org.deeplearning4j.text.tokenization.tokenizer.ConcurrentTokenizer Maven / Gradle / Ivy
/*-
*
* * Copyright 2015 Skymind,Inc.
* *
* * Licensed 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 org.deeplearning4j.text.tokenization.tokenizer;
import opennlp.tools.tokenize.TokenizerME;
import opennlp.tools.tokenize.TokenizerModel;
import opennlp.tools.util.Span;
import opennlp.uima.tokenize.AbstractTokenizer;
import opennlp.uima.tokenize.TokenizerModelResource;
import opennlp.uima.util.AnnotatorUtil;
import opennlp.uima.util.UimaUtil;
import org.apache.uima.UimaContext;
import org.apache.uima.analysis_engine.AnalysisEngineProcessException;
import org.apache.uima.cas.CAS;
import org.apache.uima.cas.Feature;
import org.apache.uima.cas.TypeSystem;
import org.apache.uima.cas.text.AnnotationFS;
import org.apache.uima.resource.ResourceAccessException;
import org.apache.uima.resource.ResourceInitializationException;
/**
* OpenNLP Tokenizer annotator.
*
* Mandatory parameters
*
* Type Name Description String opennlp.uima.ModelName The name of the model file String opennlp.uima.SentenceType The full name of the sentence type String opennlp.uima.TokenType The full name of the token type
*
* Optional parameters
*
* Type Name Description String opennlp.uima.ProbabilityFeature The name of the double
* probability feature (not applyTransformToDestination by default)
*
* @see {@link TokenizerME}
*/
public class ConcurrentTokenizer extends AbstractTokenizer {
/**
* The OpenNLP tokenizer.
*/
private TokenizerME tokenizer;
private Feature probabilityFeature;
@Override
public synchronized void process(CAS cas) throws AnalysisEngineProcessException {
super.process(cas);
}
/**
* Initializes a new instance.
*
* Note: Use {@link #initialize(UimaContext) } to initialize
* this instance. Not use the constructor.
*/
public ConcurrentTokenizer() {
super("OpenNLP Tokenizer");
// must not be implemented !
}
/**
* Initializes the current instance with the given context.
*
* Note: Do all initialization in this method, do not use the constructor.
*/
public void initialize(UimaContext context) throws ResourceInitializationException {
super.initialize(context);
TokenizerModel model;
try {
TokenizerModelResource modelResource =
(TokenizerModelResource) context.getResourceObject(UimaUtil.MODEL_PARAMETER);
model = modelResource.getModel();
} catch (ResourceAccessException e) {
throw new ResourceInitializationException(e);
}
tokenizer = new TokenizerME(model);
}
/**
* Initializes the type system.
*/
public void typeSystemInit(TypeSystem typeSystem) throws AnalysisEngineProcessException {
super.typeSystemInit(typeSystem);
probabilityFeature = AnnotatorUtil.getOptionalFeatureParameter(context, tokenType,
UimaUtil.PROBABILITY_FEATURE_PARAMETER, CAS.TYPE_NAME_DOUBLE);
}
@Override
protected Span[] tokenize(CAS cas, AnnotationFS sentence) {
return tokenizer.tokenizePos(sentence.getCoveredText());
}
@Override
protected void postProcessAnnotations(Span[] tokens, AnnotationFS[] tokenAnnotations) {
// if interest
if (probabilityFeature != null) {
double tokenProbabilties[] = tokenizer.getTokenProbabilities();
for (int i = 0; i < tokenAnnotations.length; i++) {
tokenAnnotations[i].setDoubleValue(probabilityFeature, tokenProbabilties[i]);
}
}
}
/**
* Releases allocated resources.
*/
public void destroy() {
// dereference model to allow garbage collection
tokenizer = null;
}
}