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Diffstat (limited to 'src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp')
| -rw-r--r-- | src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp | 315 |
1 files changed, 315 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp new file mode 100644 index 0000000000..589cc03cbc --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ReductionTestImpl.cpp @@ -0,0 +1,315 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ReductionTestImpl.hpp" + +#include <backendsCommon/test/DataTypeUtils.hpp> +#include <backendsCommon/test/TensorCopyUtils.hpp> +#include <backendsCommon/test/WorkloadTestUtils.hpp> + +#include <test/TensorHelpers.hpp> + +#include <iostream> + +namespace +{ + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<float, 4> ReductionTestCommon( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory, + const armnn::TensorInfo inputTensorInfo, + const armnn::TensorInfo outputTensorInfo, + const std::vector<float>& inputData, + const std::vector<float>& outputData, + const std::vector<int32_t> vAxis, + const armnn::ReduceOperation reduceOperation, + bool keepDims = false) +{ + IgnoreUnused(memoryManager); + auto inputTensor = MakeTensor<T, 4>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo)); + + LayerTestResult<float, 4> result(outputTensorInfo); + result.outputExpected = MakeTensor<float, 4>(outputTensorInfo, outputData); + + std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo); + std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.CreateTensorHandle(outputTensorInfo); + + armnn::ReduceQueueDescriptor descriptor; + std::vector<uint32_t> updated_idx; + uint32_t resolvedAxis = 0; + for (uint32_t i = 0; i < vAxis.size(); ++i) + { + if (vAxis[i] < 0) + { + resolvedAxis = inputTensorInfo.GetNumDimensions() + static_cast<uint32_t>(vAxis[i]); + } else + { + resolvedAxis = static_cast<uint32_t>(vAxis[i]); + } + + updated_idx.push_back(resolvedAxis); + } + + descriptor.m_Parameters.m_vAxis = updated_idx; + descriptor.m_Parameters.m_ReduceOperation = reduceOperation; + descriptor.m_Parameters.m_KeepDims = keepDims; + armnn::WorkloadInfo info; + + AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get()); + AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get()); + + std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateReduce(descriptor, info); + + inputHandle->Allocate(); + outputHandle->Allocate(); + + CopyDataToITensorHandle(inputHandle.get(), inputTensor.origin()); + + workload->Execute(); + + CopyDataFromITensorHandle(result.output.origin(), outputHandle.get()); + + return result; +} + +} // namespace + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceMaxSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; + const armnn::TensorShape outputShape{ 1, 1, 1, 3}; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + + if (armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(1.0f); + inputTensorInfo.SetQuantizationOffset(0); + } + + armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); + + std::vector<float> inputValues + ({ + 1001.0f, 11.0f, 1003.0f, + 10.0f, 1002.0f, 12.0f + }); + std::vector<float> outputValues + ({ + 1001.0f, 1002.0f, 1003.0f + }); + + return ReductionTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 2 }, + armnn::ReduceOperation::Max); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceMaxNegativeAxisTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; + const armnn::TensorShape outputShape{ 1, 1, 2, 1}; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + + if (armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(1.0f); + inputTensorInfo.SetQuantizationOffset(0); + } + + armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); + + std::vector<float> inputValues + ({ + 1001.0f, 11.0f, 1003.0f, + 10.0f, 1002.0f, 12.0f + }); + std::vector<float> outputValues + ({ + 1003.0f, 1002.0f + }); + + return ReductionTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { -1 }, + armnn::ReduceOperation::Max, + true); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceMaxSimpleTest2( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; + const armnn::TensorShape outputShape{ 1, 1, 2, 1 }; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + + if (armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(1.0f); + inputTensorInfo.SetQuantizationOffset(0); + } + + armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); + + std::vector<float> inputValues + ({ + 1.0f, 3.0f, 2.0f, + 6.0f, 4.0f, 5.0f + }); + + std::vector<float> outputValues + ({ + 3.0f, 6.0f + }); + + return ReductionTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 3 }, + armnn::ReduceOperation::Max, + true); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceMinSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape { 1, 1, 2, 3 }; + const armnn::TensorShape outputShape { 1, 1, 1, 3}; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + + if (armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(1.0f); + inputTensorInfo.SetQuantizationOffset(0); + } + + armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); + + std::vector<float> inputValues + ({ + 1001.0f, 11.0f, 1003.0f, + 10.0f, 1002.0f, 12.0f + }); + std::vector<float> outputValues + ({ + 10.0f, 11.0f, 12.0f + }); + + return ReductionTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 2 }, + armnn::ReduceOperation::Min); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceMinNegativeAxisTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 1, 2, 3 }; + const armnn::TensorShape outputShape{ 1, 1, 2, 1}; + + armnn::TensorInfo inputTensorInfo(inputShape, ArmnnType); + + if (armnn::IsQuantizedType<T>()) + { + inputTensorInfo.SetQuantizationScale(1.0f); + inputTensorInfo.SetQuantizationOffset(0); + } + + armnn::TensorInfo outputTensorInfo(outputShape, armnn::DataType::Float32); + + std::vector<float> inputValues + ({ + 1001.0f, 11.0f, 1003.0f, + 10.0f, 1002.0f, 12.0f + }); + std::vector<float> outputValues + ({ + 11.0f, 10.0f + }); + + return ReductionTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { -1 }, + armnn::ReduceOperation::Min, + true); +} + +// Explicit template specializations +template LayerTestResult<float, 4> +ReduceMaxSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceMaxNegativeAxisTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceMaxSimpleTest2<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceMinSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceMinNegativeAxisTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + |