 08:34:44: Finished Epoch[10 of 100]: [Validate] CrossEntropyWithSoftmax = 2.48163049 * 81
12/15/2016 08:34:44: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.9.
12/15/2016 08:34:44: learnRatePerSample reduced to 0.050000001
12/15/2016 08:34:44: SGD: revoke back to and update checkpoint file for epoch 9

12/15/2016 08:34:44: Starting Epoch 10: learning rate per sample = 0.050000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:44: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:45: Finished Epoch[10 of 100]: [Training] CrossEntropyWithSoftmax = 2.47900353 * 81; totalSamplesSeen = 810; learningRatePerSample = 0.050000001; epochTime=0.112029s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:45: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.44586276 * 81; perplexity = 11.54050197
12/15/2016 08:34:45: Finished Epoch[10 of 100]: [Validate] CrossEntropyWithSoftmax = 2.44586276 * 81
12/15/2016 08:34:45: SGD: Saving checkpoint model 'C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10'

12/15/2016 08:34:45: Starting Epoch 11: learning rate per sample = 0.050000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:45: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:45: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.050000001; epochTime=0.106523s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:45: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.88468236 * 81; perplexity = 17.89788163
12/15/2016 08:34:45: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.88468236 * 81
12/15/2016 08:34:45: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:45: learnRatePerSample reduced to 0.025
12/15/2016 08:34:45: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:45: Starting Epoch 11: learning rate per sample = 0.025000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:45: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:45: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.025; epochTime=0.105858s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:45: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.94010643 * 81; perplexity = 18.91785958
12/15/2016 08:34:45: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.94010643 * 81
12/15/2016 08:34:45: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:46: learnRatePerSample reduced to 0.0125
12/15/2016 08:34:46: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:46: Starting Epoch 11: learning rate per sample = 0.012500  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:46: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:46: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.0125; epochTime=0.102622s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:46: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.96854956 * 81; perplexity = 19.46366830
12/15/2016 08:34:46: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.96854956 * 81
12/15/2016 08:34:46: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:46: learnRatePerSample reduced to 0.0062500001
12/15/2016 08:34:46: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:46: Starting Epoch 11: learning rate per sample = 0.006250  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:46: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:46: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.0062500001; epochTime=0.103713s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:46: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.98295292 * 81; perplexity = 19.74603908
12/15/2016 08:34:46: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.98295292 * 81
12/15/2016 08:34:46: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:47: learnRatePerSample reduced to 0.003125
12/15/2016 08:34:47: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:47: Starting Epoch 11: learning rate per sample = 0.003125  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:47: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:47: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.003125; epochTime=0.10705s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:47: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99019990 * 81; perplexity = 19.88965807
12/15/2016 08:34:47: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99019990 * 81
12/15/2016 08:34:47: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:47: learnRatePerSample reduced to 0.0015625
12/15/2016 08:34:47: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:47: Starting Epoch 11: learning rate per sample = 0.001563  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:47: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:48: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.0015625; epochTime=0.105542s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:48: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99383470 * 81; perplexity = 19.96208443
12/15/2016 08:34:48: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99383470 * 81
12/15/2016 08:34:48: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:48: learnRatePerSample reduced to 0.00078125001
12/15/2016 08:34:48: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:48: Starting Epoch 11: learning rate per sample = 0.000781  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:48: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:48: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.00078125001; epochTime=0.110689s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:48: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99565482 * 81; perplexity = 19.99845108
12/15/2016 08:34:48: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99565482 * 81
12/15/2016 08:34:48: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:48: learnRatePerSample reduced to 0.00039062501
12/15/2016 08:34:48: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:48: Starting Epoch 11: learning rate per sample = 0.000391  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:48: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:49: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.00039062501; epochTime=0.104555s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:49: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99656583 * 81; perplexity = 20.01667809
12/15/2016 08:34:49: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99656583 * 81
12/15/2016 08:34:49: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:49: learnRatePerSample reduced to 0.0001953125
12/15/2016 08:34:49: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:49: Starting Epoch 11: learning rate per sample = 0.000195  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:49: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:49: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 0.0001953125; epochTime=0.107601s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:49: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99702115 * 81; perplexity = 20.02579405
12/15/2016 08:34:49: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99702115 * 81
12/15/2016 08:34:49: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:49: learnRatePerSample reduced to 9.7656251e-005
12/15/2016 08:34:49: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:49: Starting Epoch 11: learning rate per sample = 0.000098  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:49: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:50: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 9.7656251e-005; epochTime=0.102611s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:50: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99724890 * 81; perplexity = 20.03035548
12/15/2016 08:34:50: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99724890 * 81
12/15/2016 08:34:50: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:50: learnRatePerSample reduced to 4.8828126e-005
12/15/2016 08:34:50: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:50: Starting Epoch 11: learning rate per sample = 0.000049  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:50: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:50: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 4.8828126e-005; epochTime=0.102795s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:50: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99736306 * 81; perplexity = 20.03264224
12/15/2016 08:34:50: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99736306 * 81
12/15/2016 08:34:50: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:50: learnRatePerSample reduced to 2.4414063e-005
12/15/2016 08:34:50: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:50: Starting Epoch 11: learning rate per sample = 0.000024  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:50: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:51: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 2.4414063e-005; epochTime=0.106282s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:51: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99741995 * 81; perplexity = 20.03378195
