diff options
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp | 17 | ||||
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp | 49 |
2 files changed, 22 insertions, 44 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp index 9588f560ef..e21a4b64f8 100644 --- a/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/DepthToSpaceTestImpl.cpp @@ -9,6 +9,7 @@ #include <armnn/ArmNN.hpp> +#include <backendsCommon/test/DataLayoutUtils.hpp> #include <backendsCommon/test/TensorCopyUtils.hpp> #include <backendsCommon/test/WorkloadTestUtils.hpp> @@ -29,22 +30,10 @@ LayerTestResult<T, 4> DepthToSpaceTestImpl( const float qScale = 1.0f, const int32_t qOffset = 0) { - const armnn::PermutationVector permVector{0, 2, 3, 1}; - if (descriptor.m_Parameters.m_DataLayout == armnn::DataLayout::NCHW) { - inputInfo = armnnUtils::Permuted(inputInfo, permVector); - outputInfo = armnnUtils::Permuted(outputInfo, permVector); - - constexpr size_t typeSize = sizeof(float); - - std::vector<float> inputTmp(inputData.size()); - armnnUtils::Permute(inputInfo.GetShape(), permVector, inputData.data(), inputTmp.data(), typeSize); - inputData = inputTmp; - - std::vector<float> outputTmp(expectedOutputData.size()); - armnnUtils::Permute(outputInfo.GetShape(), permVector, expectedOutputData.data(), outputTmp.data(), typeSize); - expectedOutputData = outputTmp; + PermuteTensorNhwcToNchw<float>(inputInfo, inputData); + PermuteTensorNhwcToNchw<float>(outputInfo, expectedOutputData); } if(armnn::IsQuantizedType<T>()) diff --git a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp index 6191adf61f..7391f9c198 100644 --- a/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp +++ b/src/backends/backendsCommon/test/layerTests/TransposeConvolution2dTestImpl.hpp @@ -12,7 +12,7 @@ #include <backendsCommon/CpuTensorHandle.hpp> -#include <backendsCommon/test/CommonTestUtils.hpp> +#include <backendsCommon/test/DataLayoutUtils.hpp> #include <backendsCommon/test/QuantizeHelper.hpp> #include <backendsCommon/test/TensorCopyUtils.hpp> #include <backendsCommon/test/WorkloadTestUtils.hpp> @@ -194,27 +194,16 @@ LayerTestResult<T, 4> TransposeConvolution2dTest( } template<typename T> -void SwizzleData(const armnn::TensorInfo& inputInfo, +void SwizzleData(armnn::TensorInfo& inputInfo, std::vector<T>& inputData, - const armnn::TensorInfo& outputInfo, + armnn::TensorInfo& outputInfo, std::vector<T>& outputData, - const armnn::TensorInfo& weightsInfo, + armnn::TensorInfo& weightsInfo, std::vector<T>& weightsData) { - constexpr size_t dataTypeSize = sizeof(float); - const armnn::PermutationVector nchwToNhwc = { 0, 3, 1, 2 }; - - std::vector<T> tmp(inputData.size()); - armnnUtils::Permute(inputInfo.GetShape(), nchwToNhwc, inputData.data(), tmp.data(), dataTypeSize); - inputData = tmp; - - tmp.resize(weightsData.size()); - armnnUtils::Permute(weightsInfo.GetShape(), nchwToNhwc, weightsData.data(), tmp.data(), dataTypeSize); - weightsData = tmp; - - tmp.resize(outputData.size()); - armnnUtils::Permute(outputInfo.GetShape(), nchwToNhwc, outputData.data(), tmp.data(), dataTypeSize); - outputData = tmp; + PermuteTensorNchwToNhwc<T>(inputInfo, inputData); + PermuteTensorNchwToNhwc<T>(outputInfo, outputData); + PermuteTensorNchwToNhwc<T>(weightsInfo, weightsData); } } // anonymous namespace @@ -240,9 +229,9 @@ LayerTestResult<T, 4> SimpleTransposeConvolution2dTest( constexpr unsigned int wWeights = 3u; constexpr unsigned int hWeights = wWeights; - TensorShape inputShape = MakeTensorShape(batches, channels, hInput, wInput, layout); - TensorShape outputShape = MakeTensorShape(batches, channels, hOutput, wOutput, layout); - TensorShape weightsShape = MakeTensorShape(batches, channels, hWeights, wWeights, layout); + TensorShape inputShape = { batches, channels, hInput, wInput }; + TensorShape outputShape = { batches, channels, hOutput, wOutput }; + TensorShape weightsShape = { batches, channels, hWeights, wWeights }; TensorInfo inputInfo(inputShape, ArmnnType); TensorInfo outputInfo(outputShape, ArmnnType); @@ -327,9 +316,9 @@ LayerTestResult<T, 4> PaddedTransposeConvolution2dTest( constexpr unsigned int wWeights = 3u; constexpr unsigned int hWeights = wWeights; - TensorShape inputShape = MakeTensorShape(batches, channels, hInput, wInput, layout); - TensorShape outputShape = MakeTensorShape(batches, channels, hOutput, wOutput, layout); - TensorShape weightsShape = MakeTensorShape(batches, channels, hWeights, wWeights, layout); + TensorShape inputShape = { batches, channels, hInput, wInput }; + TensorShape outputShape = { batches, channels, hOutput, wOutput }; + TensorShape weightsShape = { batches, channels, hWeights, wWeights }; TensorInfo inputInfo(inputShape, ArmnnType); TensorInfo outputInfo(outputShape, ArmnnType); @@ -416,9 +405,9 @@ LayerTestResult<T, 4> StridedTransposeConvolution2dTest( constexpr unsigned int wWeights = 3u; constexpr unsigned int hWeights = wWeights; - TensorShape inputShape = MakeTensorShape(batches, channels, hInput, wInput, layout); - TensorShape outputShape = MakeTensorShape(batches, channels, hOutput, wOutput, layout); - TensorShape weightsShape = MakeTensorShape(batches, channels, hWeights, wWeights, layout); + TensorShape inputShape = { batches, channels, hInput, wInput }; + TensorShape outputShape = { batches, channels, hOutput, wOutput }; + TensorShape weightsShape = { batches, channels, hWeights, wWeights }; TensorInfo inputInfo(inputShape, ArmnnType); TensorInfo outputInfo(outputShape, ArmnnType); @@ -492,11 +481,11 @@ LayerTestResult<T, 4> MultiChannelTransposeConvolution2dTest( { using namespace armnn; - TensorShape inputShape = MakeTensorShape(1, 1, 2, 2, layout); - TensorShape outputShape = MakeTensorShape(1, 2, 5, 5, layout); + TensorShape inputShape = { 1, 1, 2, 2 }; + TensorShape outputShape = { 1, 2, 5, 5 }; // OIHW for NCHW; OHWI for NHWC - TensorShape weightsShape = MakeTensorShape(2, 1, 3, 3, layout); + TensorShape weightsShape = { 2, 1, 3, 3 }; TensorShape biasesShape = { 2 }; TensorInfo inputInfo(inputShape, ArmnnType); |