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; } }