package edu.cmu.graphchi.toolkits.collaborative_filtering;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.logging.Logger;
import edu.cmu.graphchi.ChiFilenames;
import edu.cmu.graphchi.ChiLogger;
import edu.cmu.graphchi.datablocks.FloatConverter;
import edu.cmu.graphchi.datablocks.IntConverter;
import edu.cmu.graphchi.preprocessing.EdgeProcessor;
import edu.cmu.graphchi.preprocessing.FastSharder;
import edu.cmu.graphchi.util.HugeDoubleMatrix;
public class ProblemSetup {
static HugeDoubleMatrix latent_factors_inmem;
static long M,N,L;
static int D = 10;
static double minval = -1e100;
static double maxval = 1e100;
protected static Logger logger = ChiLogger.getLogger("ALS");
static double train_rmse = 0.0;
FastSharder sharder_validation;
static RMSEEngine validation_rmse_engine;
static String training;
static String validation;
static String test;
static int nShards;
static int quiet;
void init_feature_vectors(long size){
logger.info("Initializing latent factors for " + size + " vertices");
latent_factors_inmem = new HugeDoubleMatrix(size, D);
/* Fill with random data */
latent_factors_inmem.randomize(0f, 1.0f);
}
}