Address review comments

2016-04-13 14:30:06 +02:00 · 2016-04-13 14:30:06 +02:00 · ca4afe5c67
--- a/1
+++ b/1
@ -586,7 +586,6 @@ CNTK_SRC =\
 	$(SOURCEDIR)/CNTK/BrainScript/BrainScriptEvaluator.cpp \
 	$(SOURCEDIR)/CNTK/BrainScript/BrainScriptParser.cpp \
 	$(SOURCEDIR)/CNTK/BrainScript/BrainScriptTest.cpp \
-	$(SOURCEDIR)/CNTK/BrainScript/ExperimentalNetworkBuilder.cpp \
 	$(SOURCEDIR)/Common/BestGpu.cpp \
 	$(SOURCEDIR)/Common/MPIWrapper.cpp \

--- a/Source/ActionsLib/NDLNetworkBuilder.cpp
+++ b/Source/ActionsLib/NDLNetworkBuilder.cpp
@ -73,7 +73,7 @@ void NDLNodeEvaluatorImpl<ElemType>::Evaluate(NDLNode<ElemType>* node, const wst
            size_t i = 0;
            auto tensorShape = ProcessTensorShapeParameters(node, params, i, /*isImage=*/false, cnNodeType);

-            wstring dynamicAxis = node->GetOptionalParameter("dynamic", "");
+            wstring dynamicAxis = node->GetOptionalParameter("dynamicAxis", "");
            // first look for this node already existing in the network
            // BUGBUG: How does this set the dimensions then?
            if (m_net->NodeNameExists(name))
@ -98,7 +98,7 @@ void NDLNodeEvaluatorImpl<ElemType>::Evaluate(NDLNode<ElemType>* node, const wst
            size_t imageHeight   = ((NDLNode<ElemType>*) params[1])->GetScalar();
            size_t imageChannels = ((NDLNode<ElemType>*) params[2])->GetScalar();
            ImageLayoutKind imageLayoutKind = ImageLayoutKindFrom(node->GetOptionalParameter("imageLayout", "HWC"));
-            wstring dynamicAxis = node->GetOptionalParameter("dynamic", "");
+            wstring dynamicAxis = node->GetOptionalParameter("dynamicAxis", "");

