IVGCVSW-5815 Generalise ConstCpuTensorHandle

* Generalises ConstCpuTensorHandle and inherited
  classes by removing 'Cpu' from aliases.
* New renamed classes: ConstTensorHandle, TensorHandle,
  ScopedTensorHandle, PassthroughTensorHandle,
  ConstPassthroughTensorHandle.

Signed-off-by: James Conroy <james.conroy@arm.com>
Change-Id: I1824e0e134202735fb77051f20a7252f161dfe16

5 files changed, 10 insertions, 10 deletions

diff --git a/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp b/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp
index 4523e70437..d0d728bfab 100644
--- a/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp
+++ b/src/armnn/test/optimizations/AddBroadcastReshapeLayerTests.cpp
@@ -299,7 +299,7 @@ BOOST_AUTO_TEST_CASE(ReshapeParentConstLayerTest)
 
     uint8_t tensor[] = { 1, 1, 1, 1, 1 };
 
-    constant->m_LayerOutput = std::make_unique<ScopedCpuTensorHandle>(ConstTensor(info1, &tensor));
+    constant->m_LayerOutput = std::make_unique<ScopedTensorHandle>(ConstTensor(info1, &tensor));
 
     input->GetOutputSlot().SetTensorInfo(info0);
     constant->GetOutputSlot().SetTensorInfo(info1);
@@ -357,7 +357,7 @@ BOOST_AUTO_TEST_CASE(ReshapeParentConstAddLayerMultipleConnectionsTest)
     input->GetOutputSlot().SetTensorInfo(inputInfo);
     constant->GetOutputSlot().SetTensorInfo(constantTermInfo);
     float tensor[] = { 2.0f };
-    constant->m_LayerOutput = std::make_unique<ScopedCpuTensorHandle>(ConstTensor(constantTermInfo, &tensor));
+    constant->m_LayerOutput = std::make_unique<ScopedTensorHandle>(ConstTensor(constantTermInfo, &tensor));
     add1->GetOutputSlot().SetTensorInfo(outputInfo);
 
     input->GetOutputSlot().Connect(add1->GetInputSlot(0));
diff --git a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
index bb8e674b56..e4c1f2f413 100644
--- a/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsBFloatTests.cpp
@@ -38,7 +38,7 @@ BOOST_AUTO_TEST_CASE(ConvertConstantsFloatToBFloatTest)
     input->GetOutputSlot().SetTensorInfo(info);
 
     auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
+    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
     fc->GetOutputSlot().SetTensorInfo(info);
 
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
@@ -94,7 +94,7 @@ BOOST_AUTO_TEST_CASE(ConvertConstantsBFloatToFloatTest)
     input->GetOutputSlot().SetTensorInfo(info);
 
     auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
+    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
     fc->GetOutputSlot().SetTensorInfo(info);
 
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
diff --git a/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp b/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
index 12df462456..1dfe7f431c 100644
--- a/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsFloatToHalfTests.cpp
@@ -31,7 +31,7 @@ BOOST_AUTO_TEST_CASE(ConvertConstantsFloatToHalfTest)
     input->GetOutputSlot().SetTensorInfo(info);
 
     auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
+    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
     fc->GetOutputSlot().SetTensorInfo(info);
 
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
diff --git a/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp b/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
index 7d7c6b2b0a..1ddf5262e8 100644
--- a/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
+++ b/src/armnn/test/optimizations/ConvertConstantsHalfToFloatTests.cpp
@@ -31,7 +31,7 @@ BOOST_AUTO_TEST_CASE(ConvertConstantsHalfToFloatTest)
     input->GetOutputSlot().SetTensorInfo(info);
 
     auto fc      = graph.AddLayer<armnn::FullyConnectedLayer>(armnn::FullyConnectedDescriptor(), "fc");
-    fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
+    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
     fc->GetOutputSlot().SetTensorInfo(info);
 
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
diff --git a/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp b/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
index a65012eef4..f93fa77b0d 100644
--- a/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
+++ b/src/armnn/test/optimizations/Fp32NetworkToBf16ConverterTests.cpp
@@ -72,8 +72,8 @@ BOOST_AUTO_TEST_CASE(Fp32NetworkToBf16OptimizationConv2DTest)
     armnn::Convolution2dDescriptor descriptor;
 
     auto conv = graph.AddLayer<armnn::Convolution2dLayer>(descriptor, "conv2d");
-    conv->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
-    conv->m_Bias = std::make_unique<armnn::ScopedCpuTensorHandle>(bias);
+    conv->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
+    conv->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(bias);
     conv->GetOutputSlot().SetTensorInfo(infoFP32);
 
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");
@@ -142,8 +142,8 @@ BOOST_AUTO_TEST_CASE(Fp32NetworkToBf16OptimizationFullyConnectedTest)
     armnn::FullyConnectedDescriptor descriptor;
 
     auto fc = graph.AddLayer<armnn::FullyConnectedLayer>(descriptor, "fully");
-    fc->m_Weight = std::make_unique<armnn::ScopedCpuTensorHandle>(weights);
-    fc->m_Bias = std::make_unique<armnn::ScopedCpuTensorHandle>(bias);
+    fc->m_Weight = std::make_unique<armnn::ScopedTensorHandle>(weights);
+    fc->m_Bias = std::make_unique<armnn::ScopedTensorHandle>(bias);
     fc->GetOutputSlot().SetTensorInfo(infoFP32);
 
     auto output = graph.AddLayer<armnn::OutputLayer>(1, "output");