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//
// Copyright © 2019 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <armnnTestUtils/LayerTestResult.hpp>
#include <armnn/ArmNN.hpp>
#include <ResolveType.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <armnn/backends/Workload.hpp>
#include <armnn/backends/WorkloadData.hpp>
#include <armnn/backends/WorkloadFactory.hpp>
#include <DataTypeUtils.hpp>
#include <armnnTestUtils/TensorCopyUtils.hpp>
#include <armnnTestUtils/WorkloadTestUtils.hpp>
#include <armnnTestUtils/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,
const armnn::ITensorHandleFactory& tensorHandleFactory,
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);
std::vector<T> input = ConvertToDataType<ArmnnType>(values, inputTensorInfo);
std::vector<T> expectedOutput = ConvertToDataType<ArmnnType>(outValues, inputTensorInfo);
std::vector<T> actualOutput(outputTensorInfo.GetNumElements());
std::unique_ptr<armnn::ITensorHandle> inputHandle = tensorHandleFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = tensorHandleFactory.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.data());
workload->PostAllocationConfigure();
ExecuteWorkload(*workload, memoryManager);
CopyDataFromITensorHandle(actualOutput.data(), outputHandle.get());
return LayerTestResult<T, NumDims>(actualOutput,
expectedOutput,
outputHandle->GetShape(),
outputTensorInfo.GetShape());
}
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,
const armnn::ITensorHandleFactory& tensorHandleFactory,
float quantScale = 1.0f,
int quantOffset = 0)
{
return ElementwiseUnaryTestHelper<NumDims, ArmnnType>(
workloadFactory,
memoryManager,
op,
shape,
values,
quantScale,
quantOffset,
outShape,
outValues,
tensorHandleFactory,
quantScale,
quantOffset);
}
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