12/15/2016 08:34:51: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99741995 * 81
12/15/2016 08:34:51: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:51: learnRatePerSample reduced to 1.2207031e-005
12/15/2016 08:34:51: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:51: Starting Epoch 11: learning rate per sample = 0.000012  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:51: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:51: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 1.2207031e-005; epochTime=0.110491s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:51: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99744858 * 81; perplexity = 20.03435560
12/15/2016 08:34:51: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99744858 * 81
12/15/2016 08:34:51: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:51: learnRatePerSample reduced to 6.1035157e-006
12/15/2016 08:34:51: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:51: Starting Epoch 11: learning rate per sample = 0.000006  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:51: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:52: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 6.1035157e-006; epochTime=0.106499s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:52: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99746290 * 81; perplexity = 20.03464243
12/15/2016 08:34:52: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99746290 * 81
12/15/2016 08:34:52: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:52: learnRatePerSample reduced to 3.0517579e-006
12/15/2016 08:34:52: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:52: Starting Epoch 11: learning rate per sample = 0.000003  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:52: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:52: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 3.0517579e-006; epochTime=0.109128s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:52: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747006 * 81; perplexity = 20.03478585
12/15/2016 08:34:52: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747006 * 81
12/15/2016 08:34:52: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:52: learnRatePerSample reduced to 1.5258789e-006
12/15/2016 08:34:52: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:53: Starting Epoch 11: learning rate per sample = 0.000002  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:53: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:53: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 1.5258789e-006; epochTime=0.128828s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:53: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747345 * 81; perplexity = 20.03485378
12/15/2016 08:34:53: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747345 * 81
12/15/2016 08:34:53: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:53: learnRatePerSample reduced to 7.6293946e-007
12/15/2016 08:34:53: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:53: Starting Epoch 11: learning rate per sample = 0.000001  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:53: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:53: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 7.6293946e-007; epochTime=0.106968s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:53: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747552 * 81; perplexity = 20.03489530
12/15/2016 08:34:53: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747552 * 81
12/15/2016 08:34:53: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:54: learnRatePerSample reduced to 3.8146973e-007
12/15/2016 08:34:54: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:54: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:54: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:54: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 3.8146973e-007; epochTime=0.111302s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:54: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747608 * 81; perplexity = 20.03490662
12/15/2016 08:34:54: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747608 * 81
12/15/2016 08:34:54: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:54: learnRatePerSample reduced to 1.9073487e-007
12/15/2016 08:34:54: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:54: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:54: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:54: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 1.9073487e-007; epochTime=0.143378s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:54: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747646 * 81; perplexity = 20.03491417
12/15/2016 08:34:54: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747646 * 81
12/15/2016 08:34:54: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:55: learnRatePerSample reduced to 9.5367433e-008
12/15/2016 08:34:55: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:55: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:55: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:55: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 9.5367433e-008; epochTime=0.105619s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:55: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747684 * 81; perplexity = 20.03492172
12/15/2016 08:34:55: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747684 * 81
12/15/2016 08:34:55: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:55: learnRatePerSample reduced to 4.7683717e-008
12/15/2016 08:34:55: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:55: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:55: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:55: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 4.7683717e-008; epochTime=0.104103s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:55: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747684 * 81; perplexity = 20.03492172
12/15/2016 08:34:55: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747684 * 81
12/15/2016 08:34:55: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:56: learnRatePerSample reduced to 2.3841858e-008
12/15/2016 08:34:56: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:56: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:56: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:56: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 2.3841858e-008; epochTime=0.105915s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:56: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747684 * 81; perplexity = 20.03492172
12/15/2016 08:34:56: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747684 * 81
12/15/2016 08:34:56: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:56: learnRatePerSample reduced to 1.1920929e-008
12/15/2016 08:34:56: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:56: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:56: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:56: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 1.1920929e-008; epochTime=0.110015s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:56: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747684 * 81; perplexity = 20.03492172
12/15/2016 08:34:56: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747684 * 81
12/15/2016 08:34:56: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:57: learnRatePerSample reduced to 5.9604646e-009
12/15/2016 08:34:57: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:57: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:57: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:57: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 5.9604646e-009; epochTime=0.10407s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:57: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747721 * 81; perplexity = 20.03492927
12/15/2016 08:34:57: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747721 * 81
12/15/2016 08:34:57: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:57: learnRatePerSample reduced to 2.9802323e-009
12/15/2016 08:34:57: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:57: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:57: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:57: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 2.9802323e-009; epochTime=0.110198s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:58: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747721 * 81; perplexity = 20.03492927
12/15/2016 08:34:58: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747721 * 81
12/15/2016 08:34:58: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:58: learnRatePerSample reduced to 1.4901161e-009
12/15/2016 08:34:58: SGD: revoke back to and update checkpoint file for epoch 10