            if (isSparse)
                nodePtr = builder.CreateSparseInputNode(name, ImageDimensions::AsTensorShape(imageWidth, imageHeight, imageChannels, imageLayoutKind), dynamicAxis);
--- a/Source/CNTK/BrainScript/CNTKCoreLib/CNTK.core.bs
+++ b/Source/CNTK/BrainScript/CNTKCoreLib/CNTK.core.bs
@ -34,11 +34,11 @@ Parameter = LearnableParameter // deprecated
 # TODO: make Parameter take tensor dims?
 ParameterTensor(dims, learningRateMultiplier = 1.0, init = 'uniform'/*|fixedValue|gaussian|fromFile*/, initValueScale = 1, value = 0, initFromFilePath = '', initFromLiteral = '', initOnCPUOnly=true, randomSeed=-1, tag='') = new ComputationNode [ operation = 'LearnableParameter' ; shape = new TensorShape [ /*dims*/ ] /*plus the function args*/ ]
 ConstantFromString(literal, tag='') = ParameterTensor((0)/*dim, will be inferred*/, init = 'fromLiteral', initFromLiteral = literal, learningRateMultiplier = 0.0)
-DynamicAxis(Name='', tag='') = new ComputationNode [ operation = 'DynamicAxis' ; name = Name ]
-Input(dims, dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'InputValue' ; shape = new TensorShape [ /*dims*/ ] ; dynamicAxes = dynamicAxis ; isImage = false /*plus the function args*/ ]
-SparseInput(dims, dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'SparseInputValue' ; shape = new TensorShape [ /*dims*/ ] ; dynamicAxes = dynamicAxis ; isImage = false /*plus the function args*/ ]
-ImageInput(imageWidth, imageHeight, imageChannels, imageLayout='CHW', dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'InputValue' ; dynamicAxes = dynamicAxis ; isImage = true /*plus the function args*/ ]
-SparseImageInput(imageWidth, imageHeight, imageChannels, imageLayout='CHW', dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'SparseInputValue' ; dynamicAxes = dynamicAxis ; isImage = true /*plus the function args*/ ]
+DynamicAxis(name='', tag='') = new ComputationNode [ operation = 'DynamicAxis' ; /*plus the function args*/  ]
+Input(dims, dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'InputValue' ; shape = new TensorShape [ /*dims*/ ] ; isImage = false /*plus the function args*/ ]
+SparseInput(dims, dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'SparseInputValue' ; shape = new TensorShape [ /*dims*/ ] ; isImage = false /*plus the function args*/ ]
+ImageInput(imageWidth, imageHeight, imageChannels, imageLayout='CHW', dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'InputValue' ; isImage = true /*plus the function args*/ ]
+SparseImageInput(imageWidth, imageHeight, imageChannels, imageLayout='CHW', dynamicAxis='', tag='feature') = new ComputationNode [ operation = 'SparseInputValue' ; isImage = true /*plus the function args*/ ]
 EnvironmentInput(propertyName, tag='') = new ComputationNode [ operation = 'EnvironmentInput' /*plus the function args*/ ]
 ConstantTensor(val, dims, tag='') = ParameterTensor(dims, learningRateMultiplier = 0, init = 'fixedValue', value = val) 
 Constant(val, rows = 1, cols = 1, tag='') = Parameter(rows, cols, learningRateMultiplier = 0, init = 'fixedValue', value = val) 
--- a/Source/CNTK/BrainScript/ExperimentalNetworkBuilder.cpp
+++ b/Source/CNTK/BrainScript/ExperimentalNetworkBuilder.cpp
@ -1,134 +0,0 @@
-#if 0 // this entire file can be removed once CNTK.core.bs works
-// ExperimentalNetworkBuilder.cpp -- interface to new version of NDL (and config) parser  --fseide
-
-#define _CRT_NONSTDC_NO_DEPRECATE // make VS accept POSIX functions without _
-#define _CRT_SECURE_NO_WARNINGS   // "secure" CRT not available on all platforms  --add this at the top of all CPP files that give "function or variable may be unsafe" warnings
-
-#include <string>
-
-using namespace std;
-
-// TODO: move to actual text files to be included
-
-wstring standardFunctions =
-    L"Print(value, format='') = new PrintAction [ what = value /*; how = format*/ ] \n"
-    L"Debug(value, say = '', enabled = true) = new Debug [ /*macro arg values*/ ] \n"
-    L"Format(value, format) = new StringFunction [ what = 'Format' ; arg = value ; how = format ] \n"
-    L"Replace(s, from, to) = new StringFunction [ what = 'Replace' ; arg = s ; replacewhat = from ; withwhat = to ] \n"
