From c577f2c6a3b4ddb6ba87a882723c53a248afbeba Mon Sep 17 00:00:00 2001 From: telsoa01 Date: Fri, 31 Aug 2018 09:22:23 +0100 Subject: Release 18.08 --- src/armnn/backends/test/WorkloadDataValidation.cpp | 71 ++++++++++++++-------- 1 file changed, 46 insertions(+), 25 deletions(-) (limited to 'src/armnn/backends/test/WorkloadDataValidation.cpp') diff --git a/src/armnn/backends/test/WorkloadDataValidation.cpp b/src/armnn/backends/test/WorkloadDataValidation.cpp index c3a9d40116..bc3898b405 100644 --- a/src/armnn/backends/test/WorkloadDataValidation.cpp +++ b/src/armnn/backends/test/WorkloadDataValidation.cpp @@ -22,7 +22,7 @@ BOOST_AUTO_TEST_CASE(QueueDescriptor_Validate_WrongNumOfInputsOutputs) { InputQueueDescriptor invalidData; WorkloadInfo invalidInfo; - //invalid argument exception is expected, because no inputs and no outputs were defined + //Invalid argument exception is expected, because no inputs and no outputs were defined. BOOST_CHECK_THROW(RefWorkloadFactory().CreateInput(invalidData, invalidInfo), armnn::InvalidArgumentException); } @@ -31,7 +31,7 @@ BOOST_AUTO_TEST_CASE(RefPooling2dFloat32Workload_Validate_WrongDimTensor) armnn::TensorInfo inputTensorInfo; armnn::TensorInfo outputTensorInfo; - unsigned int inputShape[] = {2, 3, 4}; // <- invalid - input tensor has to be 4D + unsigned int inputShape[] = {2, 3, 4}; // <- Invalid - input tensor has to be 4D. unsigned int outputShape[] = {2, 3, 4, 5}; outputTensorInfo = armnn::TensorInfo(4, outputShape, armnn::DataType::Float32); @@ -43,7 +43,7 @@ BOOST_AUTO_TEST_CASE(RefPooling2dFloat32Workload_Validate_WrongDimTensor) AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); - // invalid argument exception is expected, input tensor has to be 4D + // Invalid argument exception is expected, input tensor has to be 4D. BOOST_CHECK_THROW(RefPooling2dFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } @@ -55,7 +55,7 @@ BOOST_AUTO_TEST_CASE(SoftmaxQueueDescriptor_Validate_WrongInputHeight) unsigned int inputNum = 2; unsigned int outputChannels = inputChannels; - unsigned int outputHeight = inputHeight + 1; //makes data invalid - Softmax expects height and width to be 1 + unsigned int outputHeight = inputHeight + 1; //Makes data invalid - Softmax expects height and width to be 1. unsigned int outputWidth = inputWidth; unsigned int outputNum = inputNum; @@ -74,7 +74,7 @@ BOOST_AUTO_TEST_CASE(SoftmaxQueueDescriptor_Validate_WrongInputHeight) AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); - //invalid argument exception is expected, because height != 1 + //Invalid argument exception is expected, because height != 1. BOOST_CHECK_THROW(RefSoftmaxFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } @@ -90,7 +90,7 @@ BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing) unsigned int outputChannels = 3; unsigned int outputNum = 2; - // Define the tensor descriptors + // Define the tensor descriptors. armnn::TensorInfo inputTensorInfo; armnn::TensorInfo outputTensorInfo; armnn::TensorInfo weightsDesc; @@ -120,8 +120,8 @@ BOOST_AUTO_TEST_CASE(FullyConnectedQueueDescriptor_Validate_RequiredDataMissing) invalidData.m_Parameters.m_TransposeWeightMatrix = false; - //invalid argument exception is expected, because not all required fields have been provided - //in particular inputsData[0], outputsData[0] and weightsData can not be null + //Invalid argument exception is expected, because not all required fields have been provided. + //In particular inputsData[0], outputsData[0] and weightsData can not be null. BOOST_CHECK_THROW(RefFullyConnectedFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } @@ -135,8 +135,8 @@ BOOST_AUTO_TEST_CASE(NormalizationQueueDescriptor_Validate_WrongInputHeight) constexpr unsigned int outputNum = inputNum; constexpr unsigned int outputChannels = inputChannels; - constexpr unsigned int outputHeight = inputHeight + 1; //makes data invalid - normalization requires - //input and output to have the same dimensions + constexpr unsigned int outputHeight = inputHeight + 1; //Makes data invalid - normalization requires. + //Input and output to have the same dimensions. constexpr unsigned int outputWidth = inputWidth; @@ -169,7 +169,7 @@ BOOST_AUTO_TEST_CASE(NormalizationQueueDescriptor_Validate_WrongInputHeight) invalidData.m_Parameters.m_Beta = beta; invalidData.m_Parameters.m_K = kappa; - //invalid argument exception is expected, because input height != output height + //Invalid argument exception is expected, because input height != output height. BOOST_CHECK_THROW(RefNormalizationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } @@ -201,7 +201,7 @@ BOOST_AUTO_TEST_CASE(SplitterQueueDescriptor_Validate_WrongWindow) AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); - // invalid since it has only 3 dimensions while the input tensor is 4d + // Invalid, since it has only 3 dimensions while the input tensor is 4d. std::vector wOrigin = {0, 0, 0}; armnn::SplitterQueueDescriptor::ViewOrigin window(wOrigin); invalidData.m_ViewOrigins.push_back(window); @@ -210,7 +210,7 @@ BOOST_AUTO_TEST_CASE(SplitterQueueDescriptor_Validate_WrongWindow) "match input."); BOOST_CHECK_THROW(RefSplitterFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); - // invalid since window extends past