12/15/2016 08:34:58: Starting Epoch 11: learning rate per sample = 0.000000  effective momentum = 0.000045  momentum as time constant = 1000.0 samples

12/15/2016 08:34:58: Starting minibatch loop.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:58: Finished Epoch[11 of 100]: [Training] CrossEntropyWithSoftmax = 2.44586276 * 81; totalSamplesSeen = 891; learningRatePerSample = 1.4901161e-009; epochTime=0.104357s
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 6 lines with a total of 81+6 tokens.
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
12/15/2016 08:34:58: Final Results: Minibatch[1-1]: CrossEntropyWithSoftmax = 2.99747684 * 81; perplexity = 20.03492172
12/15/2016 08:34:58: Finished Epoch[11 of 100]: [Validate] CrossEntropyWithSoftmax = 2.99747684 * 81
12/15/2016 08:34:58: Loading (rolling back to) previous model with best training-criterion value: C:\Users\svcphil\AppData\Local\Temp\cntk-test-20161215082658.690476\Examples\Text\Miscellaneous_SLU@release_cpu/cntkdebug.dnn.10.
12/15/2016 08:34:58: learnRatePerSample reduced to 7.4505807e-010
12/15/2016 08:34:58: SGD: revoke back to and update checkpoint file for epoch 10
12/15/2016 08:34:58: Learn Rate Per Sample for Epoch[11] = 7.4505807e-010 is less than minLearningRatePerSample 9.9999997e-010. Training complete.

12/15/2016 08:34:59: Action "train" complete.


12/15/2016 08:34:59: ##############################################################################
12/15/2016 08:34:59: #                                                                            #
12/15/2016 08:34:59: # LSTMTest command (write action)                                            #
12/15/2016 08:34:59: #                                                                            #
12/15/2016 08:34:59: ##############################################################################

BatchLUSequenceReader: Input file is C:\jenkins\workspace\CNTK-Test-Windows-W1\Tests\EndToEndTests\Text\SLU/atis.test.apos.pred.pos.head.IOB.simple

Post-processing network...

4 roots:
	CrossEntropyWithSoftmax = CrossEntropyWithSoftmax()
	PosteriorProb = Softmax()
	labels = InputValue()
	outputs = Times()

Loop[0] --> Loop_AutoName38 -> 31 nodes

	AutoName3	AutoName31	AutoName34
	AutoName2	AutoName22	AutoName25
	AutoName6	AutoName21	AutoName26
	AutoName27	AutoName7	AutoName28
	AutoName1	AutoName9	AutoName12
	AutoName5	AutoName8	AutoName13
	AutoName14	AutoName4	AutoName15
	AutoName16	AutoName18	AutoName19
	AutoName20	AutoName29	AutoName30
	AutoName35	AutoName36	AutoName37
	AutoName38

Loop[1] --> Loop_AutoName76 -> 31 nodes

	AutoName41	AutoName69	AutoName72
	AutoName40	AutoName60	AutoName63
	AutoName44	AutoName59	AutoName64
	AutoName65	AutoName45	AutoName66
	AutoName39	AutoName47	AutoName50
	AutoName43	AutoName46	AutoName51
	AutoName52	AutoName42	AutoName53
	AutoName54	AutoName56	AutoName57
	AutoName58	AutoName67	AutoName68
	AutoName73	AutoName74	AutoName75
	AutoName76

Loop[2] --> Loop_AutoName114 -> 31 nodes

	AutoName79	AutoName107	AutoName110
	AutoName78	AutoName98	AutoName101
	AutoName82	AutoName97	AutoName102
	AutoName103	AutoName83	AutoName104
	AutoName77	AutoName85	AutoName88
	AutoName81	AutoName84	AutoName89
	AutoName90	AutoName80	AutoName91
	AutoName92	AutoName94	AutoName95
	AutoName96	AutoName105	AutoName106
	AutoName111	AutoName112	AutoName113
	AutoName114

Validating network. 168 nodes to process in pass 1.

