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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "LayerTestResult.hpp"
#include <ResolveType.hpp>
#include <armnn/ArmNN.hpp>
#include <armnn/backends/IBackendInternal.hpp>
#include <backendsCommon/WorkloadFactory.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,
std::size_t InputDim,
std::size_t OutputDim,
typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, OutputDim> BatchToSpaceNdHelper(
armnn::IWorkloadFactory &workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager,
const armnn::DataLayout& dataLayout,
const unsigned int *inputShape,
const std::vector<float> &inputData,
const std::vector<unsigned int> &blockShape,
const std::vector<std::pair<unsigned int, unsigned int>> &crops,
const unsigned int *outputShape,
const std::vector<float> &outputData,
float scale = 1.0f,
int32_t offset = 0)
{
boost::ignore_unused(memoryManager);
armnn::TensorInfo inputTensorInfo(InputDim, inputShape, ArmnnType);
armnn::TensorInfo outputTensorInfo(OutputDim, outputShape, ArmnnType);
inputTensorInfo.SetQuantizationScale(scale);
inputTensorInfo.SetQuantizationOffset(offset);
outputTensorInfo.SetQuantizationScale(scale);
outputTensorInfo.SetQuantizationOffset(offset);
auto input = MakeTensor<T, InputDim>(inputTensorInfo, ConvertToDataType<ArmnnType>(inputData, inputTensorInfo));
LayerTestResult<T, OutputDim> result(outputTensorInfo);
result.outputExpected = MakeTensor<T, OutputDim>(outputTensorInfo,
ConvertToDataType<ArmnnType>(outputData, outputTensorInfo));
std::unique_ptr<armnn::ITensorHandle> inputHandle = workloadFactory.CreateTensorHandle(inputTensorInfo);
std::unique_ptr<armnn::ITensorHandle> outputHandle = workloadFactory.CreateTensorHandle(outputTensorInfo);
armnn::BatchToSpaceNdQueueDescriptor data;
data.m_Parameters.m_DataLayout = dataLayout;
data.m_Parameters.m_BlockShape = blockShape;
data.m_Parameters.m_Crops = crops;
armnn::WorkloadInfo info;
AddInputToWorkload(data, info, inputTensorInfo, inputHandle.get());
AddOutputToWorkload(data, info, outputTensorInfo, outputHandle.get());
std::unique_ptr<armnn::IWorkload> workload = workloadFactory.CreateBatchToSpaceNd(data, info);
inputHandle->Allocate();
outputHandle->Allocate();
CopyDataToITensorHandle(inputHandle.get(), input.origin());
workload->PostAllocationConfigure();
workload->Execute();
CopyDataFromITensorHandle(&result.output[0][0][0][0], outputHandle.get());
return result;
}
} // anonymous namespace
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest1(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 2, 2, 1};
const unsigned int outputShape[] = {1, 4, 4, 1};
std::vector<float> input({
// Batch 0, Height 0, Width (2) x Channel (1)
1.0f, 3.0f,
// Batch 0, Height 1, Width (2) x Channel (1)
9.0f, 11.0f,
// Batch 1, Height 0, Width (2) x Channel (1)
2.0f, 4.0f,
// Batch 1, Height 1, Width (2) x Channel (1)
10.0f, 12.0f,
// Batch 2, Height 0, Width (2) x Channel (1)
5.0f, 7.0f,
// Batch 2, Height 1, Width (2) x Channel (1)
13.0f, 15.0f,
// Batch 3, Height 0, Width (2) x Channel (3)
6.0f, 8.0f,
// Batch 3, Height 1, Width (2) x Channel (1)
14.0f, 16.0f
});
std::vector<float> expectedOutput({
1.0f, 2.0f, 3.0f, 4.0f,
5.0f, 6.0f, 7.0f, 8.0f,
9.0f, 10.0f, 11.0f, 12.0f,
13.0f, 14.0f, 15.0f, 16.0f
});
std::vector<unsigned int> blockShape {2, 2};
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NHWC, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest2(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 1, 1, 1};
const unsigned int outputShape[] = {1, 2, 2, 1};
std::vector<float> input({
// Batch 0, Height 0, Width (2) x Channel (1)
1.0f, 2.0f, 3.0f, 4.0f
});
std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NHWC, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest3(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 1, 1, 3};
const unsigned int outputShape[] = {1, 2, 2, 3};
std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});
std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NHWC, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest4(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {8, 1, 3, 1};
const unsigned int outputShape[] = {2, 2, 4, 1};
std::vector<float> input({
0.0f, 1.0f, 3.0f,
0.0f, 9.0f, 11.0f,
0.0f, 2.0f, 4.0f,
0.0f, 10.0f, 12.0f,
0.0f, 5.0f, 7.0f,
0.0f, 13.0f, 15.0f,
0.0f, 6.0f, 8.0f,
0.0f, 14.0f, 16.0f
});
std::vector<float> expectedOutput({
1.0f, 2.0f, 3.0f, 4.0f,
5.0f, 6.0f, 7.0f, 8.0f,
9.0f, 10.0f, 11.0f, 12.0f,
13.0f, 14.0f, 15.0f, 16.0f
});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NHWC, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest5(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 2, 2, 1};
