Teresa Charlin | 2e3f4d2 | 2020-07-29 14:29:20 +0100 | [diff] [blame] | 1 | // |
| 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 | |
| 15 | namespace |
| 16 | { |
| 17 | |
| 18 | armnn::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 | |
| 33 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 34 | void 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 |