diff --git a/src/backends/reference/workloads/Pad.cpp b/src/backends/reference/workloads/Pad.cpp
index 5c85931..a50fa23 100644
--- a/src/backends/reference/workloads/Pad.cpp
+++ b/src/backends/reference/workloads/Pad.cpp
@@ -5,24 +5,22 @@
 
 #include "Pad.hpp"
 #include "backends/WorkloadData.hpp"
-
 #include <boost/numeric/conversion/cast.hpp>
 #include "TensorBufferArrayView.hpp"
-
 #include <cmath>
 #include <cstddef>
 #include <functional>
 #include <limits>
 #include <cassert>
 
-
 namespace armnn
 {
+template <typename T>
 void Pad(const TensorInfo& inputInfo,
          const TensorInfo& outputInfo,
          std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
-         const float* inputData,
-         float* outData)
+         const T* inputData,
+         T* outData)
 {
     unsigned int numOutputElements = outputInfo.GetNumElements();
 
@@ -30,10 +28,12 @@
     TensorShape inputShape = inputInfo.GetShape();
 
     unsigned int numInputDimensions = inputShape.GetNumDimensions();
-    #ifndef NDEBUG
-    unsigned int numOutputDimensions = outputShape.GetNumDimensions();
 
+    #ifndef NDEBUG
+
+    unsigned int numOutputDimensions = outputShape.GetNumDimensions();
     assert(numInputDimensions == numOutputDimensions);
+
     #endif
 
     unsigned int inputBatches = 0;
@@ -51,29 +51,27 @@
     }
 
     switch(numInputDimensions) {
+
         case 1:
 
             inputWidth = inputShape[0];
 
             for (unsigned int w = 0; w < inputWidth ; w++)
             {
-
                 outData[w+std::get<0>(m_PadList[0])] = inputData[w];
-
             }
 
             break;
+
         case 2  :
 
             inputHeight = inputShape[0];
             inputWidth = inputShape[1];
-
             outputHeight = outputShape[0];
             outputWidth = outputShape[1];
 
             for (unsigned int h = 0; h < inputHeight; h++)
             {
-
                 for (unsigned int w = 0; w < inputWidth ; w++)
                 {
                     outData[(h+std::get<0>(m_PadList[0]))*outputWidth
@@ -82,25 +80,22 @@
             }
 
             break;
+
         case 3  :
 
             inputChannels = inputShape[0];
             inputHeight = inputShape[1];
             inputWidth = inputShape[2];
-
             outputChannels = outputShape[0];
             outputHeight = outputShape[1];
             outputWidth = outputShape[2];
 
             for (unsigned int c = 0; c < inputChannels; c++)
             {
-
                 for (unsigned int h = 0; h < inputHeight; h++)
                 {
-
                     for (unsigned int w = 0; w < inputWidth ; w++)
                     {
-
                         outData[(c+std::get<0>(m_PadList[0]))*outputHeight*outputWidth
                         + (h+std::get<0>(m_PadList[1]))*outputWidth
                         + (w+std::get<0>(m_PadList[2]))] = inputData[c * inputHeight * inputWidth
@@ -111,13 +106,13 @@
             }
 
             break;
+
         case 4  :
 
             inputBatches = inputShape[0];
             inputChannels = inputShape[1];
             inputHeight = inputShape[2];
             inputWidth = inputShape[3];
-
             outputChannels = outputShape[1];
             outputHeight = outputShape[2];
             outputWidth = outputShape[3];
@@ -126,13 +121,10 @@
             {
                 for (unsigned int c = 0; c < inputChannels; c++)
                 {
-
                     for (unsigned int h = 0; h < inputHeight; h++)
                     {
-
                         for (unsigned int w = 0; w < inputWidth ; w++)
                         {
-
                             outData[(b+std::get<0>(m_PadList[0])) * outputChannels * outputHeight * outputWidth
                                    + (c+std::get<0>(m_PadList[1])) * outputHeight * outputWidth
                                    + (h+std::get<0>(m_PadList[2])) * outputWidth
@@ -141,7 +133,6 @@
                                                                              + c * inputHeight * inputWidth
                                                                              + h * inputWidth
                                                                              + w];
-
                         }
                     }
                 }
@@ -150,9 +141,20 @@
             break;
 
         default :
+
             break;
     }
-
 }
 
-} //namespace armnn
+template void Pad<float>(const TensorInfo& inputInfo,
+                         const TensorInfo& outputInfo,
+                         std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
+                         const float* inputData,
+                         float* outData);
+template void Pad<uint8_t>(const TensorInfo& inputInfo,
+                           const TensorInfo& outputInfo,
+                           std::vector<std::pair<unsigned int, unsigned int>> m_PadList,
+                           const uint8_t* inputData,
+                           uint8_t* outData);
+
+} //namespace armnn
\ No newline at end of file