First commit

1 files changed, 87 insertions, 0 deletions

diff --git a/src/CuTNetLib/cuObjectiveFunction.cc b/src/CuTNetLib/cuObjectiveFunction.cc
new file mode 100644
index 0000000..e2b0a1d
--- /dev/null
+++ b/src/CuTNetLib/cuObjectiveFunction.cc
@@ -0,0 +1,87 @@
+
+#include "cuObjectiveFunction.h"
+
+#include "Error.h"
+#include "cumath.h"
+
+
+namespace TNet
+{
+
+
+
+  CuObjectiveFunction*
+  CuObjectiveFunction::
+  Factory(ObjFunType type) {
+    CuObjectiveFunction* ret = NULL;
+    switch(type) {
+      case MEAN_SQUARE_ERROR:  ret = new CuMeanSquareError;  break;
+      case CROSS_ENTROPY:      ret = new CuCrossEntropy;     break;
+      default: Error("Unknown ObjFun type");
+    }
+    return ret;
+  }
+
+
+  void 
+  CuMeanSquareError::
+  Evaluate(const CuMatrix<BaseFloat>& rNetOutput, const CuMatrix<BaseFloat>& rDesired, CuMatrix<BaseFloat>& rNetError)
+  {
+    //get the global error
+    rNetError.CopyFrom(rNetOutput);
+    rNetError.AddScaled(-1.0,rDesired,1.0);
+
+    //calculate the MSE
+    mAuxMat.CopyFrom(rNetError);
+    mAuxMat.MulElem(mAuxMat);
+    
+    mAuxVec.Init(mAuxMat.Cols());
+    mAuxVec.AddColSum(1.0,mAuxMat,0.0);
+    mAuxVec.CopyTo(mAuxVecHost);
+
+    mError += mAuxVecHost.Sum();
+ 
+    //count the frames    
+    mFrames += rNetError.Rows();
+  }
+
+  void 
+  CuCrossEntropy::
+  Evaluate(const CuMatrix<BaseFloat>& rNetOutput, const CuMatrix<BaseFloat>& rDesired, CuMatrix<BaseFloat>& rNetError)
+  {
+    if(rDesired.Cols() != rNetOutput.Cols()) {
+      std::ostringstream os;
+      os << "Non-matching dimensions of network output with training targets!!!"
+         << " Netoutput:" << rNetOutput.Cols()
+         << " Targets:" << rDesired.Cols();
+      Error(os.str());
+    }
+
+    //get the global error
+    //dXent/dSoftmax_in = y-d
+    rNetError.CopyFrom(rNetOutput);
+    rNetError.AddScaled(-1.0,rDesired,1.0);
+   
+    //check classification
+    mClassifyVec.Init(rNetOutput.Rows());
+    CuMath<BaseFloat>::CheckClass(rNetOutput,rDesired,mClassifyVec);
+    mClassifyVec.CopyTo(mClassifyVecHost);
+    mCorrect += mClassifyVecHost.Sum();
+
+    //calculate Xent
+    mAuxMat.CopyFrom(rNetOutput);
+    mAuxMat.LogElem();
+    mAuxMat.MulElem(rDesired);
+
+    mAuxVec.Init(mAuxMat.Cols());
+    mAuxVec.AddColSum(-1.0,mAuxMat,0.0);
+    mAuxVec.CopyTo(mAuxVecHost);
+
+    mError += mAuxVecHost.Sum();
+
+    //count the frames    
+    mFrames += rNetError.Rows();
+  }
+
+
+} // namespace TNet