diff options
Diffstat (limited to 'src/backends/backendsCommon/test/layerTests')
5 files changed, 194 insertions, 267 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/AbsTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/AbsTestImpl.cpp index cc57893439..7706809e8b 100644 --- a/src/backends/backendsCommon/test/layerTests/AbsTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/AbsTestImpl.cpp @@ -4,85 +4,15 @@ // #include "AbsTestImpl.hpp" +#include "ElementwiseUnaryTestImpl.hpp" -#include <backendsCommon/test/DataTypeUtils.hpp> -#include <backendsCommon/test/TensorCopyUtils.hpp> -#include <backendsCommon/test/WorkloadTestUtils.hpp> - -#include <test/TensorHelpers.hpp> - -namespace -{ - -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> -LayerTestResult<T, 2> Abs2dTestCommon( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::TensorInfo inputTensorInfo, - const armnn::TensorInfo outputTensorInfo, - const std::vector<float>& inputValues, - const std::vector<float>& expectedOutputValues) -{ - boost::ignore_unused(memoryManager); - auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo)); - - LayerTestResult<T, 2> result(outputTensorInfo); - - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, - ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo)); - - std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - - armnn::AbsQueueDescriptor descriptor; - - armnn::WorkloadInfo info; - - AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); - AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); - - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAbs(descriptor, info); - - inputHandle->Allocate(); - outputHandle->Allocate(); - - CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); - - workload->PostAllocationConfigure(); - workload->Execute(); - - CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); - - return result; -} - -} // anonymous namespace - template<armnn::DataType ArmnnType, typename T> LayerTestResult<T, 2> Abs2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - const armnn::TensorShape inputShape{ 2, 2 }; - const armnn::TensorShape outputShape{ 2, 2 }; - - float qScale = 0.0625f; - int32_t qOffset = 64; - - if (ArmnnType == armnn::DataType::QSymmS16) - { - qScale = 0.1f; - qOffset = 0; - } - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(qScale); - inputTensorInfo.SetQuantizationOffset(qOffset); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(qScale); - outputTensorInfo.SetQuantizationOffset(qOffset); + const unsigned int inputShape[] = { 2, 2 }; std::vector<float> inputValues { @@ -98,9 +28,14 @@ LayerTestResult<T, 2> Abs2dTest( std::vector<float> expectedOutputValues(inputValues.size()); std::transform(inputValues.begin(), inputValues.end(), expectedOutputValues.begin(), f); - return Abs2dTestCommon<ArmnnType>(workloadFactory, memoryManager, - inputTensorInfo, outputTensorInfo, - inputValues, expectedOutputValues); + return ElementwiseUnaryTestHelper<2, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Abs, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } template<armnn::DataType ArmnnType, typename T> @@ -108,27 +43,7 @@ LayerTestResult<T, 3> Abs3dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - boost::ignore_unused(memoryManager); - - const armnn::TensorShape inputShape{ 3, 1, 2 }; - const armnn::TensorShape outputShape{ 3, 1, 2 }; - - float qScale = 0.0625f; - int32_t qOffset = 64; - - if (ArmnnType == armnn::DataType::QSymmS16) - { - qScale = 0.1f; - qOffset = 0; - } - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(qScale); - inputTensorInfo.SetQuantizationOffset(qOffset); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(qScale); - outputTensorInfo.SetQuantizationOffset(qOffset); + const unsigned int inputShape[] = { 3, 1, 2 }; std::vector<float> inputValues { @@ -143,35 +58,14 @@ LayerTestResult<T, 3> Abs3dTest( std::vector<float>expectedOutputValues(inputValues.size()); std::transform(inputValues.begin(), inputValues.end(), expectedOutputValues.begin(), f); - auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo)); - - LayerTestResult<T, 3> result(outputTensorInfo); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, - ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo)); - - std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - - armnn::AbsQueueDescriptor descriptor; - - armnn::WorkloadInfo info; - - AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); - AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); - - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateAbs(descriptor, info); - - inputHandle->Allocate(); - outputHandle->Allocate(); - - CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]); - - workload->PostAllocationConfigure(); - workload->Execute(); - - CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get()); - - return result; + return ElementwiseUnaryTestHelper<3, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Abs, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } template<armnn::DataType ArmnnType, typename T> @@ -179,14 +73,7 @@ LayerTestResult<T, 2> AbsZeroTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - const armnn::TensorShape inputShape{ 1, 2 }; - const armnn::TensorShape outputShape{ 1, 2 }; - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(0.1f); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(0.1f); + const unsigned int inputShape[] = { 1, 2 }; std::vector<float> inputValues { @@ -198,9 +85,14 @@ LayerTestResult<T, 2> AbsZeroTest( 0.f, 0.f }; - return Abs2dTestCommon<ArmnnType>(workloadFactory, memoryManager, - inputTensorInfo, outputTensorInfo, - inputValues, expectedOutputValues); + return ElementwiseUnaryTestHelper<2, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Abs, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } // diff --git a/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp index c0a779c0e6..cbbe140843 100644 --- a/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp +++ b/src/backends/backendsCommon/test/layerTests/ElementwiseTestImpl.hpp @@ -15,6 +15,7 @@ #include <backendsCommon/WorkloadData.hpp> #include <backendsCommon/WorkloadFactory.hpp> +#include <backendsCommon/test/DataTypeUtils.hpp> #include <backendsCommon/test/TensorCopyUtils.hpp> #include <backendsCommon/test/WorkloadTestUtils.hpp> @@ -202,4 +203,4 @@ LayerTestResult<T, NumDims> ElementwiseTestHelper( outValues, quantScale, quantOffset); -} +}
\ No newline at end of file diff --git a/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.cpp new file mode 100644 index 0000000000..a2c88a62e7 --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.cpp @@ -0,0 +1,14 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ElementwiseUnaryTestImpl.hpp" + +std::unique_ptr<armnn::IWorkload> CreateWorkload( + const armnn::IWorkloadFactory& workloadFactory, + const armnn::WorkloadInfo& info, + const armnn::ElementwiseUnaryQueueDescriptor& descriptor) +{ + return workloadFactory.CreateElementwiseUnary(descriptor, info); +}
\ No newline at end of file diff --git a/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp new file mode 100644 index 0000000000..bea4ec205e --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ElementwiseUnaryTestImpl.hpp @@ -0,0 +1,113 @@ +// +// Copyright © 2019 Arm Ltd. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerTestResult.hpp" + +#include <armnn/ArmNN.hpp> + +#include <ResolveType.hpp> + +#include <armnn/backends/IBackendInternal.hpp> +#include <backendsCommon/Workload.hpp> +#include <backendsCommon/WorkloadData.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +#include <backendsCommon/test/DataTypeUtils.hpp> +#include <backendsCommon/test/TensorCopyUtils.hpp> +#include <backendsCommon/test/WorkloadTestUtils.hpp> + +#include <test/TensorHelpers.hpp> + +#include <memory> + +std::unique_ptr<armnn::IWorkload> CreateWorkload( + const armnn::IWorkloadFactory& workloadFactory, + const armnn::WorkloadInfo& info, + const armnn::ElementwiseUnaryQueueDescriptor& descriptor); + +template <std::size_t NumDims, + armnn::DataType ArmnnType, + typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<T, NumDims> ElementwiseUnaryTestHelper( + armnn::IWorkloadFactory & workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager, + armnn::UnaryOperation op, + const unsigned int shape[NumDims], + std::vector<float> values, + float quantScale, + int quantOffset, + const unsigned int outShape[NumDims], + std::vector<float> outValues, + float outQuantScale, + int outQuantOffset) +{ + armnn::TensorInfo inputTensorInfo{NumDims, shape, ArmnnType}; + armnn::TensorInfo outputTensorInfo{NumDims, outShape, ArmnnType}; + + inputTensorInfo.SetQuantizationScale(quantScale); + inputTensorInfo.SetQuantizationOffset(quantOffset); + + outputTensorInfo.SetQuantizationScale(outQuantScale); + outputTensorInfo.SetQuantizationOffset(outQuantOffset); + + auto input = MakeTensor<T, NumDims>(inputTensorInfo, ConvertToDataType<ArmnnType>(values, inputTensorInfo)); + + LayerTestResult<T, NumDims> ret(outputTensorInfo); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); + + armnn::ElementwiseUnaryDescriptor desc(op); + armnn::ElementwiseUnaryQueueDescriptor qDesc; + qDesc.m_Parameters = desc; + armnn::WorkloadInfo info; + AddInputToWorkload(qDesc, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(qDesc, info, outputTensorInfo, outputHandle.get()); + auto workload = CreateWorkload(workloadFactory, info, qDesc); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), input.origin()); + + workload->PostAllocationConfigure(); + ExecuteWorkload(*workload, memoryManager); + + CopyDataFromITensorHandle(ret.output.origin(), outputHandle.get()); + + ret.outputExpected = MakeTensor<T, NumDims>(outputTensorInfo, ConvertToDataType<ArmnnType>(outValues, + inputTensorInfo)); + return ret; +} + +template <std::size_t NumDims, + armnn::DataType ArmnnType, + typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<T, NumDims> ElementwiseUnaryTestHelper( + armnn::IWorkloadFactory & workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager, + armnn::UnaryOperation op, + const unsigned int shape[NumDims], + std::vector<float> values, + const unsigned int outShape[NumDims], + std::vector<float> outValues, + float quantScale = 1.0f, + int quantOffset = 0) +{ + return ElementwiseUnaryTestHelper<NumDims, ArmnnType>( + workloadFactory, + memoryManager, + op, + shape, + values, + quantScale, + quantOffset, + outShape, + outValues, + quantScale, + quantOffset); +}
\ No newline at end of file diff --git a/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp index db928cf2e0..ca423835dc 100644 --- a/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp +++ b/src/backends/backendsCommon/test/layerTests/RsqrtTestImpl.cpp @@ -4,76 +4,15 @@ // #include "ReshapeTestImpl.hpp" +#include "ElementwiseUnaryTestImpl.hpp" -#include <backendsCommon/test/DataTypeUtils.hpp> -#include <backendsCommon/test/TensorCopyUtils.hpp> -#include <backendsCommon/test/WorkloadTestUtils.hpp> - -#include <test/TensorHelpers.hpp> - -namespace -{ - -template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> -LayerTestResult<T, 2> Rsqrt2dTestCommon( - armnn::IWorkloadFactory& workloadFactory, - const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, - const armnn::TensorInfo inputTensorInfo, - const armnn::TensorInfo outputTensorInfo, - const std::vector<float>& inputValues, - const std::vector<float>& expectedOutputValues) -{ - boost::ignore_unused(memoryManager); - auto inputTensor = MakeTensor<T, 2>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo)); - - LayerTestResult<T, 2> result(outputTensorInfo); - - result.outputExpected = MakeTensor<T, 2>(outputTensorInfo, - ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo)); - - std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - - armnn::RsqrtQueueDescriptor descriptor; - - armnn::WorkloadInfo info; - - AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); - AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); - - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info); - - inputHandle->Allocate(); - outputHandle->Allocate(); - - CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0]); - - workload->PostAllocationConfigure(); - workload->Execute(); - - CopyDataFromITensorHandle(&result.output[0][0], outputHandle.get()); - - return result; -} - -} // anonymous namespace - template<armnn::DataType ArmnnType, typename T> LayerTestResult<T, 2> Rsqrt2dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - const armnn::TensorShape inputShape{ 2, 2 }; - const armnn::TensorShape outputShape{ 2, 2 }; - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(0.1f); - inputTensorInfo.SetQuantizationOffset(0); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(0.1f); - outputTensorInfo.SetQuantizationOffset(0); + const