telsoa01 | 4fcda01 | 2018-03-09 14:13:49 +0000 | [diff] [blame^] | 1 | // |
| 2 | // Copyright © 2017 Arm Ltd. All rights reserved. |
| 3 | // See LICENSE file in the project root for full license information. |
| 4 | // |
| 5 | #include <iostream> |
| 6 | #include <chrono> |
| 7 | #include <vector> |
| 8 | #include <array> |
| 9 | #include <boost/log/trivial.hpp> |
| 10 | |
| 11 | #include "armnn/ArmNN.hpp" |
| 12 | #include "armnn/Utils.hpp" |
| 13 | #include "armnn/INetwork.hpp" |
| 14 | #include "armnnCaffeParser/ICaffeParser.hpp" |
| 15 | #include "../Cifar10Database.hpp" |
| 16 | #include "../InferenceTest.hpp" |
| 17 | #include "../InferenceModel.hpp" |
| 18 | |
| 19 | using namespace std; |
| 20 | using namespace std::chrono; |
| 21 | using namespace armnn::test; |
| 22 | |
| 23 | int main(int argc, char* argv[]) |
| 24 | { |
| 25 | #ifdef NDEBUG |
| 26 | armnn::LogSeverity level = armnn::LogSeverity::Info; |
| 27 | #else |
| 28 | armnn::LogSeverity level = armnn::LogSeverity::Debug; |
| 29 | #endif |
| 30 | |
| 31 | try |
| 32 | { |
| 33 | // Configure logging for both the ARMNN library and this test program |
| 34 | armnn::ConfigureLogging(true, true, level); |
| 35 | armnnUtils::ConfigureLogging(boost::log::core::get().get(), true, true, level); |
| 36 | |
| 37 | namespace po = boost::program_options; |
| 38 | |
| 39 | armnn::Compute computeDevice; |
| 40 | std::string modelDir; |
| 41 | std::string dataDir; |
| 42 | |
| 43 | po::options_description desc("Options"); |
| 44 | try |
| 45 | { |
| 46 | // Add generic options needed for all inference tests |
| 47 | desc.add_options() |
| 48 | ("help", "Display help messages") |
| 49 | ("model-dir,m", po::value<std::string>(&modelDir)->required(), |
| 50 | "Path to directory containing the Cifar10 model file") |
| 51 | ("compute,c", po::value<armnn::Compute>(&computeDevice)->default_value(armnn::Compute::CpuAcc), |
| 52 | "Which device to run layers on by default. Possible choices: CpuAcc, CpuRef, GpuAcc") |
| 53 | ("data-dir,d", po::value<std::string>(&dataDir)->required(), |
| 54 | "Path to directory containing the Cifar10 test data"); |
| 55 | } |
| 56 | catch (const std::exception& e) |
| 57 | { |
| 58 | // Coverity points out that default_value(...) can throw a bad_lexical_cast, |
| 59 | // and that desc.add_options() can throw boost::io::too_few_args. |
| 60 | // They really won't in any of these cases. |
| 61 | BOOST_ASSERT_MSG(false, "Caught unexpected exception"); |
| 62 | std::cerr << "Fatal internal error: " << e.what() << std::endl; |
| 63 | return 1; |
| 64 | } |
| 65 | |
| 66 | po::variables_map vm; |
| 67 | |
| 68 | try |
| 69 | { |
| 70 | po::store(po::parse_command_line(argc, argv, desc), vm); |
| 71 | |
| 72 | if (vm.count("help")) |
| 73 | { |
| 74 | std::cout << desc << std::endl; |
| 75 | return 1; |
| 76 | } |
| 77 | |
| 78 | po::notify(vm); |
| 79 | } |
| 80 | catch (po::error& e) |
| 81 | { |
| 82 | std::cerr << e.what() << std::endl << std::endl; |
| 83 | std::cerr << desc << std::endl; |
| 84 | return 1; |
| 85 | } |
| 86 | |
| 87 | if (!ValidateDirectory(modelDir)) |
| 88 | { |
| 89 | return 1; |
| 90 | } |
| 91 | string modelPath = modelDir + "cifar10_full_iter_60000.caffemodel"; |
| 92 | |
| 93 | // Create runtime |
| 94 | armnn::IRuntimePtr runtime(armnn::IRuntime::Create(computeDevice)); |
| 95 | |
| 96 | // Load networks |
| 97 | armnn::Status status; |
| 98 | struct Net |
| 99 | { |
| 100 | Net(armnn::NetworkId netId, |
| 101 | const std::pair<armnn::LayerBindingId, armnn::TensorInfo>& in, |
