diff options
Diffstat (limited to 'src/armnn/test/optimizations')
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"); |