diff options
Diffstat (limited to 'src/backends/backendsCommon/test/LayerTests.cpp')
| -rwxr-xr-x | src/backends/backendsCommon/test/LayerTests.cpp | 47 |
1 files changed, 15 insertions, 32 deletions
diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp index ecd09ca024..f10d14e942 100755 --- a/src/backends/backendsCommon/test/LayerTests.cpp +++ b/src/backends/backendsCommon/test/LayerTests.cpp @@ -4,6 +4,7 @@ // #include "LayerTests.hpp" #include "WorkloadTestUtils.hpp" +#include "TensorUtils.hpp" #include "test/TensorHelpers.hpp" #include "TensorCopyUtils.hpp" @@ -68,24 +69,6 @@ static std::vector<float> ConvInput3x8x16({ // 2-channel bias used by a number of Conv2d tests. static std::vector<float> Bias2({0, 2}); -armnn::TensorShape GetTestTensorShape(unsigned int numberOfBatches, - unsigned int numberOfChannels, - unsigned int height, - unsigned int width, - const armnn::DataLayoutIndexed& dataLayout) -{ - switch (dataLayout.GetDataLayout()) - { - case armnn::DataLayout::NCHW: - return armnn::TensorShape({numberOfBatches, numberOfChannels, height, width}); - case armnn::DataLayout::NHWC: - return armnn::TensorShape({numberOfBatches, height, width, numberOfChannels}); - default: - throw armnn::InvalidArgumentException("unknown data layout [" - + std::to_string(static_cast<int>(dataLayout.GetDataLayout())) + "]"); - } -} - // Helper function that returns either Bias2 or an empty vector depending on whether bias is enabled. template<typename T> boost::multi_array<T, 1> GetBias2(bool biasEnabled, float qScale, int32_t qOffset) @@ -3859,8 +3842,8 @@ LayerTestResult<float, 4> ResizeBilinearNopTest( const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, const armnn::DataLayout dataLayout) { - const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 4, 4, dataLayout); - const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 4, 4, dataLayout); + const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); + const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f, @@ -3913,8 +3896,8 @@ LayerTestResult<float, 4> SimpleResizeBilinearTest( const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, const armnn::DataLayout dataLayout) { - const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 2, 2, dataLayout); - const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 1, 1, dataLayout); + const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 2, dataLayout); + const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 1, 1, dataLayout); std::vector<float> inputData({ 1.0f, 255.0f, @@ -3979,8 +3962,8 @@ LayerTestResult<float, 4> ResizeBilinearSqMinTest( const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, const armnn::DataLayout dataLayout) { - const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 4, 4, dataLayout); - const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 2, 2, dataLayout); + const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 4, 4, dataLayout); + const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 2, dataLayout); std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 4.0f, @@ -4045,8 +4028,8 @@ LayerTestResult<float, 4> ResizeBilinearMinTest( const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, const armnn::DataLayout dataLayout) { - const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 3, 5, dataLayout); - const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 2, 3, dataLayout); + const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 5, dataLayout); + const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 2, 3, dataLayout); std::vector<float> inputData({ 1.0f, 2.0f, 3.0f, 5.0f, 8.0f, @@ -4109,8 +4092,8 @@ LayerTestResult<float, 4> ResizeBilinearMagTest( const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, const armnn::DataLayout dataLayout) { - const armnn::TensorInfo inputTensorInfo = GetTensorInfo<float>(1, 2, 3, 2, dataLayout); - const armnn::TensorInfo outputTensorInfo = GetTensorInfo<float>(1, 2, 3, 5, dataLayout); + const armnn::TensorInfo inputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 2, dataLayout); + const armnn::TensorInfo outputTensorInfo = armnnUtils::GetTensorInfo<float>(1, 2, 3, 5, dataLayout); std::vector<float> inputData({ 1.0f, 2.0f, @@ -4741,7 +4724,7 @@ LayerTestResult<float, 4> L2Normalization1dTest( unsigned int width = 1; - const armnn::TensorShape inputOutputShape = GetTestTensorShape( + const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( numberOfBatches, numberOfChannels, height, width, layout); std::vector<float> inputValues { @@ -4810,7 +4793,7 @@ LayerTestResult<float, 4> L2Normalization2dTest( unsigned int height = 1; unsigned int width = 5; - const armnn::TensorShape inputOutputShape = GetTestTensorShape( + const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( numberOfBatches, numberOfChannels, height, width, layout); std::vector<float> inputValues { @@ -4855,7 +4838,7 @@ LayerTestResult<float, 4> L2Normalization3dTest( unsigned int height = 4; unsigned int width = 3; - const armnn::TensorShape inputOutputShape = GetTestTensorShape( + const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( numberOfBatches, numberOfChannels, height, width, layout); std::vector<float> inputValues { @@ -4920,7 +4903,7 @@ LayerTestResult<float, 4> L2Normalization4dTest( unsigned int height = 4; unsigned int width = 3; - const armnn::TensorShape inputOutputShape = GetTestTensorShape( + const armnn::TensorShape inputOutputShape = armnnUtils::GetTensorShape( numberOfBatches, numberOfChannels, height, width, layout); std::vector<float> inputValues { |