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//
// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include "CommonTestUtils.hpp"
#include <armnn/INetwork.hpp>
#include <ResolveType.hpp>
#include <doctest/doctest.h>
namespace{
armnn::INetworkPtr CreateChannelShuffleNetwork(const armnn::TensorInfo& inputInfo,
const armnn::TensorInfo& outputInfo,
const armnn::ChannelShuffleDescriptor& descriptor)
{
armnn::INetworkPtr net(armnn::INetwork::Create());
armnn::IConnectableLayer* inputLayer = net->AddInputLayer(0);
armnn::IConnectableLayer* channelShuffleLayer = net->AddChannelShuffleLayer(descriptor, "channelShuffle");
armnn::IConnectableLayer* outputLayer = net->AddOutputLayer(0, "output");
Connect(inputLayer, channelShuffleLayer, inputInfo, 0, 0);
Connect(channelShuffleLayer, outputLayer, outputInfo, 0, 0);
return net;
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void ChannelShuffleEndToEnd(const std::vector<BackendId>& backends)
{
armnn::TensorInfo inputInfo({ 3,12 }, ArmnnType);
armnn::TensorInfo outputInfo({ 3,12 }, ArmnnType);
inputInfo.SetQuantizationScale(1.0f);
inputInfo.SetQuantizationOffset(0);
inputInfo.SetConstant(true);
outputInfo.SetQuantizationScale(1.0f);
outputInfo.SetQuantizationOffset(0);
// Creates structures for input & output.
std::vector<T> inputData{
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23,
24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35
};
std::vector<T> expectedOutput{
0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11,
12, 16, 20, 13, 17, 21, 14, 18, 22, 15, 19, 23,
24, 28, 32, 25, 29, 33, 26, 30, 34, 27, 31, 35
};
ChannelShuffleDescriptor descriptor;
descriptor.m_Axis = 1;
descriptor.m_NumGroups = 3;
// Builds up the structure of the network
armnn::INetworkPtr net = CreateChannelShuffleNetwork(inputInfo, outputInfo, descriptor);
CHECK(net);
std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }};
std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }};
EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends);
}
} // anonymous namespace
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