blob: c0a779c0e639376f7db25dba5fd0da44208cca73 [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "LayerTestResult.hpp"
#include <ResolveType.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/Workload.hpp>
#include <backendsCommon/WorkloadData.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
#include <backendsCommon/test/TensorCopyUtils.hpp>
#include <backendsCommon/test/WorkloadTestUtils.hpp>
#include <test/TensorHelpers.hpp>
#include <memory>
template<typename DescriptorType>
std::unique_ptr<armnn::IWorkload> CreateWorkload(
const armnn::IWorkloadFactory& workloadFactory,
const armnn::WorkloadInfo& info,
const DescriptorType& descriptor)
{
return CreateWorkload(workloadFactory, info, descriptor);
}
template <std::size_t NumDims,
typename Descriptor,
armnn::DataType ArmnnTypeInput,
armnn::DataType ArmnnTypeOutput,
typename TInput = armnn::ResolveType<ArmnnTypeInput>,
typename TOutput = armnn::ResolveType<ArmnnTypeOutput>>
LayerTestResult<TOutput, NumDims> ElementwiseTestHelper(
armnn::IWorkloadFactory & workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,
const unsigned int shape0[NumDims],
std::vector<TInput> values0,
float quantScale0,
int quantOffset0,
const unsigned int shape1[NumDims],
std::vector<TInput> values1,
float quantScale1,
int quantOffset1,
const unsigned int outShape[NumDims],
std::vector<TOutput> outValues,
float outQuantScale,
int outQuantOffset)
{
armnn::TensorInfo inputTensorInfo0{NumDims, shape0, ArmnnTypeInput};
armnn::TensorInfo inputTensorInfo1{NumDims, shape1, ArmnnTypeInput};
armnn::TensorInfo outputTensorInfo{NumDims, outShape, ArmnnTypeOutput};
auto input0 = MakeTensor<TInput, NumDims>(inputTensorInfo0, values0);
auto input1 = MakeTensor<TInput, NumDims>(inputTensorInfo1, values1);
inputTensorInfo0.SetQuantizationScale(quantScale0);
inputTensorInfo0.SetQuantizationOffset(quantOffset0);
inputTensorInfo1.SetQuantizationScale(quantScale1);
inputTensorInfo1.SetQuantizationOffset(quantOffset1);
outputTensorInfo.SetQuantizationScale(outQuantScale);
outputTensorInfo.SetQuantizationOffset(outQuantOffset);
LayerTestResult<TOutput, NumDims> ret(outputTensorInfo);
if(ArmnnTypeOutput == armnn::DataType::Boolean)
{
ret.compareBoolean = true;
}
std::unique_ptr<armnn::ITensorHandle> inputHandle0 = workloadFactory.CreateTensorHandle(inputTensorInfo0);
std::unique_ptr<armnn::ITensorHandle> inputHandle1 = workloadFactory.CreateTensorHandle(inputTensorInfo1);
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
Descriptor data;
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, inputTensorInfo0, inputHandle0.get());
AddInputToWorkload(data, info, inputTensorInfo1, inputHandle1.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
auto workload = CreateWorkload<Descriptor>(workloadFactory, info, data);
inputHandle0->Allocate();
inputHandle1->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle0.get(), input0.origin());
CopyDataToITensorHandle(inputHandle1.get(), input1.origin());
workload->PostAllocationConfigure();
ExecuteWorkload(*workload, memoryManager);
CopyDataFromITensorHandle(ret.output.origin(), outputHandle.get());
ret.outputExpected = MakeTensor<TOutput, NumDims>(outputTensorInfo, outValues);
return ret;
}
template <std::size_t NumDims,
typename Descriptor,
armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, NumDims> ElementwiseTestHelper(
armnn::IWorkloadFactory & workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,
const unsigned int shape0[NumDims],
std::vector<T> values0,
float quantScale0,
int quantOffset0,
const unsigned int shape1[NumDims],
std::vector<T> values1,
float quantScale1,
int quantOffset1,
const unsigned int outShape[NumDims],
std::vector<T> outValues,
float outQuantScale,
int outQuantOffset)
{
return ElementwiseTestHelper<NumDims, Descriptor, ArmnnType, ArmnnType>(
workloadFactory,
memoryManager,
shape0,
values0,
quantScale0,
quantOffset0,
shape1,
values1,
quantScale1,
quantOffset1,
outShape,
outValues,
outQuantScale,
outQuantOffset);
}
template <std::size_t NumDims,
typename Descriptor,
armnn::DataType ArmnnTypeInput,
armnn::DataType ArmnnTypeOutput,
typename TInput = armnn::ResolveType<ArmnnTypeInput>,
typename TOutput = armnn::ResolveType<ArmnnTypeOutput>>
LayerTestResult<TOutput, NumDims> ElementwiseTestHelper(
armnn::IWorkloadFactory & workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,
const unsigned int shape0[NumDims],
std::vector<TInput> values0,
const unsigned int shape1[NumDims],
std::vector<TInput> values1,
const unsigned int outShape[NumDims],
std::vector<TOutput> outValues,
float quantScale = 1.0f,
int quantOffset = 0)
{
return ElementwiseTestHelper<NumDims, Descriptor, ArmnnTypeInput, ArmnnTypeOutput>(
workloadFactory,
memoryManager,
shape0,
values0,
quantScale,
quantOffset,
shape1,
values1,
quantScale,
quantOffset,
outShape,
outValues,
quantScale,
quantOffset);
}
template <std::size_t NumDims,
typename Descriptor,
armnn::DataType ArmnnType,
typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, NumDims> ElementwiseTestHelper(
armnn::IWorkloadFactory & workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr & memoryManager,
const unsigned int shape0[NumDims],
std::vector<T> values0,
const unsigned int shape1[NumDims],
std::vector<T> values1,
const unsigned int outShape[NumDims],
std::vector<T> outValues,
float quantScale = 1.0f,
int quantOffset = 0)
{
return ElementwiseTestHelper<NumDims, Descriptor, ArmnnType, ArmnnType>(
workloadFactory,
memoryManager,
shape0,
values0,
shape1,
values1,
outShape,
outValues,
quantScale,
quantOffset);
}