Validating --> labels = InputValue() :  -> [127 x *1]
Validating --> W4 = LearnableParameter() :  -> [127 x 300]
Validating --> WXO3 = LearnableParameter() :  -> [300 x 300]
Validating --> WXO2 = LearnableParameter() :  -> [300 x 300]
Validating --> WXO0 = LearnableParameter() :  -> [300 x 150]
Validating --> E0 = LearnableParameter() :  -> [50 x 944]
Validating --> features = InputValue() :  -> [2832 x *1]
Validating --> LookupTable = LookupTable (E0, features) : [50 x 944], [2832 x *1] -> [150 x *1]
Validating --> AutoName32 = Times (WXO0, LookupTable) : [300 x 150], [150 x *1] -> [300 x *1]
Validating --> bo0 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName33 = Plus (AutoName32, bo0) : [300 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHO0 = LearnableParameter() :  -> [300 x 300]
Validating --> WCO0 = LearnableParameter() :  -> [300 x 1]
Validating --> WXF0 = LearnableParameter() :  -> [300 x 150]
Validating --> AutoName23 = Times (WXF0, LookupTable) : [300 x 150], [150 x *1] -> [300 x *1]
Validating --> bf0 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName24 = Plus (AutoName23, bf0) : [300 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHF0 = LearnableParameter() :  -> [300 x 300]
Validating --> WCF0 = LearnableParameter() :  -> [300 x 1]
Validating --> WXI0 = LearnableParameter() :  -> [300 x 150]
Validating --> AutoName10 = Times (WXI0, LookupTable) : [300 x 150], [150 x *1] -> [300 x *1]
Validating --> bi0 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName11 = Plus (AutoName10, bi0) : [300 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHI0 = LearnableParameter() :  -> [300 x 300]
Validating --> WCI0 = LearnableParameter() :  -> [300 x 1]
Validating --> WXC0 = LearnableParameter() :  -> [300 x 150]
Validating --> AutoName17 = Times (WXC0, LookupTable) : [300 x 150], [150 x *1] -> [300 x *1]
Validating --> WHC0 = LearnableParameter() :  -> [300 x 300]
Validating --> bc0 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName31 = Times (WHO0, AutoName3) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName34 = Plus (AutoName33, AutoName31) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName22 = Times (WHF0, AutoName2) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName25 = Plus (AutoName24, AutoName22) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName21 = DiagTimes (WCF0, AutoName6) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName26 = Plus (AutoName25, AutoName21) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName27 = Sigmoid (AutoName26) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName28 = ElementTimes (AutoName27, AutoName7) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName9 = Times (WHI0, AutoName1) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName12 = Plus (AutoName11, AutoName9) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName8 = DiagTimes (WCI0, AutoName5) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName13 = Plus (AutoName12, AutoName8) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName14 = Sigmoid (AutoName13) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName15 = Times (WHC0, AutoName4) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName16 = Plus (AutoName15, bc0) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName18 = Plus (AutoName17, AutoName16) : [300 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName19 = Tanh (AutoName18) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName20 = ElementTimes (AutoName14, AutoName19) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName29 = Plus (AutoName28, AutoName20) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName30 = DiagTimes (WCO0, AutoName29) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName35 = Plus (AutoName34, AutoName30) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName36 = Sigmoid (AutoName35) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName37 = Tanh (AutoName29) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName38 = ElementTimes (AutoName36, AutoName37) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName70 = Times (WXO2, AutoName38) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> bo2 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName71 = Plus (AutoName70, bo2) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHO2 = LearnableParameter() :  -> [300 x 300]
Validating --> WCO2 = LearnableParameter() :  -> [300 x 1]
Validating --> WXF2 = LearnableParameter() :  -> [300 x 300]
Validating --> AutoName61 = Times (WXF2, AutoName38) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> bf2 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName62 = Plus (AutoName61, bf2) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHF2 = LearnableParameter() :  -> [300 x 300]
Validating --> WCF2 = LearnableParameter() :  -> [300 x 1]
Validating --> WXI2 = LearnableParameter() :  -> [300 x 300]
Validating --> AutoName48 = Times (WXI2, AutoName38) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> bi2 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName49 = Plus (AutoName48, bi2) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHI2 = LearnableParameter() :  -> [300 x 300]
Validating --> WCI2 = LearnableParameter() :  -> [300 x 1]
Validating --> WXC2 = LearnableParameter() :  -> [300 x 300]
Validating --> AutoName55 = Times (WXC2, AutoName38) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> WHC2 = LearnableParameter() :  -> [300 x 300]
