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//
// Copyright © 2019 Arm Ltd. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <ResolveType.hpp>
#include <armnnUtils/QuantizeHelper.hpp>
#include <armnnTestUtils/DataLayoutUtils.hpp>
namespace
{
armnn::INetworkPtr CreateDepthToSpaceNetwork(const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& outputInfo,
const armnn::DepthToSpaceDescriptor& descriptor)
{
using namespace armnn;
INetworkPtr network(INetwork::Create());
IConnectableLayer* input = network->AddInputLayer(0, "input");
IConnectableLayer* depthToSpace = network->AddDepthToSpaceLayer(descriptor, "depthToSpace");
IConnectableLayer* output = network->AddOutputLayer(0, "output");
Connect(input, depthToSpace, inputInfo, 0, 0);
Connect(depthToSpace, output, outputInfo, 0, 0);
return network;
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void DepthToSpaceEndToEndImpl(const std::vector<armnn::BackendId>& backends,
const DepthToSpaceDescriptor& descriptor,
const armnn::TensorShape& nhwcInputShape,
const armnn::TensorShape& nhwcOutputShape,
const std::vector<float>& floatInputData,
const std::vector<float>& floatExpectedOutputData)
{
using namespace armnn;
TensorInfo inputInfo(nhwcInputShape, ArmnnType);
inputInfo.SetConstant(true);
TensorInfo outputInfo(nhwcOutputShape, ArmnnType);
constexpr float qScale = 0.25f;
constexpr int32_t qOffset = 128;
// Set quantization parameters for quantized types
if (IsQuantizedType<T>())
{
inputInfo.SetQuantizationScale(qScale);
inputInfo.SetQuantizationOffset(qOffset);
outputInfo.SetQuantizationScale(qScale);
outputInfo.SetQuantizationOffset(qOffset);
}
std::vector<T> inputData = armnnUtils::QuantizedVector<T>(floatInputData, qScale, qOffset);
std::vector<T> expectedOutputData = armnnUtils::QuantizedVector<T>(floatExpectedOutputData, qScale, qOffset);
// Permute tensors from NHWC to NCHW (if needed)
if (descriptor.m_DataLayout == DataLayout::NCHW)
{
PermuteTensorNhwcToNchw(inputInfo, inputData);
PermuteTensorNhwcToNchw(outputInfo, expectedOutputData);
}
INetworkPtr network = CreateDepthToSpaceNetwork(inputInfo, outputInfo, descriptor);
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(std::move(network),
{ { 0, inputData } },
{ { 0, expectedOutputData } },
backends);
}
} // anonymous namespace
template<armnn::DataType ArmnnType>
void DepthToSpaceEndToEnd(const std::vector<armnn::BackendId>& defaultBackends,
armnn::DataLayout dataLayout)
{
using namespace armnn;
TensorShape inputShape = { 2, 2, 2, 4 };
TensorShape outputShape = { 2, 4, 4, 1 };
std::vector<float> inputData =
{
1.f, 2.f, 3.f, 4.f,
5.f, 6.f, 7.f, 8.f,
9.f, 10.f, 11.f, 12.f,
13.f, 14.f, 15.f, 16.f,
17.f, 18.f, 19.f, 20.f,
21.f, 22.f, 23.f, 24.f,
25.f, 26.f, 27.f, 28.f,
29.f, 30.f, 31.f, 32.f
};
std::vector<float> expectedOutputData =
{
1.f, 2.f, 5.f, 6.f,
3.f, 4.f, 7.f, 8.f,
9.f, 10.f, 13.f, 14.f,
11.f, 12.f, 15.f, 16.f,
17.f, 18.f, 21.f, 22.f,
19.f, 20.f, 23.f, 24.f,
25.f, 26.f, 29.f, 30.f,
27.f, 28.f, 31.f, 32.f
};
DepthToSpaceEndToEndImpl<ArmnnType>(defaultBackends,
DepthToSpaceDescriptor(2, dataLayout),
inputShape,
outputShape,
inputData,
expectedOutputData);
}
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