Teresa Charlin | 43baf50 | 2021-09-27 10:10:39 +0100 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2021 Arm Ltd and Contributors. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
| 5 | |
| 6 | #pragma once |
| 7 | |
Sadik Armagan | a097d2a | 2021-11-24 15:47:28 +0000 | [diff] [blame] | 8 | #include <CommonTestUtils.hpp> |
Teresa Charlin | 43baf50 | 2021-09-27 10:10:39 +0100 | [diff] [blame] | 9 | |
| 10 | #include <armnn/INetwork.hpp> |
| 11 | #include <ResolveType.hpp> |
| 12 | |
| 13 | #include <doctest/doctest.h> |
| 14 | |
| 15 | namespace{ |
| 16 | |
| 17 | armnn::INetworkPtr CreateChannelShuffleNetwork(const armnn::TensorInfo& inputInfo, |
| 18 | const armnn::TensorInfo& outputInfo, |
| 19 | const armnn::ChannelShuffleDescriptor& descriptor) |
| 20 | { |
| 21 | armnn::INetworkPtr net(armnn::INetwork::Create()); |
| 22 | |
| 23 | armnn::IConnectableLayer* inputLayer = net->AddInputLayer(0); |
| 24 | armnn::IConnectableLayer* channelShuffleLayer = net->AddChannelShuffleLayer(descriptor, "channelShuffle"); |
| 25 | armnn::IConnectableLayer* outputLayer = net->AddOutputLayer(0, "output"); |
| 26 | Connect(inputLayer, channelShuffleLayer, inputInfo, 0, 0); |
| 27 | Connect(channelShuffleLayer, outputLayer, outputInfo, 0, 0); |
| 28 | |
| 29 | return net; |
| 30 | } |
| 31 | |
| 32 | template<armnn::DataType ArmnnType, typename T = armnn::ResolveType<ArmnnType>> |
| 33 | void ChannelShuffleEndToEnd(const std::vector<BackendId>& backends) |
| 34 | { |
| 35 | armnn::TensorInfo inputInfo({ 3,12 }, ArmnnType); |
| 36 | armnn::TensorInfo outputInfo({ 3,12 }, ArmnnType); |
| 37 | |
| 38 | inputInfo.SetQuantizationScale(1.0f); |
| 39 | inputInfo.SetQuantizationOffset(0); |
Cathal Corbett | 5b8093c | 2021-10-22 11:12:07 +0100 | [diff] [blame] | 40 | inputInfo.SetConstant(true); |
Teresa Charlin | 43baf50 | 2021-09-27 10:10:39 +0100 | [diff] [blame] | 41 | outputInfo.SetQuantizationScale(1.0f); |
| 42 | outputInfo.SetQuantizationOffset(0); |
| 43 | |
| 44 | // Creates structures for input & output. |
| 45 | std::vector<T> inputData{ |
| 46 | 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, |
| 47 | 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, |
| 48 | 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35 |
| 49 | }; |
| 50 | |
| 51 | std::vector<T> expectedOutput{ |
| 52 | 0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11, |
| 53 | 12, 16, 20, 13, 17, 21, 14, 18, 22, 15, 19, 23, |
| 54 | 24, 28, 32, 25, 29, 33, 26, 30, 34, 27, 31, 35 |
| 55 | }; |
| 56 | ChannelShuffleDescriptor descriptor; |
| 57 | descriptor.m_Axis = 1; |
| 58 | descriptor.m_NumGroups = 3; |
| 59 | |
| 60 | // Builds up the structure of the network |
| 61 | armnn::INetworkPtr net = CreateChannelShuffleNetwork(inputInfo, outputInfo, descriptor); |
| 62 | |
| 63 | CHECK(net); |
| 64 | |
| 65 | std::map<int, std::vector<T>> inputTensorData = {{ 0, inputData }}; |
| 66 | std::map<int, std::vector<T>> expectedOutputData = {{ 0, expectedOutput }}; |
| 67 | |
| 68 | EndToEndLayerTestImpl<ArmnnType, ArmnnType>(move(net), inputTensorData, expectedOutputData, backends); |
| 69 | } |
| 70 | |
| 71 | } // anonymous namespace |