diff options
author | Teresa Charlin <teresa.charlinreyes@arm.com> | 2021-08-05 12:34:37 +0100 |
---|---|---|
committer | TeresaARM <teresa.charlinreyes@arm.com> | 2021-09-03 08:41:21 +0000 |
commit | 4e3e831da1d6d85dffffacf57e9de8fc891b7e58 (patch) | |
tree | 9a3653729feba788dcfbbdc5255ad379cbbf597d /src/backends | |
parent | 14bef9f83f7cd58e5038ae7432d75da2d50e7b68 (diff) | |
download | armnn-4e3e831da1d6d85dffffacf57e9de8fc891b7e58.tar.gz |
IVGCVSW-6262 Add support for Reduce Prod
* Tflite parser
* Tflite delegate
* Serializer
* Deserializer
* Ref, CpuAcc and GpuAcc workloads
Signed-off-by: Teresa Charlin <teresa.charlinreyes@arm.com>
Change-Id: I601a9ee1680b372c7955d9a628857d08c3cfd377
Diffstat (limited to 'src/backends')
-rw-r--r-- | src/backends/aclCommon/ArmComputeUtils.hpp | 3 | ||||
-rw-r--r-- | src/backends/backendsCommon/common.mk | 1 | ||||
-rw-r--r-- | src/backends/backendsCommon/test/CMakeLists.txt | 2 | ||||
-rw-r--r-- | src/backends/backendsCommon/test/LayerTests.hpp | 1 | ||||
-rw-r--r-- | src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp | 345 | ||||
-rw-r--r-- | src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp | 43 | ||||
-rw-r--r-- | src/backends/cl/test/ClLayerTests.cpp | 9 | ||||
-rw-r--r-- | src/backends/neon/test/NeonLayerTests.cpp | 4 | ||||
-rw-r--r-- | src/backends/reference/test/RefLayerTests.cpp | 7 | ||||
-rw-r--r-- | src/backends/reference/workloads/Reduce.cpp | 43 |
10 files changed, 440 insertions, 18 deletions
diff --git a/src/backends/aclCommon/ArmComputeUtils.hpp b/src/backends/aclCommon/ArmComputeUtils.hpp index 624ce5df7a..059518acd6 100644 --- a/src/backends/aclCommon/ArmComputeUtils.hpp +++ b/src/backends/aclCommon/ArmComputeUtils.hpp @@ -272,7 +272,8 @@ inline arm_compute::ReductionOperation ConvertReductionOperationToAcl(const Redu case ReduceOperation::Mean: return arm_compute::ReductionOperation::MEAN_SUM; case ReduceOperation::Max: return arm_compute::ReductionOperation::MAX; case ReduceOperation::Min: return arm_compute::ReductionOperation::MIN; - default: throw InvalidArgumentException("Unsupported Reduction operation"); + case ReduceOperation::Prod: return arm_compute::ReductionOperation::PROD; + default: throw InvalidArgumentException("Unsupported Reduction operation"); } } diff --git a/src/backends/backendsCommon/common.mk b/src/backends/backendsCommon/common.mk index 5d339477d5..47ceffe37d 100644 --- a/src/backends/backendsCommon/common.mk +++ b/src/backends/backendsCommon/common.mk @@ -78,6 +78,7 @@ COMMON_TEST_SOURCES := \ test/layerTests/Pooling2dTestImpl.cpp \ test/layerTests/RankTestImpl.cpp \ test/layerTests/ReductionTestImpl.cpp \ + test/layerTests/ReduceProdTestImpl.cpp \ test/layerTests/ReduceSumTestImpl.cpp \ test/layerTests/ReshapeTestImpl.cpp \ test/layerTests/ResizeTestImpl.cpp \ diff --git a/src/backends/backendsCommon/test/CMakeLists.txt b/src/backends/backendsCommon/test/CMakeLists.txt index 4561fd7739..c9bc5e74b8 100644 --- a/src/backends/backendsCommon/test/CMakeLists.txt +++ b/src/backends/backendsCommon/test/CMakeLists.txt @@ -139,6 +139,8 @@ list(APPEND armnnBackendsCommonUnitTests_sources layerTests/RankTestImpl.hpp layerTests/ReductionTestImpl.cpp layerTests/ReductionTestImpl.hpp + layerTests/ReduceProdTestImpl.cpp + layerTests/ReduceProdTestImpl.hpp layerTests/ReduceSumTestImpl.cpp layerTests/ReduceSumTestImpl.hpp layerTests/ReshapeTestImpl.cpp diff --git a/src/backends/backendsCommon/test/LayerTests.hpp b/src/backends/backendsCommon/test/LayerTests.hpp index fcb1f71436..0690637500 100644 --- a/src/backends/backendsCommon/test/LayerTests.hpp +++ b/src/backends/backendsCommon/test/LayerTests.hpp @@ -51,6 +51,7 @@ #include <backendsCommon/test/layerTests/QuantizeTestImpl.hpp> #include <backendsCommon/test/layerTests/RankTestImpl.hpp> #include <backendsCommon/test/layerTests/ReductionTestImpl.hpp> +#include <backendsCommon/test/layerTests/ReduceProdTestImpl.hpp> #include <backendsCommon/test/layerTests/ReduceSumTestImpl.hpp> #include <backendsCommon/test/layerTests/ReshapeTestImpl.hpp> #include <backendsCommon/test/layerTests/ResizeTestImpl.hpp> diff --git a/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp new file mode 100644 index 0000000000..4fb0732141 --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.cpp @@ -0,0 +1,345 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#include "ReduceProdTestImpl.