From 95807cef855738ca481ace30f32ed9f245a098dd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?=C3=89anna=20=C3=93=20Cath=C3=A1in?= Date: Mon, 12 Nov 2018 17:14:43 +0000 Subject: Tidying up multiple issues * Fixed error in InferOutputShape implementation * Added better error checking to the BatchToSpace implementation. * Added defaults to the batchToSpace descriptors. * Changed crops to be a vector of pairs to align with the SpaceToBatch implementation Change-Id: Ib1c16d871f0898a1caeb6629c1fee6380a773e14 --- include/armnn/Descriptors.hpp | 9 ++++---- src/armnn/layers/BatchToSpaceNdLayer.cpp | 18 +++++++--------- src/backends/backendsCommon/test/LayerTests.cpp | 10 ++++----- .../reference/workloads/BatchToSpaceNd.cpp | 24 ++++++++++------------ .../reference/workloads/BatchToSpaceNd.hpp | 2 +- 5 files changed, 29 insertions(+), 34 deletions(-) diff --git a/include/armnn/Descriptors.hpp b/include/armnn/Descriptors.hpp index bda8cf7396..32ac959808 100644 --- a/include/armnn/Descriptors.hpp +++ b/include/armnn/Descriptors.hpp @@ -299,19 +299,20 @@ struct BatchNormalizationDescriptor struct BatchToSpaceNdDescriptor { BatchToSpaceNdDescriptor() - : m_BlockShape() - , m_Crops() + : m_BlockShape({0, 0}) + , m_Crops({{0, 0}, {0, 0}}) , m_DataLayout(DataLayout::NCHW) {} - BatchToSpaceNdDescriptor(std::vector blockShape, std::vector> crops) + BatchToSpaceNdDescriptor(std::vector blockShape, + std::vector> crops) : m_BlockShape(blockShape) , m_Crops(crops) , m_DataLayout(DataLayout::NCHW) {} std::vector m_BlockShape; - std::vector> m_Crops; + std::vector> m_Crops; DataLayoutIndexed m_DataLayout; }; diff --git a/src/armnn/layers/BatchToSpaceNdLayer.cpp b/src/armnn/layers/BatchToSpaceNdLayer.cpp index 595ce4a7fe..9366a8710b 100644 --- a/src/armnn/layers/BatchToSpaceNdLayer.cpp +++ b/src/armnn/layers/BatchToSpaceNdLayer.cpp @@ -57,23 +57,19 @@ std::vector BatchToSpaceNdLayer::InferOutputShapes(const std::vecto std::vector theBlockShape = m_Param.m_BlockShape; - unsigned int overallSize = inBatchSize; + unsigned int overallSize = inBatchSize * inputShape[dataLayout.GetHeightIndex()] + * inputShape[dataLayout.GetWidthIndex()]; - for (unsigned int i = 0; i < theBlockShape.size(); ++i) - { - overallSize = overallSize * theBlockShape.at(i); - } - - std::vector> crops = m_Param.m_Crops; + std::vector> crops = m_Param.m_Crops; - std::vector yCrops = crops[0]; - std::vector xCrops = crops[1]; + std::pair yCrops = crops[0]; + std::pair xCrops = crops[1]; unsigned int inputHeight = inputShape[dataLayout.GetHeightIndex()]; - unsigned int outputHeight = theBlockShape.at(0) * (inputHeight - (yCrops[0] + yCrops[1])); + unsigned int outputHeight = theBlockShape.at(0) * (inputHeight - (yCrops.first + yCrops.second)); unsigned int inputWidth = inputShape[dataLayout.GetWidthIndex()]; - unsigned int outputWidth = theBlockShape.at(1) * (inputWidth - (xCrops[0] + xCrops[1])); + unsigned int outputWidth = theBlockShape.at(1) * (inputWidth - (xCrops.first + xCrops.second)); unsigned int outputBatchSize = overallSize / (outputHeight * outputWidth); diff --git a/src/backends/backendsCommon/test/LayerTests.cpp b/src/backends/backendsCommon/test/LayerTests.cpp index 4a003036ca..85b3e1b2b7 100755 --- a/src/backends/backendsCommon/test/LayerTests.cpp +++ b/src/backends/backendsCommon/test/LayerTests.cpp @@ -6178,7 +6178,7 @@ LayerTestResult BatchToSpaceNdHelper(armnn::IWorkloadFactory &work const unsigned int *inputShape, const std::vector &inputData, const std::vector &blockShape, - const std::vector> &crops, + const std::vector> &crops, const unsigned int *outputShape, const std::vector &outputData, float scale = 1.0f, @@ -6266,7 +6266,7 @@ LayerTestResult BatchToSpaceNdNhwcFloat32Test1(armnn::IWorkloadFactory }); std::vector blockShape {2, 2}; - std::vector> crops = {{0, 0}, {0, 0}}; + std::vector> crops = {{0, 0}, {0, 0}}; return BatchToSpaceNdHelper(workloadFactory, armnn::DataLayout::NHWC, inputShape, input, blockShape, crops, outputShape, expectedOutput); @@ -6286,7 +6286,7 @@ LayerTestResult BatchToSpaceNdNhwcFloat32Test2(armnn::IWorkloadFactory std::vector expectedOutput({1.0f, 2.0f, 3.0f, 4.0f}); std::vector blockShape({2, 2}); - std::vector> crops = {{0, 0}, {0, 0}}; + std::vector> crops = {{0, 0}, {0, 0}}; return BatchToSpaceNdHelper(workloadFactory, armnn::DataLayout::NHWC, inputShape, input, blockShape, crops, outputShape, expectedOutput); @@ -6302,7 +6302,7 @@ LayerTestResult BatchToSpaceNdNhwcFloat32Test3(armnn::IWorkloadFactory std::vector expectedOutput({ 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f }); std::vector blockShape({2, 2}); - std::vector> crops = {{0, 0}, {0, 0}}; + std::vector> crops = {{0, 0}, {0, 0}}; return BatchToSpaceNdHelper(workloadFactory, armnn::DataLayout::NHWC, inputShape, input, blockShape, crops, outputShape, expectedOutput); @@ -6331,7 +6331,7 @@ LayerTestResult BatchToSpaceNdNchwFloat32Test1(armnn::IWorkloadFactory }); std::vector blockShape({2, 2}); - std::vector> crops = {{0, 0}, {0, 0}}; + std::vector> crops = {{0, 0}, {0, 0}}; return BatchToSpaceNdHelper(workloadFactory, armnn::DataLayout::NCHW, inputShape, input, blockShape, crops, outputShape, expectedOutput); diff --git a/src/backends/reference/workloads/BatchToSpaceNd.cpp b/src/backends/reference/workloads/BatchToSpaceNd.cpp index bedf8418ef..4313085ba5 100644 --- a/src/backends/reference/workloads/BatchToSpaceNd.cpp +++ b/src/backends/reference/workloads/BatchToSpaceNd.cpp @@ -34,23 +34,17 @@ void BatchToSpaceNd(const DataLayoutIndexed& dataLayout, const TensorInfo& inputTensorInfo, const TensorInfo& outputTensorInfo, const std::vector& blockShape, - const std::vector>& cropsData, + const std::vector>& cropsData, const float* inputData, float* outputData) { TensorShape inputShape = inputTensorInfo.GetShape(); - unsigned int inputNumDims = inputShape.GetNumDimensions(); - if (inputNumDims != 4) - { - throw armnn::InvalidArgumentException("Expected Input with 4 Dimensions"); - } + + BOOST_ASSERT_MSG(inputShape.GetNumDimensions() == 4, "Expected Input with 4 Dimensions"); TensorShape outputShape = outputTensorInfo.GetShape(); - unsigned int outputNumDims = outputShape.GetNumDimensions(); - if (outputNumDims != 4) - { - throw armnn::InvalidArgumentException("Expected Output with 4 Dimensions"); - } + + BOOST_ASSERT_MSG(outputShape.GetNumDimensions() == 4, "Expected Output with 4 Dimensions"); const unsigned int inputBatchSize = inputShape[0]; const unsigned int channels = inputShape[dataLayout.GetChannelsIndex()]; @@ -59,11 +53,15 @@ void BatchToSpaceNd(const DataLayoutIndexed& dataLayout, const unsigned int outputHeight = outputShape[dataLayout.GetHeightIndex()]; const unsigned int outputWidth = outputShape[dataLayout.GetWidthIndex()]; + BOOST_ASSERT_MSG(blockShape.size() > 0, "BlockShape must contain 1 or more entries"); + const unsigned int blockShapeHeight = blockShape[0]; const unsigned int blockShapeWidth = blockShape[1]; - const unsigned int cropsTop = cropsData[0][0]; - const unsigned int cropsLeft = cropsData[1][0]; + BOOST_ASSERT_MSG(cropsData.size() > 0, "Crops must contain 1 or more entries"); + + const unsigned int cropsTop = cropsData[0].first; + const unsigned int cropsLeft = cropsData[1].first; for (unsigned int inBatch = 0; inBatch < inputBatchSize; ++inBatch) { diff --git a/src/backends/reference/workloads/BatchToSpaceNd.hpp b/src/backends/reference/workloads/BatchToSpaceNd.hpp index 7923ceadd0..091d092777 100644 --- a/src/backends/reference/workloads/BatchToSpaceNd.hpp +++ b/src/backends/reference/workloads/BatchToSpaceNd.hpp @@ -16,7 +16,7 @@ void BatchToSpaceNd(const DataLayoutIndexed& dataLayout, const TensorInfo& inputTensorInfo, const TensorInfo& outputTensorInfo, const std::vector& blockShape, - const std::vector>& cropsData, + const std::vector>& cropsData, const float* inputData, float* outputData); } // namespace armnn \ No newline at end of file -- cgit v1.2.1