the boundary of input tensor + // Invalid, since window extends past the boundary of input tensor. std::vector wOrigin3 = {0, 0, 15, 0}; armnn::SplitterQueueDescriptor::ViewOrigin window3(wOrigin3); invalidData.m_ViewOrigins[0] = window3; @@ -259,7 +259,7 @@ BOOST_AUTO_TEST_CASE(MergerQueueDescriptor_Validate_WrongWindow) AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); - // invalid since it has only 3 dimensions while the input tensor is 4d + // Invalid, since it has only 3 dimensions while the input tensor is 4d. std::vector wOrigin = {0, 0, 0}; armnn::MergerQueueDescriptor::ViewOrigin window(wOrigin); invalidData.m_ViewOrigins.push_back(window); @@ -268,7 +268,7 @@ BOOST_AUTO_TEST_CASE(MergerQueueDescriptor_Validate_WrongWindow) "match input."); BOOST_CHECK_THROW(RefMergerFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); - // invalid since window extends past the boundary of output tensor + // Invalid, since window extends past the boundary of output tensor. std::vector wOrigin3 = {0, 0, 15, 0}; armnn::MergerQueueDescriptor::ViewOrigin window3(wOrigin3); invalidData.m_ViewOrigins[0] = window3; @@ -308,17 +308,17 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputNumbers) AddInputToWorkload(invalidData, invalidInfo, input1TensorInfo, nullptr); AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); - // too few inputs + // Too few inputs. BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr); - // correct + // Correct. BOOST_CHECK_NO_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo)); AddInputToWorkload(invalidData, invalidInfo, input3TensorInfo, nullptr); - // too many inputs + // Too many inputs. BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } @@ -331,7 +331,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes) unsigned int shape1[] = {1, 1, 2, 1}; unsigned int shape2[] = {1, 1, 3, 2}; - // Incompatible shapes even with broadcasting + // Incompatible shapes even with broadcasting. { input1TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); input2TensorInfo = armnn::TensorInfo(4, shape2, armnn::DataType::Float32); @@ -347,7 +347,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes) BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } - // Output size not compatible with input sizes + // Output size not compatible with input sizes. { input1TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); input2TensorInfo = armnn::TensorInfo(4, shape1, armnn::DataType::Float32); @@ -360,7 +360,7 @@ BOOST_AUTO_TEST_CASE(AdditionQueueDescriptor_Validate_InputShapes) AddInputToWorkload(invalidData, invalidInfo, input2TensorInfo, nullptr); AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); - // output differs + // Output differs. BOOST_CHECK_THROW(RefAdditionFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } } @@ -374,7 +374,7 @@ BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimension constexpr unsigned int input0Shape[] = { 2, 2, 4, 4 }; constexpr std::size_t dimensionCount = std::extent::value; - // Check dimension consistency for input tensors + // Checks dimension consistency for input tensors. for (unsigned int dimIndex = 0; dimIndex < dimensionCount; ++dimIndex) { unsigned int input1Shape[dimensionCount]; @@ -399,7 +399,7 @@ BOOST_AUTO_TEST_CASE(MultiplicationQueueDescriptor_Validate_InputTensorDimension BOOST_CHECK_THROW(RefMultiplicationFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } - // Check dimension consistency for input and output tensors + // Checks dimension consistency for input and output tensors. for (unsigned int dimIndex = 0; dimIndex < dimensionCount; ++dimIndex) { unsigned int outputShape[dimensionCount]; @@ -430,7 +430,7 @@ BOOST_AUTO_TEST_CASE(ReshapeQueueDescriptor_Validate_MismatchingNumElements) armnn::TensorInfo inputTensorInfo; armnn::TensorInfo outputTensorInfo; - // The input and output shapes should have the same number of elements, but these don't + // The input and output shapes should have the same number of elements, but these don't. unsigned int inputShape[] = { 1, 1, 2, 3 }; unsigned int outputShape[] = { 1, 1, 1, 2 }; @@ -443,8 +443,29 @@ BOOST_AUTO_TEST_CASE(ReshapeQueueDescriptor_Validate_MismatchingNumElements) AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); - // InvalidArgumentException is expected, because the number of elements don't match + // InvalidArgumentException is expected, because the number of elements don't match. BOOST_CHECK_THROW(RefReshapeFloat32Workload(invalidData, invalidInfo), armnn::InvalidArgumentException); } + +BOOST_AUTO_TEST_CASE(LstmQueueDescriptor_Validate) +{ + armnn::TensorInfo inputTensorInfo; + armnn::TensorInfo outputTensorInfo; + + unsigned int inputShape[] = { 1, 2 }; + unsigned int outputShape[] = { 1 }; + + inputTensorInfo = armnn::TensorInfo(2, inputShape, armnn::DataType::Float32); + outputTensorInfo = armnn::TensorInfo(1, outputShape, armnn::DataType::Float32); + + LstmQueueDescriptor invalidData; + WorkloadInfo invalidInfo; + + AddInputToWorkload(invalidData, invalidInfo, inputTensorInfo, nullptr); + AddOutputToWorkload(invalidData, invalidInfo, outputTensorInfo, nullptr); + + BOOST_CHECK_THROW(invalidData.Validate(invalidInfo), armnn::InvalidArgumentException); +} + BOOST_AUTO_TEST_SUITE_END() -- cgit v1.2.1