unsigned int inputShape[] = { 2, 2 }; std::vector<float> inputValues { @@ -87,9 +26,14 @@ LayerTestResult<T, 2> Rsqrt2dTest( 0.25f, 0.2f }; - return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager, - inputTensorInfo, outputTensorInfo, - inputValues, expectedOutputValues); + return ElementwiseUnaryTestHelper<2, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Rsqrt, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } template<armnn::DataType ArmnnType, typename T> @@ -97,17 +41,7 @@ LayerTestResult<T, 3> Rsqrt3dTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - boost::ignore_unused(memoryManager); - const armnn::TensorShape inputShape{ 3, 1, 2 }; - const armnn::TensorShape outputShape{ 3, 1, 2 }; - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(0.1f); - inputTensorInfo.SetQuantizationOffset(0); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(0.1f); - outputTensorInfo.SetQuantizationOffset(0); + const unsigned int inputShape[] = { 3, 1, 2 }; std::vector<float> inputValues { @@ -121,35 +55,14 @@ LayerTestResult<T, 3> Rsqrt3dTest( 0.2f, 0.125f, 0.1f }; - auto inputTensor = MakeTensor<T, 3>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputValues,inputTensorInfo)); - - LayerTestResult<T, 3> result(outputTensorInfo); - result.outputExpected = MakeTensor<T, 3>(outputTensorInfo, - ConvertToDataType<ArmnnType>(expectedOutputValues,outputTensorInfo)); - - std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo); - std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo); - - armnn::RsqrtQueueDescriptor descriptor; - - armnn::WorkloadInfo info; - - AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); - AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); - - std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateRsqrt(descriptor, info); - - inputHandle->Allocate(); - outputHandle->Allocate(); - - CopyDataToITensorHandle(inputHandle.get(), &inputTensor[0][0][0]); - - workload->PostAllocationConfigure(); - workload->Execute(); - - CopyDataFromITensorHandle(&result.output[0][0][0], outputHandle.get()); - - return result; + return ElementwiseUnaryTestHelper<3, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Rsqrt, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } template<armnn::DataType ArmnnType, typename T> @@ -157,14 +70,7 @@ LayerTestResult<T, 2> RsqrtZeroTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - const armnn::TensorShape inputShape{ 1, 2 }; - const armnn::TensorShape outputShape{ 1, 2 }; - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(0.1f); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(0.1f); + const unsigned int inputShape[] = { 1, 2 }; std::vector<float> inputValues { @@ -176,9 +82,14 @@ LayerTestResult<T, 2> RsqrtZeroTest( INFINITY, -INFINITY }; - return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager, - inputTensorInfo, outputTensorInfo, - inputValues, expectedOutputValues); + return ElementwiseUnaryTestHelper<2, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Rsqrt, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } template<armnn::DataType ArmnnType, typename T> @@ -186,16 +97,7 @@ LayerTestResult<T, 2> RsqrtNegativeTest( armnn::IWorkloadFactory& workloadFactory, const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager) { - const armnn::TensorShape inputShape{ 1, 2 }; - const armnn::TensorShape outputShape{ 1, 2 }; - - armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); - inputTensorInfo.SetQuantizationScale(0.1f); - inputTensorInfo.SetQuantizationOffset(0); - - armnn::TensorInfo outputTensorInfo(outputShape, ArmnnType); - outputTensorInfo.SetQuantizationScale(0.1f); - outputTensorInfo.SetQuantizationOffset(0); + const unsigned int inputShape[] = { 1, 2 }; std::vector<float> inputValues { @@ -207,9 +109,14 @@ LayerTestResult<T, 2> RsqrtNegativeTest( -NAN, -NAN }; - return Rsqrt2dTestCommon<ArmnnType>(workloadFactory, memoryManager, - inputTensorInfo, outputTensorInfo, - inputValues, expectedOutputValues); + return ElementwiseUnaryTestHelper<2, ArmnnType>( + workloadFactory, + memoryManager, + armnn::UnaryOperation::Rsqrt, + inputShape, + inputValues, + inputShape, + expectedOutputValues); } // |