4 files changed, 14 insertions, 14 deletions
diff --git a/src/armnn/optimizations/AddBroadcastReshapeLayer.hpp b/src/armnn/optimizations/AddBroadcastReshapeLayer.hpp
index aa00b9913c..4cfe2e4898 100644
--- a/src/armnn/optimizations/AddBroadcastReshapeLayer.hpp
+++ b/src/armnn/optimizations/AddBroadcastReshapeLayer.hpp
@@ -8,7 +8,7 @@
 
 #include <armnn/utility/IgnoreUnused.hpp>
 #include <armnn/utility/PolymorphicDowncast.hpp>
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
 
 namespace armnn
 {
@@ -70,7 +70,7 @@ public:
             {
                 ConstantLayer& constantLayer = static_cast<ConstantLayer&>(parentLayer);
 
-                constantLayer.m_LayerOutput = std::make_unique<ScopedCpuTensorHandle>(
+                constantLayer.m_LayerOutput = std::make_unique<ScopedTensorHandle>(
                     ConstTensor(reshapeInfo, constantLayer.m_LayerOutput.get()->GetConstTensor<void>()));
                 constantLayer.GetOutputSlot().SetTensorInfo(reshapeInfo);
             }
diff --git a/src/armnn/optimizations/ConvertConstants.hpp b/src/armnn/optimizations/ConvertConstants.hpp
index df5a5b4f67..66b3d2685a 100644
--- a/src/armnn/optimizations/ConvertConstants.hpp
+++ b/src/armnn/optimizations/ConvertConstants.hpp
@@ -9,7 +9,7 @@
 
 #include <armnnUtils/FloatingPointConverter.hpp>
 
-#include <backendsCommon/CpuTensorHandle.hpp>
+#include <backendsCommon/TensorHandle.hpp>
 
 #include <armnn/utility/IgnoreUnused.hpp>
 
@@ -23,7 +23,7 @@ namespace optimizations
 
 struct BFloat16ToFloat32
 {
-    static void Func(std::shared_ptr<ConstCpuTensorHandle>& handle)
+    static void Func(std::shared_ptr<ConstTensorHandle>& handle)
     {
         const TensorInfo& info = handle->GetTensorInfo();
 
@@ -37,14 +37,14 @@ struct BFloat16ToFloat32
 
             TensorInfo newInfo(info.GetShape(), DataType::Float32);
             ConstTensor newInput(newInfo, newValues);
-            handle.reset(new ScopedCpuTensorHandle(newInput));
+            handle.reset(new ScopedTensorHandle(newInput));
         }
     }
 };
 
 struct Float16ToFloat32
 {
-    static void Func(std::shared_ptr<ConstCpuTensorHandle>& handle)
+    static void Func(std::shared_ptr<ConstTensorHandle>& handle)
     {
         const TensorInfo& info = handle->GetTensorInfo();
 
@@ -58,14 +58,14 @@ struct Float16ToFloat32
 
             TensorInfo newInfo(info.GetShape(), DataType::Float32);
             ConstTensor newInput(newInfo, newValues);
-            handle.reset(new ScopedCpuTensorHandle(newInput));
+            handle.reset(new ScopedTensorHandle(newInput));
         }
     }
 };
 
 struct Float32ToBFloat16
 {
-    static void Func(std::shared_ptr<ConstCpuTensorHandle>& handle)
+    static void Func(std::shared_ptr<ConstTensorHandle>& handle)
     {
         const TensorInfo& info = handle->GetTensorInfo();
 
@@ -79,14 +79,14 @@ struct Float32ToBFloat16
 
             TensorInfo newInfo(info.GetShape(), DataType::BFloat16);
             ConstTensor newInput(newInfo, newValues);
-            handle.reset(new ScopedCpuTensorHandle(newInput));
+            handle.reset(new ScopedTensorHandle(newInput));
         }
     }
 };
 
 struct Float32ToFloat16
 {
-    static void Func(std::shared_ptr<ConstCpuTensorHandle>& handle)
+    static void Func(std::shared_ptr<ConstTensorHandle>& handle)
     {
         const TensorInfo& info = handle->GetTensorInfo();
 
@@ -100,7 +100,7 @@ struct Float32ToFloat16
 
             TensorInfo newInfo(info.GetShape(), DataType::Float16);
             ConstTensor newInput(newInfo, newValues);
-            handle.reset(new ScopedCpuTensorHandle(newInput));
+            handle.reset(new ScopedTensorHandle(newInput));
         }
     }
 };
diff --git a/src/armnn/optimizations/ConvertFp32NetworkToBf16.hpp b/src/armnn/optimizations/ConvertFp32NetworkToBf16.hpp
index a0856a485b..6c80e740be 100644
--- a/src/armnn/optimizations/ConvertFp32NetworkToBf16.hpp
+++ b/src/armnn/optimizations/ConvertFp32NetworkToBf16.hpp
@@ -35,7 +35,7 @@ inline LayerT* ConvertWeight(Layer* l)
             TensorInfo newInfo(info);
             newInfo.SetDataType(DataType::BFloat16);
             ConstTensor newInput(newInfo, newValues);
-            layer->m_Weight.reset(new ScopedCpuTensorHandle(newInput));
+            layer->m_Weight.reset(new ScopedTensorHandle(newInput));
         }
     }
     return layer;
diff --git a/src/armnn/optimizations/FuseBatchNorm.hpp b/src/armnn/optimizations/FuseBatchNorm.hpp
index 9d25379930..3fb4b34d28 100644
--- a/src/armnn/optimizations/FuseBatchNorm.hpp
+++ b/src/armnn/optimizations/FuseBatchNorm.hpp
@@ -162,8 +162,8 @@ public:
             auto& newConv2dLayer = *graph.InsertNewLayer<ConvLayer>(base.GetInputSlot(0),
                                                                     convDescriptor,
                                                                     name.c_str());
-            newConv2dLayer.m_Weight = std::make_unique<ScopedCpuTensorHandle>(fusedWeightsTensor);
-            newConv2dLayer.m_Bias = std::make_unique<ScopedCpuTensorHandle>(ConstTensor(fusedBiasTensor));
+            newConv2dLayer.m_Weight = std::make_unique<ScopedTensorHandle>(fusedWeightsTensor);
+            newConv2dLayer.m_Bias = std::make_unique<ScopedTensorHandle>(ConstTensor(fusedBiasTensor));
 
             // Reconnects with original parent.
             newConv2dLayer.GetOutputSlot().MoveAllConnections(*parentOut);