Validating --> bc2 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName69 = Times (WHO2, AutoName41) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName72 = Plus (AutoName71, AutoName69) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName60 = Times (WHF2, AutoName40) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName63 = Plus (AutoName62, AutoName60) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName59 = DiagTimes (WCF2, AutoName44) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName64 = Plus (AutoName63, AutoName59) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName65 = Sigmoid (AutoName64) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName66 = ElementTimes (AutoName65, AutoName45) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName47 = Times (WHI2, AutoName39) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName50 = Plus (AutoName49, AutoName47) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName46 = DiagTimes (WCI2, AutoName43) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName51 = Plus (AutoName50, AutoName46) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName52 = Sigmoid (AutoName51) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName53 = Times (WHC2, AutoName42) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName54 = Plus (AutoName53, bc2) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName56 = Plus (AutoName55, AutoName54) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName57 = Tanh (AutoName56) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName58 = ElementTimes (AutoName52, AutoName57) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName67 = Plus (AutoName66, AutoName58) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName68 = DiagTimes (WCO2, AutoName67) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName73 = Plus (AutoName72, AutoName68) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName74 = Sigmoid (AutoName73) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName75 = Tanh (AutoName67) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName76 = ElementTimes (AutoName74, AutoName75) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName108 = Times (WXO3, AutoName76) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> bo3 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName109 = Plus (AutoName108, bo3) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHO3 = LearnableParameter() :  -> [300 x 300]
Validating --> WCO3 = LearnableParameter() :  -> [300 x 1]
Validating --> WXF3 = LearnableParameter() :  -> [300 x 300]
Validating --> AutoName99 = Times (WXF3, AutoName76) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> bf3 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName100 = Plus (AutoName99, bf3) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHF3 = LearnableParameter() :  -> [300 x 300]
Validating --> WCF3 = LearnableParameter() :  -> [300 x 1]
Validating --> WXI3 = LearnableParameter() :  -> [300 x 300]
Validating --> AutoName86 = Times (WXI3, AutoName76) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> bi3 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName87 = Plus (AutoName86, bi3) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> WHI3 = LearnableParameter() :  -> [300 x 300]
Validating --> WCI3 = LearnableParameter() :  -> [300 x 1]
Validating --> WXC3 = LearnableParameter() :  -> [300 x 300]
Validating --> AutoName93 = Times (WXC3, AutoName76) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> WHC3 = LearnableParameter() :  -> [300 x 300]
Validating --> bc3 = LearnableParameter() :  -> [300 x 1]
Validating --> AutoName107 = Times (WHO3, AutoName79) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName110 = Plus (AutoName109, AutoName107) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName98 = Times (WHF3, AutoName78) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName101 = Plus (AutoName100, AutoName98) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName97 = DiagTimes (WCF3, AutoName82) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName102 = Plus (AutoName101, AutoName97) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName103 = Sigmoid (AutoName102) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName104 = ElementTimes (AutoName103, AutoName83) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName85 = Times (WHI3, AutoName77) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName88 = Plus (AutoName87, AutoName85) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName84 = DiagTimes (WCI3, AutoName81) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName89 = Plus (AutoName88, AutoName84) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName90 = Sigmoid (AutoName89) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName91 = Times (WHC3, AutoName80) : [300 x 300], [300 x 1] -> [300 x 1]
Validating --> AutoName92 = Plus (AutoName91, bc3) : [300 x 1], [300 x 1] -> [300 x 1]
Validating --> AutoName94 = Plus (AutoName93, AutoName92) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName95 = Tanh (AutoName94) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName96 = ElementTimes (AutoName90, AutoName95) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName105 = Plus (AutoName104, AutoName96) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName106 = DiagTimes (WCO3, AutoName105) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName111 = Plus (AutoName110, AutoName106) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName112 = Sigmoid (AutoName111) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName113 = Tanh (AutoName105) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName114 = ElementTimes (AutoName112, AutoName113) : [300 x 1 x *1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName115 = Times (W4, AutoName114) : [127 x 300], [300 x 1 x *1] -> [127 x 1 x *1]
Validating --> CrossEntropyWithSoftmax = CrossEntropyWithSoftmax (labels, AutoName115) : [127 x *1], [127 x 1 x *1] -> [1]
Validating --> outputs = Times (W4, AutoName114) : [127 x 300], [300 x 1 x *1] -> [127 x 1 x *1]
Validating --> PosteriorProb = Softmax (outputs) : [127 x 1 x *1] -> [127 x 1 x *1]

