switched to linear neuron (test), bug correct in the DoPredictBatch method

include/AutoencoderModel.txx

@@ -395,9 +395,11 @@ void AutoencoderModel<TInputValue,NeuronType>
 		data = net.encode(data);    
 	}
 	*/
-	data = m_net.evalLayer( m_net.layerMatrices().size()/2 ,data);   // features layer for a network containing the encoder and decoder part
+	data = m_net.evalLayer( m_net.layerMatrices().size()/2-1 ,data);   // features layer for a network containing the encoder and decoder part
+	std::cout << data.element(0) << std::endl;
 	unsigned int id = startIndex;
 	target.SetSize(this->m_Dimension);
+	
 	for(const auto& p : data.elements())
 	{
 		for(unsigned int a = 0; a < this->m_Dimension; ++a){

include/DimensionalityReductionModelFactory.txx

@@ -46,7 +46,7 @@ using TiedAutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTa
 */
 
 template <class TInputValue, class TTargetValue>
-using AutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::TanhNeuron>  ;
+using AutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::LinearNeuron>  ;
 
 
 template <class TInputValue, class TTargetValue>

include/cbLearningApplicationBaseDR.h

@@ -103,7 +103,7 @@ public:
 #ifdef OTB_USE_SHARK
 
 	// typedef shark::Autoencoder< shark::TanhNeuron, shark::LinearNeuron> AutoencoderType;
-	typedef shark::TanhNeuron NeuronType;
+	typedef shark::LinearNeuron NeuronType;
 	typedef otb::AutoencoderModel<InputValueType, NeuronType> AutoencoderModelType;
 	/*
 	// typedef shark::TiedAutoencoder< shark::TanhNeuron, shark::LinearNeuron> TiedAutoencoderType;