66 lines
1.7 KiB
C++
66 lines
1.7 KiB
C++
/*! @page timer mlpack Timers
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@section timerintro Introduction
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mlpack provides a simple timer interface for the timing of machine learning
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methods. The results of any timers used during the program are displayed at
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output by the mlpack::CLI object, when --verbose is given:
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@code
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$ allknn -r dataset.csv -n neighbors_out.csv -d distances_out.csv -k 5 -v
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<...>
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[INFO ] Program timers:
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[INFO ] computing_neighbors: 0.010650s
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[INFO ] loading_data: 0.002567s
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[INFO ] saving_data: 0.001115s
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[INFO ] total_time: 0.149816s
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[INFO ] tree_building: 0.000534s
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@endcode
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@section usingtimer Timer API
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The mlpack::Timer class provides three simple methods:
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@code
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void Timer::Start(const char* name);
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void Timer::Stop(const char* name);
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timeval Timer::Get(const char* name);
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@endcode
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Each timer is given a name, and is referenced by that name. You can call \c
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Timer::Start() and \c Timer::Stop() multiple times for a particular timer name,
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and the result will be the sum of the runs of the timer. Note that \c
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Timer::Stop() must be called before \c Timer::Start() is called again,
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otherwise a std::runtime_error exception will be thrown.
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A "total_time" timer is run by default for each mlpack program.
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@section example Timer Example
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Below is a very simple example of timer usage in code.
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@code
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#include <mlpack/core.hpp>
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using namespace mlpack;
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int main(int argc, char** argv)
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{
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CLI::ParseCommandLine(argc, argv);
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// Start a timer.
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Timer::Start("some_timer");
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// Do some things.
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DoSomeStuff();
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// Stop the timer.
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Timer::Stop("some_timer");
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}
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@endcode
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If the --verbose flag was given to this executable, the resultant time that
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"some_timer" ran for would be shown.
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*/
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