-    L"Substr(s, begin, num) = new StringFunction [ what = 'Substr' ; arg = s ; pos = begin ; chars = num ] \n"
-    L"Chr(c) = new StringFunction [ what = 'Chr' ;  arg = c ] \n"
-    L"Floor(x)  = new NumericFunction [ what = 'Floor' ;  arg = x ] \n"
-    L"Length(x) = new NumericFunction [ what = 'Length' ; arg = x ] \n"
-    L"Ceil(x) = -Floor(-x) \n"
-    L"Round(x) = Floor(x+0.5) \n"
-    L"Sign(x) = if x > 0 then 1 else if x < 0 then -1 else 0 \n"
-    L"Min(a,b) = if a < b then a else b \n"
-    L"Max(a,b) = if a > b then a else b \n"
-    L"Fac(n) = if n > 1 then Fac(n-1) * n else 1 \n";
-
-wstring commonMacros =
-    L"BFF(in, rows, cols) = [ B = Parameter(rows, 1, init = 'fixedValue', value = 0) ; W = Parameter(rows, cols) ; z = W*in+B ] \n"
-    L"SBFF(in, rows, cols) = [ Eh = Sigmoid(BFF(in, rows, cols).z) ] \n "
-    L"MeanVarNorm(feat) = PerDimMeanVarNormalization(feat, Mean(feat), InvStdDev(feat)) \n"
-    L"LogPrior(labels) = Log(Mean(labels)) \n";
-
-wstring computationNodes = // TODO: use actual TypeName() here? would first need to make it a wide string; we should also extract those two methods into the base macro
-L"LearnableParameter(rows, cols, learningRateMultiplier = 1.0, init = 'uniform'/*|fixedValue|gaussian|fromFile*/, initValueScale = 1, value = 0, initFromFilePath = '', initOnCPUOnly=true, randomSeed=-1, tag='') = new ComputationNode [ operation = 'LearnableParameter' ; shape = new TensorShape [ dims = (rows : cols) ] /*plus the function args*/ ]\n"
-    L"Parameter = LearnableParameter // deprecated \n"
-L"ParameterTensor(dims, learningRateMultiplier = 1.0, init = 'uniform'/*|fixedValue|gaussian|fromFile*/, initValueScale = 1, value = 0, initFromFilePath = '', initOnCPUOnly=true, randomSeed=-1, tag='') = new ComputationNode [ operation = 'LearnableParameter' ; shape = new TensorShape [ /*dims*/ ] /*plus the function args*/ ]\n"
-    // TODO: ImageParameter?
-    // ^^ already works; vv untested
-    L"Input(dims, tag='feature') = new ComputationNode [ operation = 'InputValue' ; shape = new TensorShape [ /*dims*/ ] ; isImage = false /*plus the function args*/ ]\n" // note: naming a little inconsistent  // TODO: re-test after flag change
-    L"SparseInput(dims, tag='feature') = new ComputationNode [ operation = 'SparseInputValue' ; shape = new TensorShape [ /*dims*/ ] ; isImage = false /*plus the function args*/ ]\n"
-    L"ImageInput(imageWidth, imageHeight, imageChannels, imageLayout='CHW', tag='feature') = new ComputationNode [ operation = 'InputValue' ; isImage = true /*plus the function args*/ ]\n"
-    L"SparseImageInput(imageWidth, imageHeight, imageChannels, imageLayout='CHW', tag='feature') = new ComputationNode [ operation = 'SparseInputValue' ; isImage = true /*plus the function args*/ ]\n"
-    L"Constant(val, rows = 1, cols = 1, tag='') = Parameter(rows, cols, learningRateMultiplier = 0, init = 'fixedValue', value = val) \n"
-    L"PastValue(dims, input, timeStep = 1, defaultHiddenActivation = 0.1, tag='') = new ComputationNode [ operation = 'PastValue' ; inputs = input ; shape = new TensorShape [ /*dims*/ ] /*plus the function args*/ ]\n"
-    L"FutureValue(dims, input, timeStep = 1, defaultHiddenActivation = 0.1, tag='') = new ComputationNode [ operation = 'FutureValue' ; inputs = input ; shape = new TensorShape [ /*dims*/ ] /*plus the function args*/ ]\n"
-    // TODO: ^^ DelayedValues no longer need to know their dimension. That is inferred in Validation.
-    L"Shift(input, fromOffset, boundaryValue, boundaryMode=-1/*context*/, dim=-1, tag='') = new ComputationNode [ operation = 'Shift' ; inputs = (input : boundaryValue) /*plus the function args*/ ]\n"
-    L"RowSlice(startIndex, numRows, input, tag='') = new ComputationNode [ operation = 'RowSlice' ; inputs = input /*plus the function args*/ ]\n"
-    L"RowRepeat(input, numRepeats, tag='') = new ComputationNode [ operation = 'RowRepeat' ; inputs = input /*plus the function args*/ ]\n"
-    L"RowStack(inputs, tag='') = new ComputationNode [ operation = 'RowStack' /*plus the function args*/ ]\n"
-    L"Reshape(input, numRows, imageWidth = 0, imageHeight = 0, imageChannels = 0, tag='') = new ComputationNode [ operation = 'LegacyReshape' ; inputs = input /*plus the function args*/ ]\n"
