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//
// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#pragma once
#include <CommonTestUtils.hpp>
#include <armnn/INetwork.hpp>
#include <armnn/TypesUtils.hpp>
#include <ResolveType.hpp>
#include <doctest/doctest.h>
namespace
{
armnn::INetworkPtr CreateRankNetwork(const armnn::TensorInfo& inputTensorInfo,
const armnn::TensorInfo& outputTensorInfo)
{
armnn::INetworkPtr network(armnn::INetwork::Create());
armnn::IConnectableLayer* inputLayer = network->AddInputLayer(0, "Input");
armnn::IConnectableLayer* rankLayer = network->AddRankLayer("Rank");
armnn::IConnectableLayer* outputLayer = network->AddOutputLayer(0, "Output");
Connect(inputLayer, rankLayer, inputTensorInfo, 0, 0);
Connect(rankLayer, outputLayer, outputTensorInfo, 0, 0);
return network;
}
template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
void RankEndToEnd(const std::vector<armnn::BackendId>& backends)
{
using namespace armnn;
std::vector<float> floatInputData{
1, 2, 3, 4, 5,
11, 12, 13, 14, 15,
21, 22, 23, 24, 25
};
std::vector<T> inputData = armnnUtils::QuantizedVector<T>(floatInputData);
std::vector<int32_t> expectedOutputData{ 4 };
TensorInfo inputInfo ({ 1, 1, 5, 3 }, ArmnnType, 0.0f, 0, true);
TensorShape outputShape (Dimensionality::Scalar);
TensorInfo outputInfo(outputShape, DataType::Signed32);
armnn::INetworkPtr network = CreateRankNetwork(inputInfo, outputInfo);
CHECK(network);
std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }};
std::map<int, std::vector<int32_t>> expectedOutputTensorData = {{ 0, expectedOutputData }};
EndToEndLayerTestImpl<ArmnnType, DataType::Signed32>(move(network),
inputTensorData,
expectedOutputTensorData,
backends);
}
} // anonymous namespace
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