diff --git a/source/Layer.hpp b/source/Layer.hpp
index 9e6243c..a5998dc 100644
--- a/source/Layer.hpp
+++ b/source/Layer.hpp
@@ -37,8 +37,24 @@ public:
 	void train(arma::mat const &batch, IListener *pListener=nullptr)
 	{
 		if (batch.n_rows > 0)
-		{
-			Rbm::train(trainingData(batch), pListener);
+		{	
+			if (numContext())
+			{
+				arma::mat c_states = arma::zeros(batch.n_rows, numContext());
+				arma::mat ctx = arma::zeros(1, numContext());
+				for (int i=1; i < batch.n_rows; i++)
+				{
+					arma::mat h = prob(v_to_h(arma::join_rows(batch.row(i-1), ctx)));
+					ctx = h;
+					c_states.row(i) = ctx;
+				}
+				arma::mat batch_with_ctx = arma::join_rows(batch, c_states);
+				Rbm::train(trainingData(batch_with_ctx), pListener);
+			}
+			else
+			{
+				Rbm::train(trainingData(batch), pListener);
+			}
 		}
 	}
 	
diff --git a/source/Rbm.cpp b/source/Rbm.cpp
index 87a8ee8..948ea15 100644
--- a/source/Rbm.cpp
+++ b/source/Rbm.cpp
@@ -147,30 +147,13 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
 	while (trainingSizeRemain && !shouldAbort)
 	{
 		int miniBatchSizeActual = std::min(m_params.miniBatchSize, trainingSizeRemain);
-		arma::mat miniBatch_v = batch.rows(batchRowIndex, batchRowIndex+miniBatchSizeActual-1);
+		arma::mat miniBatch = batch.rows(batchRowIndex, batchRowIndex+miniBatchSizeActual-1);
 		trainingSizeRemain -= miniBatchSizeActual;
 		batchRowIndex += miniBatchSizeActual;
 		int scaler = std::min(m_params.miniBatchSize, (int)batch.n_rows);
 		double learning_rate = m_params.learningRate/scaler;
 		double weight_decay = m_params.weightDecay/scaler;
 
-		arma::mat miniBatch;
-		if (numContext() > 0)
-		{
-			arma::mat c_states(arma::zeros(miniBatchSizeActual, numContext()));
-
-			for (int i=1; i < miniBatchSizeActual; i++)
-			{
-				arma::mat h = prob(v_to_h(arma::join_rows(miniBatch_v.row(i-1), ctx)));
-				ctx = h;
-				c_states.row(i) = ctx;
-			}
-			miniBatch = (arma::join_rows(miniBatch_v, c_states));
-		}
-		else
-		{
-			miniBatch = miniBatch_v;
-		}
 		arma::mat v_states(miniBatch);
 
 		// Create hidden layer base on training data
@@ -221,7 +204,6 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
 			
 	} // number of mini batches
 
-#if FIXED_BATCH
 	arma::mat diffErr = batch - prob(h_to_v(prob(v_to_h(batch))));
 	arma::mat diffErr_squared = diffErr % diffErr;
 	status.err_total = accu(diffErr_squared)/diffErr_squared.n_elem;
@@ -230,7 +212,6 @@ void Rbm::train(const arma::mat& batch, IListener* pListener)
 	{
 		pListener->onProgress(this, status);
 	}
-#endif
 }
 
 arma::mat Rbm::prob(const arma::mat &src)
diff --git a/source/Rbm.hpp b/source/Rbm.hpp
index c7cc168..c5389b7 100644
--- a/source/Rbm.hpp
+++ b/source/Rbm.hpp
@@ -144,7 +144,7 @@ public:
      
 	arma::mat toHiddenProbs(const arma::mat &visible) const
 	{
-		return Rbm::prob(v_to_h(arma::join_rows(visible, m_ctx)));
+		return Rbm::prob(v_to_h(visible));
 	}
 
 	arma::mat toVisibleProbs(const arma::mat &hidden) const