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Diffstat (limited to 'src/backends/test/CreateWorkloadCl.cpp')
| -rw-r--r-- | src/backends/test/CreateWorkloadCl.cpp | 676 |
1 files changed, 0 insertions, 676 deletions
diff --git a/src/backends/test/CreateWorkloadCl.cpp b/src/backends/test/CreateWorkloadCl.cpp deleted file mode 100644 index d56bad2bb9..0000000000 --- a/src/backends/test/CreateWorkloadCl.cpp +++ /dev/null @@ -1,676 +0,0 @@ -// -// Copyright © 2017 Arm Ltd. All rights reserved. -// SPDX-License-Identifier: MIT -// -#include <backends/cl/ClWorkloadFactory.hpp> -#include <backends/reference/RefWorkloadFactory.hpp> -#include <backends/MemCopyWorkload.hpp> -#include <backends/cl/workloads/ClWorkloadUtils.hpp> -#include <backends/cl/workloads/ClWorkloads.hpp> -#include <backends/cl/ClTensorHandle.hpp> -#include "ClContextControlFixture.hpp" - -#include <test/CreateWorkloadClNeon.hpp> - -boost::test_tools::predicate_result CompareIClTensorHandleShape(IClTensorHandle* tensorHandle, - std::initializer_list<unsigned int> expectedDimensions) -{ - return CompareTensorHandleShape<IClTensorHandle>(tensorHandle, expectedDimensions); -} - -BOOST_FIXTURE_TEST_SUITE(CreateWorkloadCl, ClContextControlFixture) - -template <typename ActivationWorkloadType, armnn::DataType DataType> -static void ClCreateActivationWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateActivationWorkloadTest<ActivationWorkloadType, DataType>(factory, graph); - - // Checks that inputs/outputs are as we expect them (see definition of CreateActivationWorkloadTest). - ActivationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {1})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {1})); -} - -BOOST_AUTO_TEST_CASE(CreateActivationFloatWorkload) -{ - ClCreateActivationWorkloadTest<ClActivationFloatWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateActivationFloat16Workload) -{ - ClCreateActivationWorkloadTest<ClActivationFloatWorkload, armnn::DataType::Float16>(); -} - -template <typename WorkloadType, - typename DescriptorType, - typename LayerType, - armnn::DataType DataType> -static void ClCreateArithmethicWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = CreateArithmeticWorkloadTest<WorkloadType, DescriptorType, LayerType, DataType>(factory, graph); - - // Checks that inputs/outputs are as we expect them (see definition of CreateArithmeticWorkloadTest). - DescriptorType queueDescriptor = workload->GetData(); - auto inputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto inputHandle2 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[1]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle1, {2, 3})); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle2, {2, 3})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {2, 3})); -} - -BOOST_AUTO_TEST_CASE(CreateAdditionFloatWorkload) -{ - ClCreateArithmethicWorkloadTest<ClAdditionWorkload, - AdditionQueueDescriptor, - AdditionLayer, - armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateAdditionFloat16Workload) -{ - ClCreateArithmethicWorkloadTest<ClAdditionWorkload, - AdditionQueueDescriptor, - AdditionLayer, - armnn::DataType::Float16>(); -} - -BOOST_AUTO_TEST_CASE(CreateSubtractionFloatWorkload) -{ - ClCreateArithmethicWorkloadTest<ClSubtractionWorkload, - SubtractionQueueDescriptor, - SubtractionLayer, - armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateSubtractionFloat16Workload) -{ - ClCreateArithmethicWorkloadTest<ClSubtractionWorkload, - SubtractionQueueDescriptor, - SubtractionLayer, - armnn::DataType::Float16>(); -} - -BOOST_AUTO_TEST_CASE(CreateMultiplicationFloatWorkloadTest) -{ - ClCreateArithmethicWorkloadTest<ClMultiplicationWorkload, - MultiplicationQueueDescriptor, - MultiplicationLayer, - armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateMultiplicationFloat16WorkloadTest) -{ - ClCreateArithmethicWorkloadTest<ClMultiplicationWorkload, - MultiplicationQueueDescriptor, - MultiplicationLayer, - armnn::DataType::Float16>(); -} - -BOOST_AUTO_TEST_CASE(CreateMultiplicationUint8WorkloadTest) -{ - ClCreateArithmethicWorkloadTest<ClMultiplicationWorkload, - MultiplicationQueueDescriptor, - MultiplicationLayer, - armnn::DataType::QuantisedAsymm8>(); -} - -BOOST_AUTO_TEST_CASE(CreateDivisionFloatWorkloadTest) -{ - ClCreateArithmethicWorkloadTest<ClDivisionFloatWorkload, - DivisionQueueDescriptor, - DivisionLayer, - armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateDivisionFloat16WorkloadTest) -{ - ClCreateArithmethicWorkloadTest<ClDivisionFloatWorkload, - DivisionQueueDescriptor, - DivisionLayer, - armnn::DataType::Float16>(); -} - -template <typename BatchNormalizationWorkloadType, armnn::DataType DataType> -static void ClCreateBatchNormalizationWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateBatchNormalizationWorkloadTest<BatchNormalizationWorkloadType, DataType> - (factory, graph); - - // Checks that inputs/outputs are as we expect them (see definition of CreateBatchNormalizationWorkloadTest). - BatchNormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {2, 3, 1, 1})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {2, 3, 1, 1})); -} - -BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloatWorkload) -{ - ClCreateBatchNormalizationWorkloadTest<ClBatchNormalizationFloatWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateBatchNormalizationFloat16Workload) -{ - ClCreateBatchNormalizationWorkloadTest<ClBatchNormalizationFloatWorkload, armnn::DataType::Float16>(); -} - -BOOST_AUTO_TEST_CASE(CreateConvertFp16ToFp32Workload) -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = CreateConvertFp16ToFp32WorkloadTest<ClConvertFp16ToFp32Workload>(factory, graph); - - ConvertFp16ToFp32QueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {3, 2, 3})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {3, 2, 3})); - BOOST_TEST((inputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F16)); - BOOST_TEST((outputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F32)); -} - -BOOST_AUTO_TEST_CASE(CreateConvertFp32ToFp16Workload) -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = CreateConvertFp32ToFp16WorkloadTest<ClConvertFp32ToFp16Workload>(factory, graph); - - ConvertFp32ToFp16QueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {3, 2, 3})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {3, 2, 3})); - BOOST_TEST((inputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F32)); - BOOST_TEST((outputHandle->GetTensor().info()->data_type() == arm_compute::DataType::F16)); -} - -template <typename Convolution2dWorkloadType, typename armnn::DataType DataType> -static void ClConvolution2dWorkloadTest(DataLayout dataLayout) -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = CreateConvolution2dWorkloadTest<ClConvolution2dWorkload, DataType>(factory, - graph, - dataLayout); - - std::initializer_list<unsigned int> inputShape = (dataLayout == DataLayout::NCHW) ? - std::initializer_list<unsigned int>({2, 3, 8, 16}) : std::initializer_list<unsigned int>({2, 8, 16, 3}); - std::initializer_list<unsigned int> outputShape = (dataLayout == DataLayout::NCHW) ? - std::initializer_list<unsigned int>({2, 2, 2, 10}) : std::initializer_list<unsigned int>({2, 2, 10, 2}); - - // Checks that outputs and inputs are as we expect them (see definition of CreateConvolution2dWorkloadTest). - Convolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, inputShape)); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, outputShape)); -} - -BOOST_AUTO_TEST_CASE(CreateConvolution2dFloatNchwWorkload) -{ - ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float32>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateConvolution2dFloatNhwcWorkload) -{ - ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float32>(DataLayout::NHWC); -} - -BOOST_AUTO_TEST_CASE(CreateConvolution2dFloat16NchwWorkload) -{ - ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float16>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateConvolution2dFloat16NhwcWorkload) -{ - ClConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float16>(DataLayout::NHWC); -} - -template <typename Convolution2dWorkloadType, typename armnn::DataType DataType> -static void ClDirectConvolution2dWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = CreateDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, DataType>(factory, graph); - - // Checks that outputs and inputs are as we expect them (see definition of CreateDirectConvolution2dWorkloadTest). - Convolution2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {2, 3, 6, 6})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {2, 2, 6, 6})); -} - -BOOST_AUTO_TEST_CASE(CreateDirectConvolution2dFloatWorkload) -{ - ClDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateDirectConvolution2dFloat16Workload) -{ - ClDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::Float16>(); -} - -BOOST_AUTO_TEST_CASE(CreateDirectConvolution2dUint8Workload) -{ - ClDirectConvolution2dWorkloadTest<ClConvolution2dWorkload, armnn::DataType::QuantisedAsymm8>(); -} - -template <typename FullyConnectedWorkloadType, typename armnn::DataType DataType> -static void ClCreateFullyConnectedWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = - CreateFullyConnectedWorkloadTest<FullyConnectedWorkloadType, DataType>(factory, graph); - - // Checks that outputs and inputs are as we expect them (see definition of CreateFullyConnectedWorkloadTest). - FullyConnectedQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {3, 1, 4, 5})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {3, 7})); -} - - -BOOST_AUTO_TEST_CASE(CreateFullyConnectedFloatWorkloadTest) -{ - ClCreateFullyConnectedWorkloadTest<ClFullyConnectedWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateFullyConnectedFloat16WorkloadTest) -{ - ClCreateFullyConnectedWorkloadTest<ClFullyConnectedWorkload, armnn::DataType::Float16>(); -} - -template <typename NormalizationWorkloadType, typename armnn::DataType DataType> -static void ClNormalizationWorkloadTest(DataLayout dataLayout) -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateNormalizationWorkloadTest<NormalizationWorkloadType, DataType> - (factory, graph, dataLayout); - - // Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest). - NormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {3, 5, 5, 1})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {3, 5, 5, 1})); -} - -BOOST_AUTO_TEST_CASE(CreateNormalizationFloat32NchwWorkload) -{ - ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateNormalizationFloat16NchwWorkload) -{ - ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateNormalizationFloat32NhwcWorkload) -{ - ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NHWC); -} - -BOOST_AUTO_TEST_CASE(CreateNormalizationFloat16NhwcWorkload) -{ - ClNormalizationWorkloadTest<ClNormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NHWC); -} - -template <typename Pooling2dWorkloadType, typename armnn::DataType DataType> -static void ClPooling2dWorkloadTest(DataLayout dataLayout) -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreatePooling2dWorkloadTest<Pooling2dWorkloadType, DataType>(factory, graph, dataLayout); - - std::initializer_list<unsigned int> inputShape = (dataLayout == DataLayout::NCHW) ? - std::initializer_list<unsigned int>({3, 2, 5, 5}) : std::initializer_list<unsigned int>({3, 5, 5, 2}); - std::initializer_list<unsigned int> outputShape = (dataLayout == DataLayout::NCHW) ? - std::initializer_list<unsigned int>({3, 2, 2, 4}) : std::initializer_list<unsigned int>({3, 2, 4, 2}); - - // Check that inputs/outputs are as we expect them (see definition of CreatePooling2dWorkloadTest). - Pooling2dQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, inputShape)); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, outputShape)); -} - -BOOST_AUTO_TEST_CASE(CreatePooling2dFloatNchwWorkload) -{ - ClPooling2dWorkloadTest<ClPooling2dFloatWorkload, armnn::DataType::Float32>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreatePooling2dFloatNhwcWorkload) -{ - ClPooling2dWorkloadTest<ClPooling2dFloatWorkload, armnn::DataType::Float32>(DataLayout::NHWC); -} - -BOOST_AUTO_TEST_CASE(CreatePooling2dFloat16NchwWorkload) -{ - ClPooling2dWorkloadTest<ClPooling2dFloatWorkload, armnn::DataType::Float16>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreatePooling2dFloat16NhwcWorkload) -{ - ClPooling2dWorkloadTest<ClPooling2dFloatWorkload, armnn::DataType::Float16>(DataLayout::NHWC); -} - -template <typename ReshapeWorkloadType, typename armnn::DataType DataType> -static void ClCreateReshapeWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateReshapeWorkloadTest<ReshapeWorkloadType, DataType>(factory, graph); - - // Checks that outputs and inputs are as we expect them (see definition of CreateReshapeWorkloadTest). - ReshapeQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {4, 1})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {4})); // Leading size 1 dimensions are collapsed by ACL. -} - -BOOST_AUTO_TEST_CASE(CreateReshapeFloatWorkload) -{ - ClCreateReshapeWorkloadTest<ClReshapeFloatWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateReshapeFloat16Workload) -{ - ClCreateReshapeWorkloadTest<ClReshapeFloatWorkload, armnn::DataType::Float16>(); -} - -BOOST_AUTO_TEST_CASE(CreateReshapeUint8Workload) -{ - ClCreateReshapeWorkloadTest<ClReshapeUint8Workload, armnn::DataType::QuantisedAsymm8>(); -} - -template <typename SoftmaxWorkloadType, typename armnn::DataType DataType> -static void ClSoftmaxWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateSoftmaxWorkloadTest<SoftmaxWorkloadType, DataType>(factory, graph); - - // Checks that inputs/outputs are as we expect them (see definition of ClSoftmaxFloatWorkload). - SoftmaxQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {4, 1})); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, {4, 1})); -} - - -BOOST_AUTO_TEST_CASE(CreateSoftmaxFloatWorkloadTest) -{ - ClSoftmaxWorkloadTest<ClSoftmaxFloatWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateSoftmaxFloat16WorkloadTest) -{ - ClSoftmaxWorkloadTest<ClSoftmaxFloatWorkload, armnn::DataType::Float16>(); -} - -template <typename armnn::DataType DataType> -static void ClSplitterWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateSplitterWorkloadTest<ClSplitterWorkload, DataType>(factory, graph); - - // Checks that outputs are as we expect them (see definition of CreateSplitterWorkloadTest). - SplitterQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, {5, 7, 7})); - - auto outputHandle1 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle1, {2, 7, 7})); - - auto outputHandle2 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[2]); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle2, {2, 7, 7})); - - auto outputHandle0 = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - // NOTE: At the moment the CL collapses the tensor to a 2 dim when dimension zero = 1 - // we are raising this difference between the NEON and CL libs as an issue with the compute library team. - BOOST_TEST(CompareIClTensorHandleShape(outputHandle0, {7, 7})); -} - -BOOST_AUTO_TEST_CASE(CreateSplitterFloatWorkload) -{ - ClSplitterWorkloadTest<armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateSplitterFloat16Workload) -{ - ClSplitterWorkloadTest<armnn::DataType::Float16>(); -} - -template <typename MergerWorkloadType, typename armnn::DataType DataType> -static void ClSplitterMergerTest() -{ - // Tests that it is possible to decide which output of the splitter layer - // should be lined to which input of the merger layer. - // We test that is is possible to specify 0th output - // of the splitter to be the 1st input to the merger and the 1st output of the splitter to be 0th input - // of the merger. - - Graph graph; - ClWorkloadFactory factory; - - auto workloads = - CreateSplitterMergerWorkloadTest<ClSplitterWorkload, MergerWorkloadType, DataType> - (factory, graph); - - auto wlSplitter = std::move(workloads.first); - auto wlMerger = std::move(workloads.second); - - //Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction. - armnn::ClSubTensorHandle* sOut0 = dynamic_cast<armnn::ClSubTensorHandle*>(wlSplitter->GetData().m_Outputs[0]); - armnn::ClSubTensorHandle* sOut1 = dynamic_cast<armnn::ClSubTensorHandle*>(wlSplitter->GetData().m_Outputs[1]); - armnn::ClSubTensorHandle* mIn0 = dynamic_cast<armnn::ClSubTensorHandle*>(wlMerger->GetData().m_Inputs[0]); - armnn::ClSubTensorHandle* mIn1 = dynamic_cast<armnn::ClSubTensorHandle*>(wlMerger->GetData().m_Inputs[1]); - - BOOST_TEST(sOut0); - BOOST_TEST(sOut1); - BOOST_TEST(mIn0); - BOOST_TEST(mIn1); - - //Fliped order of inputs/outputs. - bool validDataPointers = (sOut0 == mIn1) && (sOut1 == mIn0); - BOOST_TEST(validDataPointers); - - - //Also make sure that the inputs are subtensors of one tensor and outputs are sub tensors of another tensor. - bool validSubTensorParents = (mIn0->GetTensor().parent() == mIn1->GetTensor().parent()) - && (sOut0->GetTensor().parent() == sOut1->GetTensor().parent()); - - BOOST_TEST(validSubTensorParents); -} - -BOOST_AUTO_TEST_CASE(CreateSplitterMergerFloatWorkload) -{ - ClSplitterMergerTest<ClMergerFloatWorkload, armnn::DataType::Float32>(); -} - -BOOST_AUTO_TEST_CASE(CreateSplitterMergerFloat16Workload) -{ - ClSplitterMergerTest<ClMergerFloatWorkload, armnn::DataType::Float16>(); -} - - -BOOST_AUTO_TEST_CASE(CreateSingleOutputMultipleInputs) -{ - // Test that it is possible to assign multiple (two) different layers to each of the outputs of a splitter layer. - // We create a splitter with two outputs. That each of those outputs is used by two different activation layers. - - Graph graph; - ClWorkloadFactory factory; - std::unique_ptr<ClSplitterWorkload> wlSplitter; - std::unique_ptr<ClActivationFloatWorkload> wlActiv0_0; - std::unique_ptr<ClActivationFloatWorkload> wlActiv0_1; - std::unique_ptr<ClActivationFloatWorkload> wlActiv1_0; - std::unique_ptr<ClActivationFloatWorkload> wlActiv1_1; - - CreateSplitterMultipleInputsOneOutputWorkloadTest<ClSplitterWorkload, - ClActivationFloatWorkload, armnn::DataType::Float32>(factory, graph, wlSplitter, wlActiv0_0, wlActiv0_1, - wlActiv1_0, wlActiv1_1); - - //Checks that the index of inputs/outputs matches what we declared on InputDescriptor construction. - armnn::ClSubTensorHandle* sOut0 = dynamic_cast<armnn::ClSubTensorHandle*>(wlSplitter->GetData().m_Outputs[0]); - armnn::ClSubTensorHandle* sOut1 = dynamic_cast<armnn::ClSubTensorHandle*>(wlSplitter->GetData().m_Outputs[1]); - armnn::ClSubTensorHandle* activ0_0Im = dynamic_cast<armnn::ClSubTensorHandle*>(wlActiv0_0->GetData().m_Inputs[0]); - armnn::ClSubTensorHandle* activ0_1Im = dynamic_cast<armnn::ClSubTensorHandle*>(wlActiv0_1->GetData().m_Inputs[0]); - armnn::ClSubTensorHandle* activ1_0Im = dynamic_cast<armnn::ClSubTensorHandle*>(wlActiv1_0->GetData().m_Inputs[0]); - armnn::ClSubTensorHandle* activ1_1Im = dynamic_cast<armnn::ClSubTensorHandle*>(wlActiv1_1->GetData().m_Inputs[0]); - - - BOOST_TEST(sOut0); - BOOST_TEST(sOut1); - BOOST_TEST(activ0_0Im); - BOOST_TEST(activ0_1Im); - BOOST_TEST(activ1_0Im); - BOOST_TEST(activ1_1Im); - - bool