nnp-train.cpp File Reference

#include "Training.h"
#include "utility.h"
#include <mpi.h>
#include <cstddef>
#include <cstdlib>
#include <fstream>
#include <string>

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Functions
int	main (int argc, char *argv[])

Function Documentation

main()

int main	(	int	argc,
		char *	argv[]
	)

Definition at line 28 of file nnp-train.cpp.

{
    int numProcs = 0;
    int myRank   = 0;
    size_t stage = 0;
    ofstream myLog;
 
    string suffix = "";
    if (argc > 1)
    {
        stage = (size_t)atoi(argv[1]);
        suffix = strpr(".stage-%zu", stage);
    }
 
    MPI_Init(&argc, &argv);
    MPI_Comm_size(MPI_COMM_WORLD, &numProcs);
    MPI_Comm_rank(MPI_COMM_WORLD, &myRank);
 
    // Basic setup.
    Training training;
    if (myRank != 0) training.log.writeToStdout = false;
 
    myLog.open((strpr("nnp-train.log.%04d", myRank) + suffix).c_str());
    training.log.registerStreamPointer(&myLog);
    training.setupMPI();
    training.initialize();
    training.loadSettingsFile();
    training.setStage(stage);
    // If initial-weights-based normalization is enabled skip normalization
    // setup here.
    training.setupGeneric(
        "",
        training.settingsKeywordExists("normalize_data_set"),
        stage == 1
    );
    training.setupSymmetryFunctionScaling();
    training.setupSymmetryFunctionStatistics(false, false, false, false);
    training.setupRandomNumberGenerator();
 
    // Distribute structures to MPI processes.
    training.distributeStructures(true);
 
    // Randomly select training/test set and write them to separate files
    // (train.data/test.data, same format as input.data).
    training.selectSets();
    training.writeSetsToFiles();
 
    // Initialize weights and biases for neural networks.
    training.initializeWeights();
 
    // Run data set normalization if keyword present.
    if (training.settingsKeywordExists("normalize_data_set"))
    {
        training.dataSetNormalization();
    }
 
    // Switch to normalized units, convert all structures.
    if (training.useNormalization()) training.toNormalizedUnits();
 
    // General training settings and weight update routine.
    training.setupTraining();
 
    // Calculate neighbor lists for all structures.
    training.calculateNeighborLists();
 
    // The main training loop.
    training.loop();
 
    myLog.close();
 
    MPI_Finalize();
 
    return 0;
}

References nnp::Training::calculateNeighborLists(), nnp::Training::dataSetNormalization(), nnp::Dataset::distributeStructures(), nnp::Mode::initialize(), nnp::Training::initializeWeights(), nnp::Mode::loadSettingsFile(), nnp::Mode::log, nnp::Training::loop(), nnp::Log::registerStreamPointer(), nnp::Training::selectSets(), nnp::Training::setStage(), nnp::Mode::settingsKeywordExists(), nnp::Mode::setupGeneric(), nnp::Dataset::setupMPI(), nnp::Dataset::setupRandomNumberGenerator(), nnp::Mode::setupSymmetryFunctionScaling(), nnp::Mode::setupSymmetryFunctionStatistics(), nnp::Training::setupTraining(), nnp::strpr(), nnp::Dataset::toNormalizedUnits(), nnp::Mode::useNormalization(), nnp::Training::writeSetsToFiles(), and nnp::Log::writeToStdout.

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