Reconstruction Loss.

src/mlpack/methods/ann/loss_functions/reconstruction_loss.hpp

@@ -39,8 +39,14 @@ class ReconstructionLoss
  public:
   /**
    * Create the ReconstructionLoss object.
+   *
+   * @param reduction Specifies the reduction to apply to the output. If false,
+   *                  'mean' reduction is used, where sum of the output will be
+   *                  divided by the number of elements in the output. If true,
+   *                  'sum' reduction is used and the output will be summed. It
+   *                  is set to true by default.
    */
-  ReconstructionLoss();
+  ReconstructionLoss(const bool reduction = true);
 
   /**
    * Computes the reconstruction loss.
@@ -71,6 +77,11 @@ class ReconstructionLoss
   //! Modify the output parameter.
   OutputDataType& OutputParameter() { return outputParameter; }
 
+  //! Get the type of reduction used.
+  bool Reduction() const { return reduction; }
+  //! Modify the type of reduction used.
+  bool& Reduction() { return reduction; }
+
   /**
    * Serialize the layer
    */
@@ -83,6 +94,10 @@ class ReconstructionLoss
 
   //! Locally-stored output parameter object.
   OutputDataType outputParameter;
+
+  //! Boolean value that tells if reduction 
+  //  is 'sum' or 'mean'.
+  bool reduction;
 }; // class ReconstructionLoss
 
 } // namespace ann

src/mlpack/methods/ann/loss_functions/reconstruction_loss_impl.hpp

@@ -23,7 +23,7 @@ ReconstructionLoss<
     InputDataType,
     OutputDataType,
     DistType
->::ReconstructionLoss()
+>::ReconstructionLoss(const bool reduction) : reduction(reduction)
 {
   // Nothing to do here.
 }
@@ -35,7 +35,12 @@ ReconstructionLoss<InputDataType, OutputDataType, DistType>::Forward(
     const PredictionType& prediction, const TargetType& target)
 {
   dist = DistType(prediction);
-  return -dist.LogProbability(target);
+  typename PredictionType::elem_type lossSum = -dist.LogProbability(target);
+
+  if (reduction)
+    return lossSum;
+
+  return lossSum / target.n_elem;
 }
 
 template<typename InputDataType, typename OutputDataType, typename DistType>
@@ -47,15 +52,18 @@ void ReconstructionLoss<InputDataType, OutputDataType, DistType>::Backward(
 {
   dist.LogProbBackward(target, loss);
   loss *= -1;
+
+  if (!reduction)
+    loss = loss / target.n_elem;
 }
 
 template<typename InputDataType, typename OutputDataType, typename DistType>
 template<typename Archive>
 void ReconstructionLoss<InputDataType, OutputDataType, DistType>::serialize(
-    Archive& /* ar */,
+    Archive&  ar,
     const uint32_t /* version */)
 {
-  // Nothing to do here.
+  ar(CEREAL_NVP(reduction));
 }
 
 } // namespace ann