Validating network. 119 nodes to process in pass 2.

Validating --> AutoName3 = PastValue (AutoName38) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName31 = Times (WHO0, AutoName3) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName2 = PastValue (AutoName38) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName22 = Times (WHF0, AutoName2) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName6 = PastValue (AutoName29) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName21 = DiagTimes (WCF0, AutoName6) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName7 = PastValue (AutoName29) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName1 = PastValue (AutoName38) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName9 = Times (WHI0, AutoName1) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName5 = PastValue (AutoName29) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName8 = DiagTimes (WCI0, AutoName5) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName4 = PastValue (AutoName38) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName15 = Times (WHC0, AutoName4) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName16 = Plus (AutoName15, bc0) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName41 = PastValue (AutoName76) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName69 = Times (WHO2, AutoName41) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName40 = PastValue (AutoName76) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName60 = Times (WHF2, AutoName40) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName44 = PastValue (AutoName67) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName59 = DiagTimes (WCF2, AutoName44) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName45 = PastValue (AutoName67) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName39 = PastValue (AutoName76) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName47 = Times (WHI2, AutoName39) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName43 = PastValue (AutoName67) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName46 = DiagTimes (WCI2, AutoName43) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName42 = PastValue (AutoName76) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName53 = Times (WHC2, AutoName42) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName54 = Plus (AutoName53, bc2) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]
Validating --> AutoName79 = PastValue (AutoName114) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName107 = Times (WHO3, AutoName79) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName78 = PastValue (AutoName114) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName98 = Times (WHF3, AutoName78) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName82 = PastValue (AutoName105) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName97 = DiagTimes (WCF3, AutoName82) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName83 = PastValue (AutoName105) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName77 = PastValue (AutoName114) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName85 = Times (WHI3, AutoName77) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName81 = PastValue (AutoName105) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName84 = DiagTimes (WCI3, AutoName81) : [300 x 1], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName80 = PastValue (AutoName114) : [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName91 = Times (WHC3, AutoName80) : [300 x 300], [300 x 1 x *1] -> [300 x 1 x *1]
Validating --> AutoName92 = Plus (AutoName91, bc3) : [300 x 1 x *1], [300 x 1] -> [300 x 1 x *1]

Validating network. 42 nodes to process in pass 3.


Validating network, final pass.




Post-processing network complete.



Allocating matrices for forward and/or backward propagation.

Memory Sharing: Out of 168 matrices, 3 are shared as 1, and 165 are not shared.

	{ AutoName115 : [127 x 1 x *1]
	  CrossEntropyWithSoftmax : [1]
	  PosteriorProb : [127 x 1 x *1] }

BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 5 lines with a total of 92+5 tokens.
O O O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O O O O O B-stoploc.city_name I-stoploc.city_name O 
O O O O O O O O O O O O O O O O O O O O O 
O O B-depart_date.month_name B-depart_date.day_number O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_time.time_relative B-depart_time.time I-depart_time.time O 
O O O O O O O O O O O O O O O O O O 
O O B-depart_date.month_name B-depart_date.day_number O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O 
O O O O O O O O O O O O O O O 
O O O O O O O B-round_trip I-round_trip O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number O 
O O O O O O O O O O O O O O O O O O 
O O O O O O O B-fromloc.city_name O B-toloc.city_name I-toloc.city_name I-toloc.city_name O B-depart_date.month_name B-depart_date.day_number O B-airline_name I-airline_name O 
O O O O O O O O O O O O O O O O O O O 
BatchLUSequenceParser: Parsing input data...
BatchLUSequenceParser: Parsed 0 lines with a total of 0+0 tokens.
EnsureDataAvailable: No more data.
Total Samples Evaluated = 91

12/15/2016 08:34:59: Action "write" complete.

12/15/2016 08:34:59: __COMPLETED__