-    L"NewReshape(input, dims, beginDim=0, endDim=0, tag='') = new ComputationNode [ operation = 'Reshape' ; inputs = input ; shape = new TensorShape [ /*dims*/ ] /*plus the function args*/ ]\n"
-    L"ReshapeDimension(x, dim, tensorShape) = NewReshape(x, tensorShape, beginDim=dim, endDim=dim + 1) \n"
-    L"FlattenDimensions(x, dim, num) = NewReshape(x, 0, beginDim=dim, endDim=dim + num) \n"
-    L"SplitDimension(x, dim, N) = ReshapeDimension(x, dim, 0:N) \n"
-    L"TransposeDimensions(input, dim1, dim2, tag='') = new ComputationNode [ operation = 'TransposeDimensions' ; inputs = input /*plus the function args*/ ]\n"
-    L"Transpose(x) = TransposeDimensions(x, 1, 2)\n"
-    L"Times(A, B, outputRank=1, tag='') = new ComputationNode [ operation = 'Times' ; inputs = ( A : B ) /*plus the function args*/ ]\n"
-    // TODO: Logistic should be generated with with BinaryStandardNode macro below.
-    L"Logistic(label, probability, tag='') = new ComputationNode [ operation = 'Logistic' ; inputs = (label : probability) /*plus the function args*/ ]\n"
-    L"WeightedLogistic(label, probability, instanceWeight, tag='') = new ComputationNode [ operation = 'Logistic' ; inputs = (label : probability : instanceWeight) /*plus the function args*/ ]\n"
-    L"ReconcileDynamicAxis(dataInput, layoutInput, tag='') = new ComputationNode [ operation = 'ReconcileDynamicAxis' ; inputs = (dataInput : layoutInput) /*plus the function args*/ ]\n"
-    L"Convolution(weightNode, inputValueNode, kernelWidth, kernelHeight, outputChannels, horizontalSubsample, verticalSubsample, zeroPadding = false, maxTempMemSizeInSamples = 0, imageLayout='CHW', tag='') = new ComputationNode [ operation = 'Convolution' ; inputs = (weightNode : inputValueNode) /*plus the function args*/ ]\n"
-    L"MaxPooling(input, windowWidth, windowHeight, horizontalSubsample, verticalSubsample, imageLayout='CHW', tag='') = new ComputationNode [ operation = 'MaxPooling' ; inputs = input /*plus the function args*/ ]\n"
-    L"AveragePooling(input, windowWidth, windowHeight, horizontalSubsample, verticalSubsample, imageLayout='CHW', tag='') = new ComputationNode [ operation = 'AveragePooling' ; inputs = input /*plus the function args*/ ]\n"
-    // TODO: define DelayedValue, with negative delay for future; cannot do this yet, need to be able to say something like delay = -(^.delay)
-    // aliases
-    L"ColumnwiseCrossProduct = KhatriRaoProduct // deprecated \n" // TODO: should it be deprecated? It is described as easier to understand in the CNTKBook.
-    L"ClassificationError = ErrorPrediction \n"
-    L"Delay = PastValue \n" // TODO: should it allow negative offsets and an if test here?
-    L"BatchNormalization(input, scale, bias, runMean, runInvStdDev, eval, spatial, normalizationTimeConstant = 0, epsilon = 0.00001, useCntkEngine = true, imageLayout='CHW', tag='') = new ComputationNode [ operation = 'BatchNormalization' ; inputs = (input : scale : bias : runMean : runInvStdDev) /*plus the function args*/ ]\n"
-// standard nodes. We use macros to define these strings.
-#define UnaryStandardNode(Op, a) L## #Op L"(" L## #a L", tag='') = new ComputationNode [ operation = '" L## #Op L"' ; inputs = " L## #a L" /*plus the function args*/ ]\n"
-#define BinaryStandardNode(Op, a, b) L## #Op L"(" L## #a L", " L## #b L", tag='') = new ComputationNode [ operation = '" L## #Op L"' ; inputs = (" L## #a L" : " L## #b L") /*plus the function args*/ ]\n"
-#define TernaryStandardNode(Op, a, b, c) L## #Op L"(" L## #a L", " L## #b L", " L## #c L", tag='') = new ComputationNode [ operation = '" L## #Op L"' ; inputs = (" L## #a L" : " L## #b L" : " L## #c L") /*plus the function args*/ ]\n"
-#define QuaternaryStandardNode(Op, a, b, c, d) L## #Op L"(" L## #a L", " L## #b L", " L## #c L", " L## #d L", tag='') = new ComputationNode [ operation = '" L## #Op L"' ; inputs = (" L## #a L" : " L## #b L" : " L## #c L" : " L## #d L") /*plus the function args*/ ]\n"
-#ifdef COMING_SOON
-    TernaryStandardNode(CRF, labelVectorSequence, positionDependenScoreVectorSequence, transitionScores) // TODO: better names
-#endif
-    UnaryStandardNode(Abs, x)
