debug

Source/ComputationNetworkLib/EvaluationNodes.h

@@ -60,9 +60,9 @@ public:
         MaskMissingColumnsToZero(*m_maxIndexes0, InputRef(0).GetMBLayout(), fr);
         MaskMissingColumnsToZero(*m_maxIndexes1, InputRef(1).GetMBLayout(), fr);
         Value().AssignNumOfDiff(*m_maxIndexes0, *m_maxIndexes1, m_topK > 1);
-#if NANCHECK
+//#if NANCHECK
         Value().HasNan("ClassificationError");
-#endif
+//#endif
 #if DUMPOUTPUT
         Value().Print("ClassificationErrorNode");
 #endif

Source/SGDLib/SGD.cpp

@@ -853,7 +853,7 @@ void SGD<ElemType>::TrainOrAdaptModel(int startEpoch, ComputationNetworkPtr net,
                 // m_modelPath = m_modelPath + L "debug"
                 fprintf(stderr, "Saving model for debugging to:%ls", w.c_str());
                 net->Save(w);
-                RuntimeError("The training is not a number (NAN).");
+                RuntimeError("The2 training is not a number (NAN).");
             }
 
             // not loading previous values then set them
@@ -1560,7 +1560,7 @@ void SGD<ElemType>::TrainOrAdaptModel(int startEpoch, ComputationNetworkPtr net,
                     // m_modelPath = m_modelPath + L "debug"
                     fprintf(stderr, "Saving model for debugging to:%ls", w.c_str());
                     net->Save(w);
-                    RuntimeError("The training is not a number (NAN).");
+                    RuntimeError("The1 training is not a number (NAN).");
                 }
 
                 // reset statistics for differential logging