package edu.stanford.nlp.sentiment;
import java.io.Serializable;
/**
* Evaluation-only options for the RNN models
*
* @author John Bauer
*/
public class RNNTestOptions implements Serializable {
public int ngramRecordSize = 0;
public int ngramRecordMaximumLength = 0;
public boolean printLengthAccuracies = false;
@Override
public String toString() {
StringBuilder result = new StringBuilder();
result.append("TEST OPTIONS\n");
result.append("ngramRecordSize=" + ngramRecordSize + "\n");
result.append("ngramRecordMaximumLength=" + ngramRecordMaximumLength + "\n");
result.append("printLengthAccuracies=" + printLengthAccuracies + "\n");
return result.toString();
}
public int setOption(String[] args, int argIndex) {
if (args[argIndex].equalsIgnoreCase("-ngramRecordSize")) {
ngramRecordSize = Integer.parseInt(args[argIndex + 1]);
return argIndex + 2;
} else if (args[argIndex].equalsIgnoreCase("-ngramRecordMaximumLength")) {
ngramRecordMaximumLength = Integer.parseInt(args[argIndex + 1]);
return argIndex + 2;
} else if (args[argIndex].equalsIgnoreCase("-printLengthAccuracies")) {
printLengthAccuracies = true;
return argIndex + 1;
} else if (args[argIndex].equalsIgnoreCase("-noprintLengthAccuracies")) {
printLengthAccuracies = false;
return argIndex + 1;
}
return argIndex;
}
}