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<float, 4> ReduceTestCommon( + 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 = ConvertToDataType<ArmnnType>(inputData, inputTensorInfo); + + std::vector<float> actualOutput(outputTensorInfo.GetNumElements()); + + 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.data()); + + workload->Execute(); + + CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get()); + + return LayerTestResult<float, 4>(actualOutput, + outputData, + outputHandle->GetShape(), + outputTensorInfo.GetShape()); +} + +} // namespace + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceProdSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 1, 1, 5 }; + const armnn::TensorShape outputShape{ 1, 1, 1, 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({ 5.0f, 2.0f, 8.0f, 10.0f, 9.0f }); + std::vector<float> outputValues({ 7200.0f }); + + return ReduceTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { -1 }, + armnn::ReduceOperation::Prod); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceProdSingleAxisTest1( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 3, 2, 4 }; + const armnn::TensorShape outputShape{ 1, 1, 2, 4 }; + + 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, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, + 10.0f, 20.0f, 30.0f, 40.0f, 50.0f, 60.0f, 70.0f, 80.0f, + 100.0f, 200.0f, 300.0f, 400.0f, 500.0f, 600.0f, 700.0f, 800.0f + }); + std::vector<float> outputValues({ 1000.0f, 8000.0f, 27000.0f, 64000.0f, 125000.0f, 216000.0f, 343000.0f, 512000.0f + }); + + return ReduceTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 1 }, + armnn::ReduceOperation::Prod); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceProdSingleAxisTest2( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 6, 3, 4 }; + const armnn::TensorShape outputShape{ 1, 1, 3, 4}; + + 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( {7, 8, 6, 1, + 1, 1, 8, 7, + 3, 7, 7, 7, + + 6, 8, 4, 7, + 3, 8, 7, 3, + 5, 8, 8, 8, + + + 7, 8, 2, 7, + 3, 8, 5, 6, + 8, 4, 2, 7, + + 1, 6, 7, 2, + 8, 3, 3, 1, + 7, 6, 2, 6, + + + 5, 3, 4, 8, + 7, 8, 2, 4, + 6, 6, 2, 8, + + 2, 2, 7, 2, + 5, 3, 6, 3, + 6, 1, 8, 8}); + std::vector<float> outputValues({ 2940.f, 18432.f, 9408.f, 1568.f, + 2520.f, 4608.f, 10080.f, 1512.f, + 30240.f, 8064.f, 3584.f, 150528.f }); + + return ReduceTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 1 }, + armnn::ReduceOperation::Prod); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceProdSingleAxisTest3( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 6, 3, 4 }; + const armnn::TensorShape outputShape{ 1, 6, 3, 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({ 7, 8, 6, 1, + 1, 1, 8, 7, + 3, 7, 7, 7, + + 6, 8, 4, 7, + 3, 8, 7, 3, + 5, 8, 8, 8, + + + 7, 8, 2, 7, + 3, 8, 5, 6, + 8, 4, 2, 7, + + 1, 6, 7, 2, + 8, 3, 3, 1, + 7, 6, 2, 6, + + + 5, 3, 4, 8, + 7, 8, 2, 4, + 6, 6, 2, 8, + + 2, 2, 7, 2, + 5, 3, 6, 3, + 6, 1, 8, 8 }); + std::vector<float> outputValues({ 336.f, 56.f, 1029.f, + 1344.f, 504.f, 2560.f, + + 784.f, 720.f, 448.f, + 84.f, 72.f, 504.f, + + 480.f, 448.f, 576.f, + 56.f, 270.f, 384.f }); + + return ReduceTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 3 }, + armnn::ReduceOperation::Prod, + true); +} + +template<armnn::DataType ArmnnType, typename T> +LayerTestResult<float, 4> ReduceProdMultipleAxisTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory) +{ + const armnn::TensorShape inputShape{ 1, 3, 2, 4 }; + const armnn::TensorShape outputShape{ 1, 1, 1, 4 }; + + 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, 2.0f, 3.0f, 4.0f, + 5.0f, 6.0f, 7.0f, 8.0f, + + 10.0f, 20.0f, 30.0f, 40.0f, + 50.0f, 60.0f, 70.0f, 80.0f, + + 11.0f, 22.0f, 33.0f, 44.0f, + 55.0f, 66.0f, 77.0f, 88.0f }); + std::vector<float> outputValues({ 1512500.f, 20908800.f, 112058100.f, 396492800.f }); + + return ReduceTestCommon<ArmnnType>(workloadFactory, + memoryManager, + tensorHandleFactory, + inputTensorInfo, + outputTensorInfo, + inputValues, + outputValues, + { 1, 2 }, + armnn::ReduceOperation::Prod); +} + +// Explicit template specializations + +template LayerTestResult<float, 4> +ReduceProdSimpleTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceProdSingleAxisTest1<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceProdSingleAxisTest2<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceProdSingleAxisTest3<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template LayerTestResult<float, 4> +ReduceProdMultipleAxisTest<armnn::DataType::Float32>( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); diff --git a/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp new file mode 100644 index 0000000000..97e94978f7 --- /dev/null +++ b/src/backends/backendsCommon/test/layerTests/ReduceProdTestImpl.hpp @@ -0,0 +1,43 @@ +// +// Copyright © 2021 Arm Ltd and Contributors. All rights reserved. +// SPDX-License-Identifier: MIT +// + +#pragma once + +#include "LayerTestResult.hpp" + +#include <ResolveType.hpp> + +#include <armnn/backends/IBackendInternal.hpp> +#include <backendsCommon/WorkloadFactory.hpp> + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<float, 4> ReduceProdSimpleTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<float, 4> ReduceProdSingleAxisTest1( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<float, 4> ReduceProdSingleAxisTest2( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<float, 4> ReduceProdSingleAxisTest3( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); + +template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> +LayerTestResult<float, 4> ReduceProdMultipleAxisTest( + armnn::IWorkloadFactory& workloadFactory, + const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager, + const armnn::ITensorHandleFactory& tensorHandleFactory); diff --git a/src/backends/cl/test/ClLayerTests.cpp b/src/backends/cl/test/ClLayerTests.cpp index f5b26d37f3..2bb63b5347 100644 --- a/src/backends/cl/test/ClLayerTests.cpp +++ b/src/backends/cl/test/ClLayerTests.cpp @@ -1894,6 +1894,15 @@ ARMNN_AUTO_TEST_FIXTURE_WITH_THF( ARMNN_AUTO_TEST_FIXTURE_WITH_THF( ReduceSumSingleAxisFloat32_3, ClContextControlFixture, ReduceSumSingleAxisTest3<DataType::Float32>) +// ReduceProd +ARMNN_AUTO_TEST_FIXTURE_WITH_THF(ReduceProdFloat32, ClContextControlFixture, ReduceProdSimpleTest<DataType::Float32>) +ARMNN_AUTO_TEST_FIXTURE_WITH_THF( + ReduceProdSingleAxisFloat32_1, ClContextControlFixture, ReduceProdSingleAxisTest1<DataType::Float32>) +ARMNN_AUTO_TEST_FIXTURE_WITH_THF( + ReduceProdSingleAxisFloat32_2, ClContextControlFixture, ReduceProdSingleAxisTest2<DataType::Float32>) +ARMNN_AUTO_TEST_FIXTURE_WITH_THF( + ReduceProdSingleAxisFloat32_3, ClContextControlFixture, ReduceProdSingleAxisTest3<DataType::Float32>) + // ReduceMax ARMNN_AUTO_TEST_FIXTURE_WITH_THF(ReduceMaxFloat32, ClContextControlFixture, ReduceMaxSimpleTest<DataType::Float32>) ARMNN_AUTO_TEST_FIXTURE_WITH_THF( diff --git a/src/backends/neon/test/NeonLayerTests.cpp b/src/backends/neon/test/NeonLayerTests.cpp index 6985776bf0..75f9648f2d 100644 --- a/src/backends/neon/test/NeonLayerTests.cpp +++ b/src/backends/neon/test/NeonLayerTests.cpp @@ -1399,6 +1399,10 @@ ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceSumSingleAxisFloat32_2, ReduceSumSingleAxisT // Moved to NeonLayerTests_NDK_Bug.cpp //ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceSumSingleAxisFloat32_3, ReduceSumSingleAxisTest3<DataType::Float32>) +// ReduceProd +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdSingleAxisFloat32_1, ReduceProdSingleAxisTest1<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdSingleAxisFloat32_2, ReduceProdSingleAxisTest2<DataType::Float32>) + // ReduceMax ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceMaxFloat32, ReduceMaxSimpleTest<DataType::Float32>) ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceMaxNegativeAxisFloat32, ReduceMaxNegativeAxisTest<DataType::Float32>) diff --git a/src/backends/reference/test/RefLayerTests.cpp b/src/backends/reference/test/RefLayerTests.cpp index e906b2962c..18490e29c7 100644 --- a/src/backends/reference/test/RefLayerTests.cpp +++ b/src/backends/reference/test/RefLayerTests.cpp @@ -2321,6 +2321,13 @@ ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceSumSingleAxisFloat32_2, ReduceSumSingleAxisT ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceSumSingleAxisFloat32_3, ReduceSumSingleAxisTest3<DataType::Float32>) ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceSumMultipleAxisFloat32, ReduceSumMultipleAxisTest<DataType::Float32>) +// ReduceProd +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdFloat32, ReduceProdSimpleTest<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdSingleAxisFloat32_1, ReduceProdSingleAxisTest1<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdSingleAxisFloat32_2, ReduceProdSingleAxisTest2<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdSingleAxisFloat32_3, ReduceProdSingleAxisTest3<DataType::Float32>) +ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceProdMultipleAxisFloat32, ReduceProdMultipleAxisTest<DataType::Float32>) + // ReduceMax ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceMaxFloat32, ReduceMaxSimpleTest<DataType::Float32>) ARMNN_AUTO_TEST_CASE_WITH_THF(ReduceMaxNegativeAxisFloat32, ReduceMaxNegativeAxisTest<DataType::Float32>) diff --git a/src/backends/reference/workloads/Reduce.cpp b/src/backends/reference/workloads/Reduce.cpp index 8bf422aea3..3f929c43bc 100644 --- a/src/backends/reference/workloads/Reduce.cpp +++ b/src/backends/reference/workloads/Reduce.cpp @@ -9,7 +9,6 @@ #include <backendsCommon/WorkloadData.hpp> -#include <cmath> #include <cstddef> #include <functional> #include <limits> @@ -87,6 +86,9 @@ void Reduce(const TensorInfo& inputInfo, case ReduceOperation::Sum: std::fill(tempOut.begin(), tempOut.end(), 0.0f); break; + case ReduceOperation::Prod: + std::fill(tempOut.begin(), tempOut.end(), 1.0f); + break; case ReduceOperation::Max: std::fill(tempOut.begin(), tempOut.end(), -1 * std::numeric_limits<float>::max()); break; @@ -119,23 +121,30 @@ void Reduce(const TensorInfo& inputInfo, numResolvedAxis, resolvedAxis); input[inputOffset]; auto inputValue = input.Get(); - if (reduceOperation == ReduceOperation::Max) - { - if (inputValue > tempOut[outputOffset]) - { - tempOut[outputOffset] = inputValue; - } - } - else if (reduceOperation == ReduceOperation::Min) - { - if (inputValue < tempOut[outputOffset]) - { - tempOut[outputOffset] = inputValue; - } - } - else + switch(reduceOperation) { - tempOut[outputOffset] += inputValue; + case ReduceOperation::Mean: + case ReduceOperation::Sum: + tempOut[outputOffset] += inputValue; + break; + case ReduceOperation::Prod: + tempOut[outputOffset] *= inputValue; + break; + case ReduceOperation::Max: + if (inputValue > tempOut[outputOffset]) + { + tempOut[outputOffset] = inputValue; + } + break; + case ReduceOperation::Min: + if (inputValue < tempOut[outputOffset]) + { + tempOut[outputOffset] = inputValue; + } + break; + default: + throw armnn::InvalidArgumentException("Unknown reduce method: " + + std::to_string(static_cast<int>(reduceOperation))); } } |