-    QuaternaryStandardNode(ClassBasedCrossEntropyWithSoftmax, labelClassDescriptorVectorSequence, mainInputInfo, mainWeight, classLogProbsBeforeSoftmax)
-    // BUGBUG: the commented-out ones are not mentioned in the CNTK book, nor are their parameters documented in the source code
-    BinaryStandardNode(ColumnElementTimes, aVectorSequence, anotherVectorSequence)
-    BinaryStandardNode(CosDistance, aVectorSequence, anotherVectorSequence)
-    QuaternaryStandardNode(CosDistanceWithNegativeSamples, aVectorSequence, anotherVectorSequence, numShifts, numNegSamples)
-    //BinaryStandardNode(CosDistanceWithNegativeSamplesNode)
-    UnaryStandardNode(Cosine, x)
-    BinaryStandardNode(CrossEntropy, refProbVectorSequence, outProbVectorSequence)
-    BinaryStandardNode(CrossEntropyWithSoftmax, labelVectorSequence, outProbVectorSequence)
-    BinaryStandardNode(DiagTimes, diagonalMatrixAsColumnVector, matrix)
-    UnaryStandardNode(Dropout, activationVectorSequence)
-    //BinaryStandardNode(DummyCriterionNode)
-    BinaryStandardNode(ElementTimes, aMatrix, anotherMatrix)
-    BinaryStandardNode(ErrorPrediction, labelVectorSequence, outVectorSequence) // CNTKBook: ClassificationError?
-    UnaryStandardNode(Exp, x)
-    QuaternaryStandardNode(GMMLogLikelihood, unnormalizedPriorVector, meansAsRows, logStdDevAsRows, dataVectorSequence)
-    UnaryStandardNode(InvStdDev, dataVectorSequence)
-    BinaryStandardNode(KhatriRaoProduct, leftMatrix, rightMatrix)
-    //BinaryStandardNode(LSTMNode)
-    UnaryStandardNode(Log, x)
-    UnaryStandardNode(LogSoftmax, z)
-    //BinaryStandardNode(LookupTableNode)
-    UnaryStandardNode(MatrixL1Reg, matrix)
-    UnaryStandardNode(MatrixL2Reg, matrix)
-    // BUGBUG: CNTKBook also mentions L1Norm and L2Norm
-    UnaryStandardNode(Mean, dataVectorSequence)
-    BinaryStandardNode(Minus, leftMatrix, rightMatrix)
-    UnaryStandardNode(Negate, input)
-    TernaryStandardNode(PerDimMeanVarDeNormalization, dataVectorSequence, meanVector, invStdDevVector) // TODO: correct?
-    TernaryStandardNode(PerDimMeanVarNormalization, dataVectorSequence, meanVector, invStdDevVector)
-    BinaryStandardNode(Plus, leftMatrix, rightMatrix)
-    UnaryStandardNode(RectifiedLinear, z)
-    //BinaryStandardNode(RowElementTimesNode)
-    BinaryStandardNode(Scale, scalarScalingFactor, matrix)
-#ifdef COMING_SOON
-    //BinaryStandardNode(SequenceDecoderNode)
-#endif
-    UnaryStandardNode(Sigmoid, z)
-    UnaryStandardNode(Softmax, z)
-    UnaryStandardNode(Hardmax, z)
-    BinaryStandardNode(SquareError, aMatrix, anotherMatrix)
-    UnaryStandardNode(SumColumnElements, z)
-    UnaryStandardNode(SumElements, matrix)
-    UnaryStandardNode(Tanh, z)
-    UnaryStandardNode(TimeReverse, vectorSequence)
-    BinaryStandardNode(TransposeTimes, leftMatrix, rightMatrix)
-    // those nodes are deprecated, we won't implement them in BS:
-    //BinaryStandardNode(NoiseContrastiveEstimationNode)
-    //BinaryStandardNode(ParallelNode)
-    //BinaryStandardNode(StrideTimesNode)
-    ;
-#endif
--- a/Source/CNTK/CNTK.vcxproj
+++ b/Source/CNTK/CNTK.vcxproj
@ -203,7 +203,6 @@
    <ClCompile Include="BrainScript\BrainScriptEvaluator.cpp" />
    <ClCompile Include="BrainScript\BrainScriptParser.cpp" />
    <ClCompile Include="BrainScript\BrainScriptTest.cpp" />
-    <ClCompile Include="BrainScript\ExperimentalNetworkBuilder.cpp" />
    <ClCompile Include="CNTK.cpp" />
    <ClCompile Include="ModelEditLanguage.cpp" />
    <ClCompile Include="stdafx.cpp" />
@ -226,4 +225,4 @@
  </ItemGroup>
  <Import Project="$(VCTargetsPath)\Microsoft.Cpp.targets" />
  <ImportGroup Label="ExtensionTargets" />
-</Project>
+</Project>
--- a/Source/CNTK/CNTK.vcxproj.filters
+++ b/Source/CNTK/CNTK.vcxproj.filters
@ -44,9 +44,6 @@
    <ClCompile Include="BrainScript\BrainScriptTest.cpp">
      <Filter>BrainScript</Filter>
    </ClCompile>
-    <ClCompile Include="BrainScript\ExperimentalNetworkBuilder.cpp">
-      <Filter>BrainScript</Filter>
-    </ClCompile>
    <ClCompile Include="..\Common\ExceptionWithCallStack.cpp">
      <Filter>Common</Filter>
    </ClCompile>
--- a/Source/Common/Include/Sequences.h
+++ b/Source/Common/Include/Sequences.h
@ -120,6 +120,8 @@ struct MBLayout

