diff options
Diffstat (limited to 'src/armnn/test')
| -rw-r--r-- | src/armnn/test/CreateWorkload.hpp | 19 | ||||
| -rw-r--r-- | src/armnn/test/TensorHelpers.hpp | 6 |
2 files changed, 13 insertions, 12 deletions
diff --git a/src/armnn/test/CreateWorkload.hpp b/src/armnn/test/CreateWorkload.hpp index 1a9bd56ac5..b8ba72f271 100644 --- a/src/armnn/test/CreateWorkload.hpp +++ b/src/armnn/test/CreateWorkload.hpp @@ -8,6 +8,7 @@ #include <boost/cast.hpp> +#include <backendsCommon/DataLayoutIndexed.hpp> #include <backendsCommon/WorkloadData.hpp> #include <backendsCommon/WorkloadFactory.hpp> #include <backendsCommon/CpuTensorHandle.hpp> @@ -133,11 +134,11 @@ std::unique_ptr<WorkloadType> CreateArithmeticWorkloadTest(armnn::IWorkloadFacto template <typename BatchNormalizationFloat32Workload, armnn::DataType DataType> std::unique_ptr<BatchNormalizationFloat32Workload> CreateBatchNormalizationWorkloadTest( - armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayoutIndexed dataLayout = DataLayout::NCHW) + armnn::IWorkloadFactory& factory, armnn::Graph& graph, DataLayout dataLayout = DataLayout::NCHW) { TensorShape tensorShape; - switch (dataLayout.GetDataLayout()) + switch (dataLayout) { case DataLayout::NHWC: tensorShape = { 2, 4, 4, 3 }; @@ -184,7 +185,7 @@ std::unique_ptr<BatchNormalizationFloat32Workload> CreateBatchNormalizationWorkl BOOST_TEST((queueDescriptor.m_Variance->GetTensorInfo() == TensorInfo({3}, DataType))); BOOST_TEST((queueDescriptor.m_Gamma->GetTensorInfo() == TensorInfo({3}, DataType))); BOOST_TEST((queueDescriptor.m_Beta->GetTensorInfo() == TensorInfo({3}, DataType))); - BOOST_TEST((queueDescriptor.m_Parameters.m_DataLayout.GetDataLayout() == dataLayout)); + BOOST_TEST((queueDescriptor.m_Parameters.m_DataLayout == dataLayout)); // Returns so we can do extra, backend-specific tests. return workload; @@ -842,13 +843,12 @@ void CreateSplitterMultipleInputsOneOutputWorkloadTest(armnn::IWorkloadFactory& template <typename ResizeBilinearWorkload, armnn::DataType DataType> std::unique_ptr<ResizeBilinearWorkload> CreateResizeBilinearWorkloadTest(armnn::IWorkloadFactory& factory, armnn::Graph& graph, - DataLayoutIndexed dataLayout = - DataLayout::NCHW) + DataLayout dataLayout = DataLayout::NCHW) { TensorShape inputShape; TensorShape outputShape; - switch (dataLayout.GetDataLayout()) { + switch (dataLayout) { case DataLayout::NHWC: inputShape = { 2, 4, 4, 3 }; outputShape = { 2, 2, 2, 3 }; @@ -861,8 +861,9 @@ std::unique_ptr<ResizeBilinearWorkload> CreateResizeBilinearWorkloadTest(armnn:: // Creates the layer we're testing. ResizeBilinearDescriptor resizeDesc; - resizeDesc.m_TargetWidth = outputShape[dataLayout.GetWidthIndex()]; - resizeDesc.m_TargetHeight = outputShape[dataLayout.GetHeightIndex()]; + DataLayoutIndexed dimensionIndices = dataLayout; + resizeDesc.m_TargetWidth = outputShape[dimensionIndices.GetWidthIndex()]; + resizeDesc.m_TargetHeight = outputShape[dimensionIndices.GetHeightIndex()]; resizeDesc.m_DataLayout = dataLayout; Layer* const layer = graph.AddLayer<ResizeBilinearLayer>(resizeDesc, "layer"); @@ -883,7 +884,7 @@ std::unique_ptr<ResizeBilinearWorkload> CreateResizeBilinearWorkloadTest(armnn:: ResizeBilinearQueueDescriptor queueDescriptor = workload->GetData(); BOOST_TEST(queueDescriptor.m_Inputs.size() == 1); BOOST_TEST(queueDescriptor.m_Outputs.size() == 1); - BOOST_TEST((queueDescriptor.m_Parameters.m_DataLayout.GetDataLayout() == dataLayout)); + BOOST_TEST((queueDescriptor.m_Parameters.m_DataLayout == dataLayout)); // Returns so we can do extra, backend-specific tests. return workload; diff --git a/src/armnn/test/TensorHelpers.hpp b/src/armnn/test/TensorHelpers.hpp index 4501c3532c..238232ae96 100644 --- a/src/armnn/test/TensorHelpers.hpp +++ b/src/armnn/test/TensorHelpers.hpp @@ -216,9 +216,9 @@ armnn::TensorInfo GetTensorInfo(unsigned int numberOfBatches, unsigned int numberOfChannels, unsigned int height, unsigned int width, - const armnn::DataLayoutIndexed& dataLayout) + const armnn::DataLayout dataLayout) { - switch (dataLayout.GetDataLayout()) + switch (dataLayout) { case armnn::DataLayout::NCHW: return armnn::TensorInfo({numberOfBatches, numberOfChannels, height, width}, armnn::GetDataType<T>()); @@ -226,6 +226,6 @@ armnn::TensorInfo GetTensorInfo(unsigned int numberOfBatches, return armnn::TensorInfo({numberOfBatches, height, width, numberOfChannels}, armnn::GetDataType<T>()); default: throw armnn::InvalidArgumentException("unknown data layout [" - + std::to_string(static_cast<int>(dataLayout.GetDataLayout())) + "]"); + + std::to_string(static_cast<int>(dataLayout)) + "]"); } } |