opennlp.perceptron.PerceptronModelWriter Maven / Gradle / Ivy
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package opennlp.perceptron;
import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import opennlp.model.AbstractModel;
import opennlp.model.AbstractModelWriter;
import opennlp.model.ComparablePredicate;
import opennlp.model.Context;
import opennlp.model.IndexHashTable;
/**
* Abstract parent class for Perceptron writers. It provides the persist method
* which takes care of the structure of a stored document, and requires an
* extending class to define precisely how the data should be stored.
*
*/
public abstract class PerceptronModelWriter extends AbstractModelWriter {
protected Context[] PARAMS;
protected String[] OUTCOME_LABELS;
protected String[] PRED_LABELS;
int numOutcomes;
public PerceptronModelWriter (AbstractModel model) {
Object[] data = model.getDataStructures();
this.numOutcomes = model.getNumOutcomes();
PARAMS = (Context[]) data[0];
IndexHashTable pmap = (IndexHashTable) data[1];
OUTCOME_LABELS = (String[])data[2];
PRED_LABELS = new String[pmap.size()];
pmap.toArray(PRED_LABELS);
}
protected ComparablePredicate[] sortValues () {
ComparablePredicate[] sortPreds;
ComparablePredicate[] tmpPreds = new ComparablePredicate[PARAMS.length];
int[] tmpOutcomes = new int[numOutcomes];
double[] tmpParams = new double[numOutcomes];
int numPreds = 0;
//remove parameters with 0 weight and predicates with no parameters
for (int pid=0; pid> computeOutcomePatterns(ComparablePredicate[] sorted) {
ComparablePredicate cp = sorted[0];
List> outcomePatterns = new ArrayList>();
List newGroup = new ArrayList();
for (ComparablePredicate predicate : sorted) {
if (cp.compareTo(predicate) == 0) {
newGroup.add(predicate);
} else {
cp = predicate;
outcomePatterns.add(newGroup);
newGroup = new ArrayList();
newGroup.add(predicate);
}
}
outcomePatterns.add(newGroup);
System.err.println(outcomePatterns.size()+" outcome patterns");
return outcomePatterns;
}
/**
* Writes the model to disk, using the writeX()
methods
* provided by extending classes.
*
* If you wish to create a PerceptronModelWriter which uses a different
* structure, it will be necessary to override the persist method in
* addition to implementing the writeX()
methods.
*/
public void persist() throws IOException {
// the type of model (Perceptron)
writeUTF("Perceptron");
// the mapping from outcomes to their integer indexes
writeInt(OUTCOME_LABELS.length);
for (String label : OUTCOME_LABELS) {
writeUTF(label);
}
// the mapping from predicates to the outcomes they contributed to.
// The sorting is done so that we actually can write this out more
// compactly than as the entire list.
ComparablePredicate[] sorted = sortValues();
List> compressed = computeOutcomePatterns(sorted);
writeInt(compressed.size());
for (List a : compressed) {
writeUTF(a.size() + a.get(0).toString());
}
// the mapping from predicate names to their integer indexes
writeInt(sorted.length);
for (ComparablePredicate s : sorted) {
writeUTF(s.name);
}
// write out the parameters
for (int i=0; i