blob: af3f5d26187828888d4b6647c9d54e27f8d0fa08 [file] [log] [blame]
//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "WorkloadTestUtils.hpp"
#include <armnn/ArmNN.hpp>
#include <armnn/Tensor.hpp>
#include <armnn/TypesUtils.hpp>
#include <backendsCommon/CpuTensorHandle.hpp>
#include <backendsCommon/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.hpp>
#include <test/TensorHelpers.hpp>
template<typename T>
LayerTestResult<T, 4> SpaceToDepthTestImpl(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
armnn::TensorInfo& inputTensorInfo,
armnn::TensorInfo& outputTensorInfo,
std::vector<float>& inputData,
std::vector<float>& outputExpectedData,
armnn::SpaceToDepthQueueDescriptor descriptor,
const float qScale = 1.0f,
const int32_t qOffset = 0)
{
const armnn::PermutationVector NHWCToNCHW = {0, 2, 3, 1};
if (descriptor.m_Parameters.m_DataLayout == armnn::DataLayout::NCHW)
{
inputTensorInfo = armnnUtils::Permuted(inputTensorInfo, NHWCToNCHW);
outputTensorInfo = armnnUtils::Permuted(outputTensorInfo, NHWCToNCHW);
std::vector<float> inputTmp(inputData.size());
armnnUtils::Permute(inputTensorInfo.GetShape(), NHWCToNCHW,
inputData.data(), inputTmp.data(), sizeof(float));
inputData = inputTmp;
std::vector<float> outputTmp(outputExpectedData.size());
armnnUtils::Permute(outputTensorInfo.GetShape(), NHWCToNCHW,
outputExpectedData.data(), outputTmp.data(), sizeof(float));
outputExpectedData = outputTmp;
}
if(armnn::IsQuantizedType<T>())
{
inputTensorInfo.SetQuantizationScale(qScale);
inputTensorInfo.SetQuantizationOffset(qOffset);
outputTensorInfo.SetQuantizationScale(qScale);
outputTensorInfo.SetQuantizationOffset(qOffset);
}
boost::multi_array<T, 4> input = MakeTensor<T, 4>(inputTensorInfo, QuantizedVector<T>(qScale, qOffset, inputData));
LayerTestResult<T, 4> ret(outputTensorInfo);
ret.outputExpected = MakeTensor<T, 4>(outputTensorInfo, QuantizedVector<T>(qScale, qOffset, outputExpectedData));
std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
armnn::WorkloadInfo info;
AddInputToWorkload(descriptor, info, inputTensorInfo, inputHandle.get());
AddOutputToWorkload(descriptor, info, outputTensorInfo, outputHandle.get());
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateSpaceToDepth(descriptor, info);
inputHandle->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), &input[0][0][0][0]);
workload->Execute();
CopyDataFromITensorHandle(&ret.output[0][0][0][0], outputHandle.get());
return ret;
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> SpaceToDepthSimpleTest1(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
armnn::DataLayout dataLayout = armnn::DataLayout::NHWC)
{
unsigned int inputShape[] = {1, 2, 2, 1};
unsigned int outputShape[] = {1, 1, 1, 4};
std::vector<float> input = std::vector<float>(
{
1.0f, 2.0f, 3.0f, 4.0f
});
std::vector<float> outputExpected = std::vector<float>(
{
1.0f, 2.0f, 3.0f, 4.0f
});
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
armnn::SpaceToDepthQueueDescriptor desc;
desc.m_Parameters.m_DataLayout = dataLayout;
desc.m_Parameters.m_BlockSize = 2;
inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
return SpaceToDepthTestImpl<T>(
workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> SpaceToDepthSimpleTest2(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
armnn::DataLayout dataLayout = armnn::DataLayout::NHWC)
{
unsigned int inputShape[] = {1, 2, 2, 2};
unsigned int outputShape[] = {1, 1, 1, 8};
std::vector<float> input = std::vector<float>(
{
1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
});
std::vector<float> outputExpected = std::vector<float>(
{
1.4f, 2.3f, 3.2f, 4.1f, 5.4f, 6.3f, 7.2f, 8.1f
});
armnn::TensorInfo inputTensorInfo;
armnn::TensorInfo outputTensorInfo;
armnn::SpaceToDepthQueueDescriptor desc;
desc.m_Parameters.m_DataLayout = dataLayout;
desc.m_Parameters.m_BlockSize = 2;
inputTensorInfo = armnn::TensorInfo(4, inputShape, ArmnnType);
outputTensorInfo = armnn::TensorInfo(4, outputShape, ArmnnType);
return SpaceToDepthTestImpl<T>(
workloadFactory, memoryManager, inputTensorInfo, outputTensorInfo, input, outputExpected, desc);
}