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-rw-r--r--src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp344
1 files changed, 344 insertions, 0 deletions
diff --git a/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp b/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp
new file mode 100644
index 0000000000..4edbd1108a
--- /dev/null
+++ b/src/backends/backendsCommon/test/layerTests/ReduceSumTestImpl.cpp
@@ -0,0 +1,344 @@
+//
+// Copyright © 2020 Samsung Electronics Co Ltd and Contributors. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ReduceSumTestImpl.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)
+{
+ 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;
+ 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> ReduceSumSimpleTest(
+ 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({ 34.0f });
+
+ return ReduceTestCommon<ArmnnType>(workloadFactory,
+ memoryManager,
+ tensorHandleFactory,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputValues,
+ outputValues,
+ { -1 },
+ armnn::ReduceOperation::Sum);
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<float, 4> ReduceSumSingleAxisTest1(
+ 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({ 111.0f, 222.0f, 333.0f, 444.0f,
+ 555.0f, 666.0f, 777.0f, 888.0f });
+
+ return ReduceTestCommon<ArmnnType>(workloadFactory,
+ memoryManager,
+ tensorHandleFactory,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputValues,
+ outputValues,
+ { 1 },
+ armnn::ReduceOperation::Sum);
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<float, 4> ReduceSumSingleAxisTest2(
+ 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({ 28.0f, 35.0f, 30.0f, 27.0f,
+ 27.0f, 31.0f, 31.0f, 24.0f,
+ 35.0f, 32.0f, 29.0f, 44.0f});
+
+ return ReduceTestCommon<ArmnnType>(workloadFactory,
+ memoryManager,
+ tensorHandleFactory,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputValues,
+ outputValues,
+ { 1 },
+ armnn::ReduceOperation::Sum);
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<float, 4> ReduceSumSingleAxisTest3(
+ 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({ 22.0f, 17.0f, 24.0f,
+ 25.0f, 21.0f, 29.0f,
+
+ 24.0f, 22.0f, 21.0f,
+ 16.0f, 15.0f, 21.0f,
+
+ 20.0f, 21.0f, 22.0f,
+ 13.0f, 17.0f, 23.0f});
+
+ return ReduceTestCommon<ArmnnType>(workloadFactory,
+ memoryManager,
+ tensorHandleFactory,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputValues,
+ outputValues,
+ { 3 },
+ armnn::ReduceOperation::Sum);
+}
+
+template<armnn::DataType ArmnnType, typename T>
+LayerTestResult<float, 4> ReduceSumMultipleAxisTest(
+ 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,
+
+ 100.0f, 200.0f, 300.0f, 400.0f,
+ 500.0f, 600.0f, 700.0f, 800.0f });
+ std::vector<float> outputValues({ 666.0f, 888.0f, 1110.0f, 1332.0f });
+
+ return ReduceTestCommon<ArmnnType>(workloadFactory,
+ memoryManager,
+ tensorHandleFactory,
+ inputTensorInfo,
+ outputTensorInfo,
+ inputValues,
+ outputValues,
+ { 1, 2 },
+ armnn::ReduceOperation::Sum);
+}
+
+// Explicit template specializations
+
+template LayerTestResult<float, 4>
+ReduceSumSimpleTest<armnn::DataType::Float32>(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<float, 4>
+ReduceSumSingleAxisTest1<armnn::DataType::Float32>(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<float, 4>
+ReduceSumSingleAxisTest2<armnn::DataType::Float32>(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<float, 4>
+ReduceSumSingleAxisTest3<armnn::DataType::Float32>(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory);
+
+template LayerTestResult<float, 4>
+ReduceSumMultipleAxisTest<armnn::DataType::Float32>(
+ armnn::IWorkloadFactory& workloadFactory,
+ const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
+ const armnn::ITensorHandleFactory& tensorHandleFactory);
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-18 17:06:09 +0000