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//
// Copyright © 2021 Arm Ltd and Contributors. All rights reserved.
// SPDX-License-Identifier: MIT
//
#include "TestBlocks.hpp"
#include "TestStrategy.hpp"
#include <IMemoryOptimizerStrategy.hpp>
#include <MemoryOptimizerStrategyLibrary.hpp>
#include <strategies/StrategyValidator.hpp>
#include <cxxopts.hpp>
#include <iostream>
#include <algorithm>
#include <iomanip>
std::vector<TestBlock> testBlocks
{
{"fsrcnn", fsrcnn},
{"inceptionv4", inceptionv4},
{"deeplabv3", deeplabv3},
{"deepspeechv1", deepspeechv1},
{"mobilebert", mobilebert},
{"ssd_mobilenetv2", ssd_mobilenetv2},
{"resnetv2", resnetv2},
{"yolov3",yolov3}
};
void PrintModels()
{
std::cout << "Available models:\n";
for (const auto& model : testBlocks)
{
std::cout << model.m_Name << "\n";
}
std::cout << "\n";
}
size_t GetMinPossibleMemorySize(const std::vector<armnn::MemBlock>& blocks)
{
unsigned int maxLifetime = 0;
for (auto& block: blocks)
{
maxLifetime = std::max(maxLifetime, block.m_EndOfLife);
}
maxLifetime++;
std::vector<size_t> lifetimes(maxLifetime);
for (const auto& block : blocks)
{
for (auto lifetime = block.m_StartOfLife; lifetime <= block.m_EndOfLife; ++lifetime)
{
lifetimes[lifetime] += block.m_MemSize;
}
}
return *std::max_element(lifetimes.begin(), lifetimes.end());
}
void RunBenchmark(armnn::IMemoryOptimizerStrategy* strategy, std::vector<TestBlock>* models)
{
using Clock = std::chrono::high_resolution_clock;
float avgEfficiency = 0;
std::chrono::duration<double, std::milli> avgDuration{};
std::cout << "\nMemory Strategy: " << strategy->GetName()<< "\n";
std::cout << "===============================================\n";
for (auto& model : *models)
{
auto now = Clock::now();
const std::vector<armnn::MemBin> result = strategy->Optimize(model.m_Blocks);
auto duration = std::chrono::duration<double, std::milli>(Clock::now() - now);
avgDuration += duration;
size_t memoryUsage = 0;
for (auto bin : result)
{
memoryUsage += bin.m_MemSize;
}
size_t minSize = GetMinPossibleMemorySize(model.m_Blocks);
float efficiency = static_cast<float>(minSize) / static_cast<float>(memoryUsage);
efficiency*=100;
avgEfficiency += efficiency;
std::cout << "\nModel: " << model.m_Name << "\n";
std::cout << "Strategy execution time: " << std::setprecision(4) << duration.count() << " milliseconds\n";
std::cout << "Memory usage: " << memoryUsage/1024 << " kb\n";
std::cout << "Minimum possible usage: " << minSize/1024 << " kb\n";
std::cout << "Memory efficiency: " << std::setprecision(3) << efficiency << "%\n";
}
avgDuration/= static_cast<double>(models->size());
avgEfficiency/= static_cast<float>(models->size());
std::cout << "\n===============================================\n";
std::cout << "Average memory duration: " << std::setprecision(4) << avgDuration.count() << " milliseconds\n";
std::cout << "Average memory efficiency: " << std::setprecision(3) << avgEfficiency << "%\n";
}
struct BenchmarkOptions
{
std::string m_StrategyName;
std::string m_ModelName;
bool m_UseDefaultStrategy = false;
bool m_Validate = false;
};
BenchmarkOptions ParseOptions(int argc, char* argv[])
{
cxxopts::Options options("Memory Benchmark", "Tests memory optimization strategies on different models");
options.add_options()
("s, strategy", "Strategy name, do not specify to use default strategy", cxxopts::value<std::string>())
("m, model", "Model name", cxxopts::value<std::string>())
("v, validate", "Validate strategy", cxxopts::value<bool>()->default_value("false")->implicit_value("true"))
("h,help", "Display usage information");
auto result = options.parse(argc, argv);
if (result.count("help"))
{
std::cout << options.help() << std::endl;
PrintModels();
std::cout << "\nAvailable strategies:\n";
for (const auto& s :armnn::GetMemoryOptimizerStrategyNames())
{
std::cout << s << "\n";
}
exit(EXIT_SUCCESS);
}
BenchmarkOptions benchmarkOptions;
if(result.count("strategy"))
{
benchmarkOptions.m_StrategyName = result["strategy"].as<std::string>();
}
else
{
std::cout << "No Strategy given, using default strategy";
benchmarkOptions.m_UseDefaultStrategy = true;
}
if(result.count("model"))
{
benchmarkOptions.m_ModelName = result["model"].as<std::string>();
}
benchmarkOptions.m_Validate = result["validate"].as<bool>();
return benchmarkOptions;
}
int main(int argc, char* argv[])
{
BenchmarkOptions benchmarkOptions = ParseOptions(argc, argv);
std::shared_ptr<armnn::IMemoryOptimizerStrategy> strategy;
if (benchmarkOptions.m_UseDefaultStrategy)
{
strategy = std::make_shared<armnn::TestStrategy>();
}
else
{
strategy = armnn::GetMemoryOptimizerStrategy(benchmarkOptions.m_StrategyName);
if (!strategy)
{
std::cout << "Strategy name not found\n";
return 0;
}
}
std::vector<TestBlock> model;
std::vector<TestBlock>* modelsToTest = &testBlocks;
if (benchmarkOptions.m_ModelName.size() != 0)
{
auto it = std::find_if(testBlocks.cbegin(), testBlocks.cend(), [&](const TestBlock testBlock)
{
return testBlock.m_Name == benchmarkOptions.m_ModelName;
});
if (it == testBlocks.end())
{
std::cout << "Model name not found\n";
return 0;
}
else
{
model.push_back(*it);
modelsToTest = &model;
}
}
if (benchmarkOptions.m_Validate)
{
armnn::StrategyValidator strategyValidator;
strategyValidator.SetStrategy(strategy);
RunBenchmark(&strategyValidator, modelsToTest);
}
else
{
RunBenchmark(strategy.get(), modelsToTest);
}
}
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