const unsigned int outputShape[] = {1, 4, 4, 1};
std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16});
std::vector<float> expectedOutput({1, 5, 2, 6, 9, 13, 10, 14, 3, 7, 4, 8, 11, 15, 12, 16});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager, armnn::DataLayout::NHWC, inputShape,
input, blockShape, crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest6(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 1, 1, 1};
const unsigned int outputShape[] = {1, 2, 2, 1};
std::vector<float> input({
// Batch 0, Height 0, Width (2) x Channel (1)
1, 2, 3, 4
});
std::vector<float> expectedOutput({1, 2, 3, 4});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NHWC, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNhwcTest7(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 1, 1, 3};
const unsigned int outputShape[] = {1, 2, 2, 3};
std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
std::vector<float> expectedOutput({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NHWC, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest1(
armnn::IWorkloadFactory &workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 3, 1, 1};
const unsigned int outputShape[] = {1, 3, 2, 2};
std::vector<float> input({1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f, 11.0f, 12.0f});
std::vector<float> expectedOutput({
// Batch 0, Channel 0, Height (2) x Width (2)
1.0f, 4.0f,
7.0f, 10.0f,
// Batch 0, Channel 1, Height (2) x Width (2)
2.0f, 5.0f,
8.0f, 11.0f,
// Batch 0, Channel 2, Height (2) x Width (2)
3.0f, 6.0f,
9.0f, 12.0f,
});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest2(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 1, 1, 1};
const unsigned int outputShape[] = {1, 1, 2, 2};
std::vector<float> input({
// Batch 0, Height 0, Width (2) x Channel (1)
1.0f, 2.0f, 3.0f, 4.0f
});
std::vector<float> expectedOutput({1.0f, 2.0f, 3.0f, 4.0f});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest3(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 3, 1, 1};
const unsigned int outputShape[] = {1, 3, 2, 2};
std::vector<float> input({1.0f, 3.0f, 5.0f, 7.0f, 9.0f, 11.0f, 2.0f, 4.0f, 6.0f, 8.0f, 10.0f, 12.0f});
std::vector<float> expectedOutput({
// Batch 0, Channel 0, Height (2) x Width (2)
1.0f, 7.0f,
2.0f, 8.0f,
// Batch 0, Channel 1, Height (2) x Width (2)
3.0f, 9.0f,
4.0f, 10.0f,
// Batch 0, Channel 2, Height (2) x Width (2)
5.0f, 11.0f,
6.0f, 12.0f,
});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest4(
armnn::IWorkloadFactory &workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 3, 1, 1};
const unsigned int outputShape[] = {1, 3, 2, 2};
std::vector<float> input({1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12});
std::vector<float> expectedOutput({
// Batch 0, Channel 0, Height (2) x Width (2)
1, 4,
7, 10,
// Batch 0, Channel 1, Height (2) x Width (2)
2, 5,
8, 11,
// Batch 0, Channel 2, Height (2) x Width (2)
3, 6,
9, 12,
});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest5(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 1, 1, 1};
const unsigned int outputShape[] = {1, 1, 2, 2};
std::vector<float> input({
// Batch 0, Height 0, Width (2) x Channel (1)
1, 2, 3, 4
});
std::vector<float> expectedOutput({1, 2, 3, 4});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest6(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {4, 3, 1, 1};
const unsigned int outputShape[] = {1, 3, 2, 2};
std::vector<float> input({1, 3, 5, 7, 9, 11, 2, 4, 6, 8, 10, 12});
std::vector<float> expectedOutput({
// Batch 0, Channel 0, Height (2) x Width (2)
1, 7,
2, 8,
// Batch 0, Channel 1, Height (2) x Width (2)
3, 9,
4, 10,
// Batch 0, Channel 2, Height (2) x Width (2)
5, 11,
6, 12,
});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {0, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
LayerTestResult<T, 4> BatchToSpaceNdNchwTest7(
armnn::IWorkloadFactory& workloadFactory,
const armnn::IBackendInternal::IMemoryManagerSharedPtr& memoryManager)
{
const unsigned int inputShape[] = {8, 1, 1, 3};
const unsigned int outputShape[] = {2, 1, 2, 4};
std::vector<float> input({
0, 1, 3, 0, 9, 11,
0, 2, 4, 0, 10, 12,
0, 5, 7, 0, 13, 15,
0, 6, 8, 0, 14, 16
});
std::vector<float> expectedOutput({
1, 2, 3, 4,
5, 6, 7, 8,
9, 10, 11, 12,
13, 14, 15, 16
});
std::vector<unsigned int> blockShape({2, 2});
std::vector<std::pair<unsigned int, unsigned int>> crops = {{0, 0}, {2, 0}};
return BatchToSpaceNdHelper<ArmnnType, 4, 4>(workloadFactory, memoryManager,
armnn::DataLayout::NCHW, inputShape, input, blockShape,
crops, outputShape, expectedOutput);
}