    // copy the content of another MBLayoutPtr over
    // Use this instead of actual assignment to make it super-obvious that this is not copying the pointer but actual content. The pointer is kept fixed.
+    // Use "keepName" if the "identity" of the target is to be preserved, e.g. 
+    // while copying from reader space to network space.
    void CopyFrom(const MBLayoutPtr& other, bool keepName=false)
    {
        m_numTimeSteps = other->m_numTimeSteps;
@ -521,7 +523,7 @@ private:
    size_t m_numFramesDeclared;
    size_t m_numGapFrames;

-    // Lookup tables for determining whether any sequence at time t is a identical layouts, do noboundary or gap.
+    // Lookup tables for determining whether any sequence at time t is a boundary or gap.
    // An optional time delay can be given, then the test is whether going from t to (t + time delay) crosses a boundary.
    // The purpose is for knowing when to reset state of a recurrent node.
    //
--- a/Source/ComputationNetworkLib/ComputationNetworkBuilder.cpp
+++ b/Source/ComputationNetworkLib/ComputationNetworkBuilder.cpp
@ -76,7 +76,7 @@ static shared_ptr<ComputationNode<ElemType>> CreateStandardNode(const std::wstri
    else if (nodeType == OperationNameOf(PerDimMeanVarDeNormalizationNode))     return New<PerDimMeanVarDeNormalizationNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(PassNode))                             return New<PassNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(PlusNode))                             return New<PlusNode<ElemType>>(forward<_Types>(_Args)...);
-    else if (nodeType == OperationNameOf(ReconcileDynamicAxisNode))                return New<ReconcileDynamicAxisNode<ElemType>>(forward<_Types>(_Args)...);
+    else if (nodeType == OperationNameOf(ReconcileDynamicAxisNode))             return New<ReconcileDynamicAxisNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(ReciprocalNode))                       return New<ReciprocalNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(RectifiedLinearNode))                  return New<RectifiedLinearNode<ElemType>>(forward<_Types>(_Args)...);
    else if (nodeType == OperationNameOf(ReshapeNode))                          return New<ReshapeNode<ElemType>>(forward<_Types>(_Args)...);
--- a/Source/ComputationNetworkLib/ComputationNetworkEvaluation.cpp
+++ b/Source/ComputationNetworkLib/ComputationNetworkEvaluation.cpp
@ -525,13 +525,19 @@ void ComputationNetwork::ResetMBLayouts()
    for (const auto& node : GetAllNodesForRoot(nullptr))
        node->LinkToMBLayout(nullptr);

