blob: a67bd469824e434b50e44e094d0c8a15ca229e1a [file] [log] [blame]
Teresa Charlin2e3f4d22020-07-29 14:29:20 +01001//
2// Copyright © 2020 Arm Ltd and Contributors. All rights reserved.
3// SPDX-License-Identifier: MIT
4//
5
6#pragma once
7
8#include "CommonTestUtils.hpp"
9
10#include <armnn/INetwork.hpp>
11#include <armnn/TypesUtils.hpp>
12
13#include <ResolveType.hpp>
14
15namespace
16{
17
18armnn::INetworkPtr CreateRankNetwork(const armnn::TensorInfo& inputTensorInfo,
19 const armnn::TensorInfo& outputTensorInfo)
20{
21 armnn::INetworkPtr network(armnn::INetwork::Create());
22
23 armnn::IConnectableLayer* inputLayer = network->AddInputLayer(0, "Input");
24 armnn::IConnectableLayer* rankLayer = network->AddRankLayer("Rank");
25 armnn::IConnectableLayer* outputLayer = network->AddOutputLayer(0, "Output");
26
27 Connect(inputLayer, rankLayer, inputTensorInfo, 0, 0);
28 Connect(rankLayer, outputLayer, outputTensorInfo, 0, 0);
29
30 return network;
31}
32
33template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>>
34void RankEndToEnd(const std::vector<armnn::BackendId>& backends)
35{
36 using namespace armnn;
37
38 std::vector<float> floatInputData{
39 1, 2, 3, 4, 5,
40 11, 12, 13, 14, 15,
41 21, 22, 23, 24, 25
42 };
43 std::vector<T> inputData = armnnUtils::QuantizedVector<T>(floatInputData);
44
45 std::vector<int32_t> expectedOutputData{ 4 };
46
47 TensorInfo inputInfo ({ 1, 1, 5, 3 }, ArmnnType);
48 TensorShape outputShape (Dimensionality::Scalar);
49 TensorInfo outputInfo(outputShape, DataType::Signed32);
50
51 armnn::INetworkPtr network = CreateRankNetwork(inputInfo, outputInfo);
52
53 BOOST_TEST_CHECKPOINT("create a network");
54
55 std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }};
56 std::map<int, std::vector<int32_t>> expectedOutputTensorData = {{ 0, expectedOutputData }};
57
58 EndToEndLayerTestImpl<ArmnnType, DataType::Signed32>(move(network),
59 inputTensorData,
60 expectedOutputTensorData,
61 backends);
62}
63
64} // anonymous namespace