| 102 | const std::pair<armnn::LayerBindingId, armnn::TensorInfo>& out) |
| 103 | : m_Network(netId) |
| 104 | , m_InputBindingInfo(in) |
| 105 | , m_OutputBindingInfo(out) |
| 106 | {} |
| 107 | |
| 108 | armnn::NetworkId m_Network; |
| 109 | std::pair<armnn::LayerBindingId, armnn::TensorInfo> m_InputBindingInfo; |
| 110 | std::pair<armnn::LayerBindingId, armnn::TensorInfo> m_OutputBindingInfo; |
| 111 | }; |
| 112 | std::vector<Net> networks; |
| 113 | |
| 114 | armnnCaffeParser::ICaffeParserPtr parser(armnnCaffeParser::ICaffeParser::Create()); |
| 115 | |
| 116 | const int networksCount = 4; |
| 117 | for (int i = 0; i < networksCount; ++i) |
| 118 | { |
| 119 | // Create a network from a file on disk |
| 120 | armnn::INetworkPtr network = parser->CreateNetworkFromBinaryFile(modelPath.c_str(), {}, { "prob" }); |
| 121 | |
| 122 | // optimize the network |
| 123 | armnn::IOptimizedNetworkPtr optimizedNet(nullptr, nullptr); |
| 124 | try |
| 125 | { |
| 126 | optimizedNet = armnn::Optimize(*network, runtime->GetDeviceSpec()); |
| 127 | } |
| 128 | catch (armnn::Exception& e) |
| 129 | { |
| 130 | std::stringstream message; |
| 131 | message << "armnn::Exception ("<<e.what()<<") caught from optimize."; |
| 132 | BOOST_LOG_TRIVIAL(fatal) << message.str(); |
| 133 | return 1; |
| 134 | } |
| 135 | |
| 136 | // Load the network into the runtime |
| 137 | armnn::NetworkId networkId; |
| 138 | status = runtime->LoadNetwork(networkId, std::move(optimizedNet)); |
| 139 | if (status == armnn::Status::Failure) |
| 140 | { |
| 141 | BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to load network"; |
| 142 | return 1; |
| 143 | } |
| 144 | |
| 145 | networks.emplace_back(networkId, |
| 146 | parser->GetNetworkInputBindingInfo("data"), |
| 147 | parser->GetNetworkOutputBindingInfo("prob")); |
| 148 | } |
| 149 | |
| 150 | // Load a test case and test inference |
| 151 | if (!ValidateDirectory(dataDir)) |
| 152 | { |
| 153 | return 1; |
| 154 | } |
| 155 | Cifar10Database cifar10(dataDir); |
| 156 | |
| 157 | for (unsigned int i = 0; i < 3; ++i) |
| 158 | { |
| 159 | // Load test case data (including image data) |
| 160 | std::unique_ptr<Cifar10Database::TTestCaseData> testCaseData = cifar10.GetTestCaseData(i); |
| 161 | |
| 162 | // Test inference |
| 163 | std::vector<std::array<float, 10>> outputs(networksCount); |
| 164 | |
| 165 | for (unsigned int k = 0; k < networksCount; ++k) |
| 166 | { |
| 167 | status = runtime->EnqueueWorkload(networks[k].m_Network, |
| 168 | MakeInputTensors(networks[k].m_InputBindingInfo, testCaseData->m_InputImage), |
| 169 | MakeOutputTensors(networks[k].m_OutputBindingInfo, outputs[k])); |
| 170 | if (status == armnn::Status::Failure) |
| 171 | { |
| 172 | BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to enqueue workload"; |
| 173 | return 1; |
| 174 | } |
| 175 | } |
| 176 | |
| 177 | // Compare outputs |
| 178 | for (unsigned int k = 1; k < networksCount; ++k) |
| 179 | { |
| 180 | if (!std::equal(outputs[0].begin(), outputs[0].end(), outputs[k].begin(), outputs[k].end())) |
| 181 | { |
| 182 | BOOST_LOG_TRIVIAL(error) << "Multiple networks inference failed!"; |
| 183 | return 1; |
| 184 | } |
| 185 | } |
| 186 | } |
| 187 | |
| 188 | BOOST_LOG_TRIVIAL(info) << "Multiple networks inference ran successfully!"; |
| 189 | return 0; |
| 190 | } |
| 191 | catch (armnn::Exception const& e) |
| 192 | { |
| 193 | BOOST_LOG_TRIVIAL(fatal) <<"Armnn Error: "<< e.what(); |
| 194 | return 1; |
| 195 | } |
| 196 | } |