-    // DynamicAxis nodes are (apart from the network-wide MBLayout) the only holders of MBLayouts. Initialize them.
+    // DynamicAxis nodes are (apart from the network-wide MBLayout) the main holders of MBLayouts. Initialize them.
+    // The only other instances are nodes that change the MBLayout, like WhereNode. 
    for (auto node : GetNodesWithType(L"DynamicAxis"))
        node->LinkToMBLayout(make_shared<MBLayout>(1, 0, node->GetName()));

    // This is now initialized inside of the Input nodes, with the proper connections.
    for (auto node : InputNodes(nullptr))
-        node->AttachDynamicAxis([&](std::wstring name) { return GetNodeFromName(name); }, /* default */ m_pMBLayoutOfNetwork);
+    {
+        auto n = dynamic_pointer_cast<IDynamic>(node);
+        if (!n)
+            LogicError("Expected %ls to implement IDynamic, but it doesn't.", node->NodeDescription().c_str());
+        n->AttachDynamicAxis([&](std::wstring name) { return GetNodeFromName(name); }, /* default */ m_pMBLayoutOfNetwork);
+    }
 }

 // -----------------------------------------------------------------------
--- a/Source/ComputationNetworkLib/ComputationNode.cpp
+++ b/Source/ComputationNetworkLib/ComputationNode.cpp
@ -332,28 +332,25 @@ TensorShape ComputationNodeBase::GetOneSampleTensorSliceFor(size_t rank, const F
                prototype += "NULL";
                continue;
            }
-
-            const char* mbSizeMark = child->m_pMBLayout ? " x " : "";
-#if 0
-            if (child->m_sampleLayout.GetRank() == 3 && (child->m_sampleLayout[1] != 1 || child->m_sampleLayout[0] != 1)) // looks like an image: use WHC notation
-                prototype += msra::strfun::strprintf("%ls[%s%s {W=%lu, H=%lu, C=%lu}]", child->NodeName().c_str(), string(child->m_sampleLayout).c_str(), mbSizeMark,
-                child->m_sampleLayout[1], child->m_sampleLayout[2], child->m_sampleLayout[0]);
-            // BUGBUG: This ^^ will print based on the old legacy layout, and we have no way of knowing here whether that is correct.
-            else
-#endif
-                prototype += msra::strfun::strprintf("[%s%s%ls]", string(child->m_sampleLayout).c_str(), mbSizeMark, 
-                                                     child->HasMBLayout() ? child->GetMBLayout()->GetAxisName().c_str() : L"");
+            prototype += child->ShapeDescription().c_str();
        }
        prototype += extraArgs;
        //prototype += ")";
    }

-    prototype += msra::strfun::strprintf(" -> [%s%s%ls]", string(GetSampleLayout()).c_str(), HasMBLayout() ? " x " : "", 
-                                         HasMBLayout() ? GetMBLayout()->GetAxisName().c_str() : L"");
+    prototype += msra::strfun::strprintf(" -> %s", ShapeDescription().c_str());

    return prototype;
 }

+const std::string ComputationNodeBase::ShapeDescription() const
+{
+    return msra::strfun::strprintf("[%s%s%ls]", 
+                                   string(m_sampleLayout).c_str(), 
+                                   HasMBLayout() ? " x " : "", 
+                                   HasMBLayout() ? GetMBLayout()->GetAxisName().c_str() : L"");
+}
+
 template <class ElemType>
 /*virtual*/ void ComputationNode<ElemType>::DumpNodeInfo(const bool /*printValues*/, const bool printMetadata, File& fstream) const
 {
--- a/Source/ComputationNetworkLib/ComputationNode.h
+++ b/Source/ComputationNetworkLib/ComputationNode.h
@ -473,12 +473,6 @@ public:
        VerifyDims(node->GetSampleLayout(), node->HasMBLayout());
    }

-    virtual void AttachDynamicAxis(std::function<ComputationNodeBasePtr(const std::wstring)> nodeLookup, MBLayoutPtr defaultLayout)
-    {
-        // Applies only to input nodes.
-        NOT_IMPLEMENTED;
-    }
-
    // MBLayout (minibatch structure)
    void LinkToMBLayout(MBLayoutPtr pMBLayout)
    {
@ -551,7 +545,7 @@ public:
        return GetInputsFromConfig(configp, L"inputs");
    }

-    static vector<ComputationNodeBasePtr> GetInputsFromConfig(const ScriptableObjects::IConfigRecordPtr configp, const std::wstring property)
+    static vector<ComputationNodeBasePtr> GetInputsFromConfig(const ScriptableObjects::IConfigRecordPtr configp, const std::wstring& property)
    {
        vector<ComputationNodeBasePtr> inputs;
        const auto* inputsArg = configp->Find(property);
@ -810,6 +804,9 @@ public:
        return std::wstring(L"Node '") + NodeName().c_str() + L"' (" + OperationName().c_str() + L" operation)"; 
    };

+    // Helper that returns [a x b x c], including dynamic axes.
+    const std::string ShapeDescription() const;
+
 protected:

    // -----------------------------------------------------------------------
@ -844,7 +841,8 @@ protected:
 typedef ComputationNodeBase::ComputationNodeBasePtr ComputationNodeBasePtr;

 // =======================================================================
-// NumInputs -- little helper interface to allow derived Node classes to specify how many inputs they expect
+// NumInputs -- little helper interface to allow derived Node classes to 
+// specify how many inputs they expect
 // =======================================================================

 struct INumInputs { virtual size_t GetExpectedNumInputs() const = 0; };
@ -857,6 +855,14 @@ struct NumInputs : public INumInputs // e.g. derive from NumInputs<2>
    }
 };

