diff --git a/src/tensor.cu b/src/tensor.cu
index c5619b99..398b696a 100644
--- a/src/tensor.cu
+++ b/src/tensor.cu
@@ -80,12 +80,12 @@ void Tensor::Load(const std::string &path)
   }
   strm.close();
 
-  Load(hostData);
+  Load(hostData.begin(), hostData.begin());
 }
 
-void Tensor::Load(const std::vector<float> &values)
+void Tensor::Load(const std::vector<float>::const_iterator &begin, const std::vector<float>::const_iterator &end)
 {
-	pimpl_->set(values);
+	pimpl_->set(begin, end);
 }
 
 }
diff --git a/src/tensor.h b/src/tensor.h
index 83965508..d6acea11 100644
--- a/src/tensor.h
+++ b/src/tensor.h
@@ -158,11 +158,11 @@ class TensorImpl {
       thrust::fill(data_.begin(), data_.end(), value);
     }
 
-    void set(const std::vector<Float> &values) {
+    void set(const std::vector<float>::const_iterator &begin, const std::vector<float>::const_iterator &end) {
 	  size_t totSize = GetTotalSize(shape());
-	  std::cerr << "tensor size=" << totSize << " vector size=" << values.size() << std::endl;
-	  assert(totSize == values.size());
-	  thrust::copy(values.begin(), values.end(), data_.begin());
+	  //std::cerr << "tensor size=" << totSize << " vector size=" << values.size() << std::endl;
+	  //assert(totSize == values.size());
+	  thrust::copy(begin, end, data_.begin());
     }
 
     std::string Debug() const
@@ -275,7 +275,7 @@ class Tensor {
     }
 
     void Load(const std::string &path);
-    void Load(const std::vector<float> &values);
+    void Load(const std::vector<float>::const_iterator &begin, const std::vector<float>::const_iterator &end);
 
 };
 
diff --git a/src/test.cu b/src/test.cu
index 777b4b39..a78e182f 100644
--- a/src/test.cu
+++ b/src/test.cu
@@ -12,6 +12,7 @@ int main(int argc, char** argv) {
   using namespace marian;
   using namespace keywords;
   
+  const size_t BATCH_SIZE = 500;
   const size_t IMAGE_SIZE = 784;
   const size_t LABEL_SIZE = 10;
 
@@ -31,41 +32,51 @@ int main(int argc, char** argv) {
   //vector<float> labels = datasets::mnist::ReadLabels("../examples/mnist/t10k-labels-idx1-ubyte", numofdata, LABEL_SIZE);
   vector<float> images = datasets::mnist::ReadImages("../examples/mnist/train-images-idx3-ubyte", numofdata, IMAGE_SIZE);
   vector<float> labels = datasets::mnist::ReadLabels("../examples/mnist/train-labels-idx1-ubyte", numofdata, LABEL_SIZE);
-
-
   cerr << "images=" << images.size() << " labels=" << labels.size() << endl;
   cerr << "numofdata=" << numofdata << endl;
 
-  Tensor tx({numofdata, IMAGE_SIZE}, 1);
-  Tensor ty({numofdata, LABEL_SIZE}, 1);
+  size_t startInd = 0;
+  size_t startIndData = 0;
+  while (startInd < numofdata) {
+	  size_t batchSize = (startInd + BATCH_SIZE < numofdata) ? BATCH_SIZE : numofdata - startInd;
+	  cerr << "startInd=" << startInd
+			  << " startIndData=" << startIndData
+			  << " batchSize=" << batchSize << endl;
 
-  tx.Load(images);
-  ty.Load(labels);
+	  Tensor tx({numofdata, IMAGE_SIZE}, 1);
+	  Tensor ty({numofdata, LABEL_SIZE}, 1);
 
-  //cerr << "tx=" << Debug(tx.shape()) << endl;
-  //cerr << "ty=" << Debug(ty.shape()) << endl;
+	  tx.Load(images.begin() + startIndData, images.begin() + startIndData + batchSize * IMAGE_SIZE);
+	  ty.Load(labels.begin() + startInd, labels.begin() + startInd + batchSize);
 
-  x = tx;
-  y = ty;
+	  //cerr << "tx=" << Debug(tx.shape()) << endl;
+	  //cerr << "ty=" << Debug(ty.shape()) << endl;
 
-  cerr << "x=" << Debug(x.val().shape()) << endl;
-  cerr << "y=" << Debug(y.val().shape()) << endl;
+	  x = tx;
+	  y = ty;
+
+	  cerr << "x=" << Debug(x.val().shape()) << endl;
+	  cerr << "y=" << Debug(y.val().shape()) << endl;
 
 
-  graph.forward(500);
+	  graph.forward(batchSize);
 
-  cerr << "w=" << Debug(w.val().shape()) << endl;
-  cerr << "b=" << Debug(b.val().shape()) << endl;
-  std::cerr << "z: " << Debug(z.val().shape()) << endl;
-  std::cerr << "lr: " << Debug(lr.val().shape()) << endl;
-  std::cerr << "Log-likelihood: " << Debug(graph.val().shape()) << endl ;
+	  cerr << "w=" << Debug(w.val().shape()) << endl;
+	  cerr << "b=" << Debug(b.val().shape()) << endl;
+	  std::cerr << "z: " << Debug(z.val().shape()) << endl;
+	  std::cerr << "lr: " << Debug(lr.val().shape()) << endl;
+	  std::cerr << "Log-likelihood: " << Debug(graph.val().shape()) << endl ;
 
-  //std::cerr << "scores=" << scores.val().Debug() << endl;
-  std::cerr << "lr=" << lr.val().Debug() << endl;
+	  //std::cerr << "scores=" << scores.val().Debug() << endl;
+	  std::cerr << "lr=" << lr.val().Debug() << endl;
 
-  graph.backward();
-  
-  //std::cerr << graph["pred"].val()[0] << std::endl;
+	  graph.backward();
+
+	  //std::cerr << graph["pred"].val()[0] << std::endl;
+
+	  startInd += batchSize;
+	  startIndData += batchSize * IMAGE_SIZE;
+  }
   
 
    // XOR