Merge branch 'deepbliscore/vnext' of https://github.com/Microsoft/CNTK …

…into deepbliscore/vnext

Makefile

@@ -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 \
 

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);

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(axisName='', 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) 

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>

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>

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 @@ struct MBLayout
     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.
     //

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)...);