+// =======================================================================
+// 
+// =======================================================================
+struct IDynamic
+{
+    virtual void AttachDynamicAxis(std::function<ComputationNodeBasePtr(const std::wstring)> nodeLookup, MBLayoutPtr defaultLayout) = 0;
+};
+
 // =======================================================================
 // ComputationNode -- abstract base class for computation nodes, deriving
 // from CompuationNodeBase, parameterized by float vs. double
@ -1921,7 +1927,6 @@ protected:
 public:                                                                                                                                                  \
    using Base::AttachInputs;                                                                                                                            \
    using Base::AttachInputsFromConfig;                                                                                                                  \
-    using Base::AttachDynamicAxis;                                                                                                                       \
    using Base::CreateGradientMatrixIfNull;                                                                                                              \
    using Base::NodeName;                                                                                                                                \
    using Base::RequiresPreCompute;                                                                                                                      \
--- a/Source/ComputationNetworkLib/InputAndParamNodes.h
+++ b/Source/ComputationNetworkLib/InputAndParamNodes.h
@ -129,7 +129,7 @@ public:
        m_displayName = name;
    }
    DynamicAxisNode(const ScriptableObjects::IConfigRecordPtr configp)
-        : DynamicAxisNode(configp->Get(L"deviceId"), (const std::wstring&)configp->Get(L"name"))
+        : DynamicAxisNode(configp->Get(L"deviceId"), (const std::wstring&)configp->Get(L"axisName"))
    {
    }

@ -168,7 +168,7 @@ template class DynamicAxisNode<double>;
 // -----------------------------------------------------------------------

 template <class ElemType>
-class InputValueBase : public ComputationNode<ElemType>, public NumInputs<0>
+class InputValueBase : public ComputationNode<ElemType>, public NumInputs<0>, public IDynamic
 {
    typedef ComputationNode<ElemType> Base;
    UsingComputationNodeMembers;
@ -205,11 +205,11 @@ protected:
    {
        AttachInputsFromConfig(configp, this->GetExpectedNumInputs());
        wstring axisName = L"";
-        if (configp->Exists(L"dynamicAxes"))
+        if (configp->Exists(L"dynamicAxis"))
        {
-            if (configp->Find(L"dynamicAxes")->Is<ComputationNodeBase>())
+            if (configp->Find(L"dynamicAxis")->Is<ComputationNodeBase>())
            {
-                ComputationNodeBasePtr axis = configp->Get(L"dynamicAxes");
+                ComputationNodeBasePtr axis = configp->Get(L"dynamicAxis");
                axisName = axis->GetName();
            }
            // Else: Use default axis.
@ -245,7 +245,7 @@ protected:
        // more dependencies on the order in which things are evaluated, though.
        if (!node->Is<DynamicAxisNode<ElemType>>())
            RuntimeError("%ls: dynamicAxis argument must be of type DynamicAxis(), but got %ls.",
-            NodeDescription().c_str(), node->NodeDescription().c_str());
+                         NodeDescription().c_str(), node->NodeDescription().c_str());
        m_dynamicAxisNode = node->As<DynamicAxisNode<ElemType>>();
        if (!m_dynamicAxisNode->HasMBLayout())
            LogicError("%ls: Expected %ls to have MBLayout, but it doesn't.", NodeDescription().c_str(), node->NodeDescription().c_str());
--- a/Tests/UnitTests/NetworkTests/NetworkTests.vcxproj
+++ b/Tests/UnitTests/NetworkTests/NetworkTests.vcxproj
@ -122,7 +122,6 @@
    <ClCompile Include="..\..\..\Source\CNTK\BrainScript\BrainScriptEvaluator.cpp" />
    <ClCompile Include="..\..\..\Source\CNTK\BrainScript\BrainScriptParser.cpp" />
    <ClCompile Include="..\..\..\Source\CNTK\BrainScript\BrainScriptTest.cpp" />
-    <ClCompile Include="..\..\..\Source\CNTK\BrainScript\ExperimentalNetworkBuilder.cpp" />
    <ClCompile Include="..\..\..\Source\Common\Config.cpp" />
    <ClCompile Include="..\..\..\Source\Common\DataReader.cpp" />
    <ClCompile Include="..\..\..\Source\Common\DataWriter.cpp" />
--- a/Tests/UnitTests/NetworkTests/NetworkTests.vcxproj.filters
+++ b/Tests/UnitTests/NetworkTests/NetworkTests.vcxproj.filters
@ -34,9 +34,6 @@
    <ClCompile Include="..\..\..\Source\CNTK\BrainScript\BrainScriptTest.cpp">
      <Filter>From BrainScript</Filter>
    </ClCompile>
-    <ClCompile Include="..\..\..\Source\CNTK\BrainScript\ExperimentalNetworkBuilder.cpp">
-      <Filter>From BrainScript</Filter>
-    </ClCompile>
  </ItemGroup>
  <ItemGroup>
    <Filter Include="Config">