updated PerformSVDecomposition() to use ValueAsMatrix()

inginx · Jan 21, 2016 · c9530e8 · c9530e8
1 parent ce0c087
commit c9530e8
Showing 1 changed file with 9 additions and 19 deletions.
diff --git a/Source/ComputationNetworkLib/ComputationNetwork.cpp b/Source/ComputationNetworkLib/ComputationNetwork.cpp
@@ -487,11 +487,8 @@ void ComputationNetwork::CollectInputAndLearnableParameters(const ComputationNod
     list<ComputationNodeBasePtr> inputs;
     for (const auto& node : nodes)
     {
-        if (node->OperationName() == OperationNameOf(InputValue) /*L"InputValue"*/ ||
-            node->OperationName() == OperationNameOf(SparseInputValue) /*L"SparseInputValue"*/)
-        {
+        if (node->OperationName() == OperationNameOf(InputValue) || node->OperationName() == OperationNameOf(SparseInputValue))
             inputs.push_back(node);
-        }
     }
     m_inputValues[rootNode] = inputs;
 
@@ -500,13 +497,10 @@ void ComputationNetwork::CollectInputAndLearnableParameters(const ComputationNod
     for (auto nodeIter = nodes.begin(); nodeIter != nodes.end(); nodeIter++)
     {
         ComputationNodeBasePtr node = *nodeIter;
-        if ((node->OperationName() == OperationNameOf(LearnableParameter) && node->IsParameterUpdateRequired())
-            //|| (node->OperationName() == OperationNameOf(SparseLearnableParameter) && node->IsParameterUpdateRequired())
-            )
-        {
+        if (node->OperationName() == OperationNameOf(LearnableParameter) && node->IsParameterUpdateRequired())
             learnableParameterNames.push_back(node->NodeName());
-        }
     }
+
     // sort names so that we get consistent order when load it from saved file
     learnableParameterNames.sort();
 
@@ -944,10 +938,9 @@ void ComputationNetwork::PerformSVDecomposition(const map<wstring, float>& SVDCo
             }
 
             shared_ptr<ComputationNode<ElemType>> pNode = dynamic_pointer_cast<LearnableParameter<ElemType>>(m_nameToNodeMap[name]);
-            //========================================
+
             // Step 1. do SVD decomposition
-            //========================================
-            Matrix<ElemType> A = pNode->Value();
+            Matrix<ElemType> A = pNode->ValueAsMatrix();
 
             // it is a vector, no need to do it
             if (A.GetNumCols() == 1 || A.GetNumRows() == 1)
@@ -966,7 +959,7 @@ void ComputationNetwork::PerformSVDecomposition(const map<wstring, float>& SVDCo
             // VT \in R^{nXn}
             // S \in R^{min(m,n),1}
             // S is in descending order
-            //
+
             ElemType totalenergy = 0.0f;
             for (size_t i = 0; i < S.GetNumRows(); i++)
                 totalenergy += S(i, 0);
@@ -1019,22 +1012,19 @@ void ComputationNetwork::PerformSVDecomposition(const map<wstring, float>& SVDCo
             redU.RowElementMultiplyWith(redS.Transpose());
             redVT.ColumnElementMultiplyWith(redS);
 
-            //========================================
+
             // Step 2. create two new Parameter nodes and one Times node
-            //========================================
             wstring leftChildName = name + L"-U";
             wstring rightChildName = name + L"-V";
             shared_ptr<ComputationNode<ElemType>> pLeft = AddNodeToNetWithElemType(New<LearnableParameter<ElemType>>(m_deviceId, leftChildName, m, r));
             shared_ptr<ComputationNode<ElemType>> pRight = AddNodeToNetWithElemType(New<LearnableParameter<ElemType>>(m_deviceId, rightChildName, r, n));
 
-            pLeft->Value() = redU;
-            pRight->Value() = redVT;
+            pLeft->ValueAsMatrix() = redU;
+            pRight->ValueAsMatrix() = redVT;
 
             shared_ptr<ComputationNode<ElemType>> pTimes = AddNodeToNetAndAttachInputs(New<TimesNode<ElemType>>(m_deviceId, name + L"-SVD"), pLeft, pRight);
 
-            //========================================
             // Step 3. remove old node
-            //========================================
             ReplaceLeafNode(name, pTimes);
         }
     }