diff options
Diffstat (limited to 'src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp | 22 |
1 files changed, 11 insertions, 11 deletions
diff --git a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp index 817cdeed79..0ca4b0a7f9 100644 --- a/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp +++ b/src/backends/backendsCommon/test/LayerReleaseConstantDataTest.cpp @@ -7,7 +7,7 @@ #include <Graph.hpp> -#include <backendsCommon/CpuTensorHandle.hpp> +#include <backendsCommon/TensorHandle.hpp> #include <backendsCommon/WorkloadData.hpp> #include <boost/test/unit_test.hpp> @@ -35,10 +35,10 @@ BOOST_AUTO_TEST_CASE(ReleaseBatchNormalizationLayerConstantDataTest) BatchNormalizationLayer* const layer = graph.AddLayer<BatchNormalizationLayer>(layerDesc, "layer"); armnn::TensorInfo weightInfo({3}, armnn::DataType::Float32); - layer->m_Mean = std::make_unique<ScopedCpuTensorHandle>(weightInfo); - layer->m_Variance = std::make_unique<ScopedCpuTensorHandle>(weightInfo); - layer->m_Beta = std::make_unique<ScopedCpuTensorHandle>(weightInfo); - layer->m_Gamma = std::make_unique<ScopedCpuTensorHandle>(weightInfo); + layer->m_Mean = std::make_unique<ScopedTensorHandle>(weightInfo); + layer->m_Variance = std::make_unique<ScopedTensorHandle>(weightInfo); + layer->m_Beta = std::make_unique<ScopedTensorHandle>(weightInfo); + layer->m_Gamma = std::make_unique<ScopedTensorHandle>(weightInfo); layer->m_Mean->Allocate(); layer->m_Variance->Allocate(); layer->m_Beta->Allocate(); @@ -87,9 +87,9 @@ BOOST_AUTO_TEST_CASE(ReleaseBatchNormalizationLayerConstantDataTest) Convolution2dLayer* const layer = graph.AddLayer<Convolution2dLayer>(layerDesc, "layer"); - layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({2, 3, 5, 3}, + layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({2, 3, 5, 3}, armnn::DataType::Float32)); - layer->m_Bias = std::make_unique<ScopedCpuTensorHandle> + layer->m_Bias = std::make_unique<ScopedTensorHandle> (TensorInfo({2}, GetBiasDataType(armnn::DataType::Float32))); layer->m_Weight->Allocate(); @@ -131,8 +131,8 @@ BOOST_AUTO_TEST_CASE(ReleaseDepthwiseConvolution2dLayerConstantDataTest) DepthwiseConvolution2dLayer* const layer = graph.AddLayer<DepthwiseConvolution2dLayer>(layerDesc, "layer"); - layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({3, 3, 5, 3}, DataType::Float32)); - layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({9}, DataType::Float32)); + layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({3, 3, 5, 3}, DataType::Float32)); + layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({9}, DataType::Float32)); layer->m_Weight->Allocate(); layer->m_Bias->Allocate(); @@ -170,9 +170,9 @@ BOOST_AUTO_TEST_CASE(ReleaseFullyConnectedLayerConstantDataTest) float inputsQScale = 1.0f; float outputQScale = 2.0f; - layer->m_Weight = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({7, 20}, + layer->m_Weight = std::make_unique<ScopedTensorHandle>(TensorInfo({7, 20}, DataType::QAsymmU8, inputsQScale, 0)); - layer->m_Bias = std::make_unique<ScopedCpuTensorHandle>(TensorInfo({7}, + layer->m_Bias = std::make_unique<ScopedTensorHandle>(TensorInfo({7}, GetBiasDataType(DataType::QAsymmU8), inputsQScale)); layer->m_Weight->Allocate(); layer->m_Bias->Allocate(); |