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//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//
#include <iostream>
#include <chrono>
#include <vector>
#include <array>
#include <boost/log/trivial.hpp>
#include "armnn/ArmNN.hpp"
#include "armnn/Utils.hpp"
#include "armnn/INetwork.hpp"
#include "armnnCaffeParser/ICaffeParser.hpp"
#include "../Cifar10Database.hpp"
#include "../InferenceTest.hpp"
#include "../InferenceModel.hpp"
using namespace std;
using namespace std::chrono;
using namespace armnn::test;
int main(int argc, char* argv[])
{
#ifdef NDEBUG
armnn::LogSeverity level = armnn::LogSeverity::Info;
#else
armnn::LogSeverity level = armnn::LogSeverity::Debug;
#endif
try
{
// Configure logging for both the ARMNN library and this test program
armnn::ConfigureLogging(true, true, level);
armnnUtils::ConfigureLogging(boost::log::core::get().get(), true, true, level);
namespace po = boost::program_options;
armnn::Compute computeDevice;
std::string modelDir;
std::string dataDir;
po::options_description desc("Options");
try
{
// Add generic options needed for all inference tests
desc.add_options()
("help", "Display help messages")
("model-dir,m", po::value<std::string>(&modelDir)->required(),
"Path to directory containing the Cifar10 model file")
("compute,c", po::value<armnn::Compute>(&computeDevice)->default_value(armnn::Compute::CpuAcc),
"Which device to run layers on by default. Possible choices: CpuAcc, CpuRef, GpuAcc")
("data-dir,d", po::value<std::string>(&dataDir)->required(),
"Path to directory containing the Cifar10 test data");
}
catch (const std::exception& e)
{
// Coverity points out that default_value(...) can throw a bad_lexical_cast,
// and that desc.add_options() can throw boost::io::too_few_args.
// They really won't in any of these cases.
BOOST_ASSERT_MSG(false, "Caught unexpected exception");
std::cerr << "Fatal internal error: " << e.what() << std::endl;
return 1;
}
po::variables_map vm;
try
{
po::store(po::parse_command_line(argc, argv, desc), vm);
if (vm.count("help"))
{
std::cout << desc << std::endl;
return 1;
}
po::notify(vm);
}
catch (po::error& e)
{
std::cerr << e.what() << std::endl << std::endl;
std::cerr << desc << std::endl;
return 1;
}
if (!ValidateDirectory(modelDir))
{
return 1;
}
string modelPath = modelDir + "cifar10_full_iter_60000.caffemodel";
// Create runtime
armnn::IRuntimePtr runtime(armnn::IRuntime::Create(computeDevice));
// Load networks
armnn::Status status;
struct Net
{
Net(armnn::NetworkId netId,
const std::pair<armnn::LayerBindingId, armnn::TensorInfo>& in,
const std::pair<armnn::LayerBindingId, armnn::TensorInfo>& out)
: m_Network(netId)
, m_InputBindingInfo(in)
, m_OutputBindingInfo(out)
{}
armnn::NetworkId m_Network;
std::pair<armnn::LayerBindingId, armnn::TensorInfo> m_InputBindingInfo;
std::pair<armnn::LayerBindingId, armnn::TensorInfo> m_OutputBindingInfo;
};
std::vector<Net> networks;
armnnCaffeParser::ICaffeParserPtr parser(armnnCaffeParser::ICaffeParser::Create());
const int networksCount = 4;
for (int i = 0; i < networksCount; ++i)
{
// Create a network from a file on disk
armnn::INetworkPtr network = parser->CreateNetworkFromBinaryFile(modelPath.c_str(), {}, { "prob" });
// optimize the network
armnn::IOptimizedNetworkPtr optimizedNet(nullptr, nullptr);
try
{
optimizedNet = armnn::Optimize(*network, runtime->GetDeviceSpec());
}
catch (armnn::Exception& e)
{
std::stringstream message;
message << "armnn::Exception ("<<e.what()<<") caught from optimize.";
BOOST_LOG_TRIVIAL(fatal) << message.str();
return 1;
}
// Load the network into the runtime
armnn::NetworkId networkId;
status = runtime->LoadNetwork(networkId, std::move(optimizedNet));
if (status == armnn::Status::Failure)
{
BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to load network";
return 1;
}
networks.emplace_back(networkId,
parser->GetNetworkInputBindingInfo("data"),
parser->GetNetworkOutputBindingInfo("prob"));
}
// Load a test case and test inference
if (!ValidateDirectory(dataDir))
{
return 1;
}
Cifar10Database cifar10(dataDir);
for (unsigned int i = 0; i < 3; ++i)
{
// Load test case data (including image data)
std::unique_ptr<Cifar10Database::TTestCaseData> testCaseData = cifar10.GetTestCaseData(i);
// Test inference
std::vector<std::array<float, 10>> outputs(networksCount);
for (unsigned int k = 0; k < networksCount; ++k)
{
status = runtime->EnqueueWorkload(networks[k].m_Network,
MakeInputTensors(networks[k].m_InputBindingInfo, testCaseData->m_InputImage),
MakeOutputTensors(networks[k].m_OutputBindingInfo, outputs[k]));
if (status == armnn::Status::Failure)
{
BOOST_LOG_TRIVIAL(fatal) << "armnn::IRuntime: Failed to enqueue workload";
return 1;
}
}
// Compare outputs
for (unsigned int k = 1; k < networksCount; ++k)
{
if (!std::equal(outputs[0].begin(), outputs[0].end(), outputs[k].begin(), outputs[k].end()))
{
BOOST_LOG_TRIVIAL(error) << "Multiple networks inference failed!";
return 1;
}
}
}
BOOST_LOG_TRIVIAL(info) << "Multiple networks inference ran successfully!";
return 0;
}
catch (armnn::Exception const& e)
{
// Coverity fix: BOOST_LOG_TRIVIAL (typically used to report errors) may throw an
// exception of type std::length_error.
// Using stderr instead in this context as there is no point in nesting try-catch blocks here.
std::cerr << "Armnn Error: " << e.what() << std::endl;
return 1;
}
catch (const std::exception& e)
{
// Coverity fix: various boost exceptions can be thrown by methods called by this test.
std::cerr << "WARNING: MultipleNetworksCifar10: An error has occurred when running the "
"multiple networks inference tests: " << e.what() << std::endl;
return 1;
}
}
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