validDataPointers = (sOut0 == activ0_0Im) && (sOut0 == activ0_1Im) && - (sOut1 == activ1_0Im) && (sOut1 == activ1_1Im); - - BOOST_TEST(validDataPointers); -} - -BOOST_AUTO_TEST_CASE(CreateMemCopyWorkloadsCl) -{ - ClWorkloadFactory factory; - CreateMemCopyWorkloads<IClTensorHandle>(factory); -} - -template <typename L2NormalizationWorkloadType, typename armnn::DataType DataType> -static void ClL2NormalizationWorkloadTest(DataLayout dataLayout) -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateL2NormalizationWorkloadTest<L2NormalizationWorkloadType, DataType> - (factory, graph, dataLayout); - - // Checks that inputs/outputs are as we expect them (see definition of CreateNormalizationWorkloadTest). - L2NormalizationQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 5, 20, 50, 67 })); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, { 5, 20, 50, 67 })); -} - -BOOST_AUTO_TEST_CASE(CreateL2NormalizationFloatNchwWorkload) -{ - ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateL2NormalizationFloatNhwcWorkload) -{ - ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float32>(DataLayout::NHWC); -} - -BOOST_AUTO_TEST_CASE(CreateL2NormalizationFloat16NchwWorkload) -{ - ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateL2NormalizationFloat16NhwcWorkload) -{ - ClL2NormalizationWorkloadTest<ClL2NormalizationFloatWorkload, armnn::DataType::Float16>(DataLayout::NHWC); -} - -template <typename LstmWorkloadType> -static void ClCreateLstmWorkloadTest() -{ - Graph graph; - ClWorkloadFactory factory; - auto workload = CreateLstmWorkloadTest<LstmWorkloadType>(factory, graph); - - LstmQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[1]); - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 2, 2 })); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, { 2, 4 })); -} - -BOOST_AUTO_TEST_CASE(CreateLSTMWorkloadFloatWorkload) -{ - ClCreateLstmWorkloadTest<ClLstmFloatWorkload>(); -} - -template <typename ResizeBilinearWorkloadType, typename armnn::DataType DataType> -static void ClResizeBilinearWorkloadTest(DataLayout dataLayout) -{ - Graph graph; - ClWorkloadFactory factory; - - auto workload = CreateResizeBilinearWorkloadTest<ResizeBilinearWorkloadType, DataType>(factory, graph, dataLayout); - - // Checks that inputs/outputs are as we expect them (see definition of CreateResizeBilinearWorkloadTest). - ResizeBilinearQueueDescriptor queueDescriptor = workload->GetData(); - auto inputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Inputs[0]); - auto outputHandle = boost::polymorphic_downcast<IClTensorHandle*>(queueDescriptor.m_Outputs[0]); - - switch (dataLayout) - { - case DataLayout::NHWC: - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 2, 4, 4, 3 })); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, { 2, 2, 2, 3 })); - break; - default: // NCHW - BOOST_TEST(CompareIClTensorHandleShape(inputHandle, { 2, 3, 4, 4 })); - BOOST_TEST(CompareIClTensorHandleShape(outputHandle, { 2, 3, 2, 2 })); - } -} - -BOOST_AUTO_TEST_CASE(CreateResizeBilinearFloat32NchwWorkload) -{ - ClResizeBilinearWorkloadTest<ClResizeBilinearFloatWorkload, armnn::DataType::Float32>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateResizeBilinearFloat16NchwWorkload) -{ - ClResizeBilinearWorkloadTest<ClResizeBilinearFloatWorkload, armnn::DataType::Float16>(DataLayout::NCHW); -} - -BOOST_AUTO_TEST_CASE(CreateResizeBilinearFloat32NhwcWorkload) -{ - ClResizeBilinearWorkloadTest<ClResizeBilinearFloatWorkload, armnn::DataType::Float32>(DataLayout::NHWC); -} - -BOOST_AUTO_TEST_CASE(CreateResizeBilinearFloat16NhwcWorkload) -{ - ClResizeBilinearWorkloadTest<ClResizeBilinearFloatWorkload, armnn::DataType::Float16>(DataLayout::NHWC); -} - -BOOST_AUTO_TEST_SUITE_END() |