1 files changed, 16 insertions, 10 deletions
diff --git a/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp b/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp
index 44d5035431..fc80f413e8 100644
--- a/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp
+++ b/src/backends/neon/workloads/NeonBatchNormalizationWorkload.cpp
@@ -4,9 +4,13 @@
 //
 
 #include "NeonBatchNormalizationWorkload.hpp"
+
+#include "NeonWorkloadUtils.hpp"
+
 #include <backendsCommon/CpuTensorHandle.hpp>
 #include <aclCommon/ArmComputeTensorUtils.hpp>
-#include <armnn/ArmNN.hpp>
+
+#include <arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h>
 
 namespace armnn
 {
@@ -68,13 +72,15 @@ NeonBatchNormalizationWorkload::NeonBatchNormalizationWorkload(
     m_Beta = std::make_unique<arm_compute::Tensor>();
     BuildArmComputeTensor(*m_Beta, m_Data.m_Beta->GetTensorInfo());
 
-    m_Layer.configure(&input,
-                      &output,
-                      m_Mean.get(),
-                      m_Variance.get(),
-                      m_Beta.get(),
-                      m_Gamma.get(),
-                      m_Data.m_Parameters.m_Eps);
+    auto layer = std::make_unique<arm_compute::NEBatchNormalizationLayer>();
+    layer->configure(&input,
+                     &output,
+                     m_Mean.get(),
+                     m_Variance.get(),
+                     m_Beta.get(),
+                     m_Gamma.get(),
+                     m_Data.m_Parameters.m_Eps);
+    m_Layer.reset(layer.release());
 
     InitializeArmComputeTensorData(*m_Mean, m_Data.m_Mean);
     InitializeArmComputeTensorData(*m_Variance, m_Data.m_Variance);
@@ -83,14 +89,14 @@ NeonBatchNormalizationWorkload::NeonBatchNormalizationWorkload(
 
     // Force Compute Library to perform the necessary copying and reshaping, after which
     // delete all the input tensors that will no longer be needed
-    m_Layer.prepare();
+    m_Layer->prepare();
     FreeUnusedTensors();
 }
 
 void NeonBatchNormalizationWorkload::Execute() const
 {
     ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonBatchNormalizationWorkload_Execute");
-    m_Layer.run();
+    m_Layer->run();
 }
 
 void NeonBatchNormalizationWorkload::FreeUnusedTensors()