org.deeplearning4j.text.movingwindow.ContextLabelRetriever Maven / Gradle / Ivy
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.deeplearning4j.text.movingwindow;
import org.apache.commons.lang3.StringUtils;
import org.deeplearning4j.text.tokenization.tokenizer.Tokenizer;
import org.deeplearning4j.text.tokenization.tokenizerfactory.TokenizerFactory;
import org.nd4j.base.Preconditions;
import org.nd4j.linalg.collection.MultiDimensionalMap;
import org.nd4j.linalg.primitives.Pair;
import java.util.ArrayList;
import java.util.List;
/**
* Context Label Retriever
* @author Adam Gibson
*/
public class ContextLabelRetriever {
private static String BEGIN_LABEL = "<([A-Za-z]+|\\d+)>";
private static String END_LABEL = "";
private ContextLabelRetriever() {}
/**
* Returns a stripped sentence with the indices of words
* with certain kinds of labels.
* @param sentence the sentence to process
* @return a pair of a post processed sentence
* with labels stripped and the spans of
* the labels
*/
public static Pair> stringWithLabels(String sentence,
TokenizerFactory tokenizerFactory) {
MultiDimensionalMap map = MultiDimensionalMap.newHashBackedMap();
Tokenizer t = tokenizerFactory.create(sentence);
List currTokens = new ArrayList<>();
String currLabel = null;
String endLabel = null;
List>> tokensWithSameLabel = new ArrayList<>();
while (t.hasMoreTokens()) {
String token = t.nextToken();
if (token.matches(BEGIN_LABEL)) {
if (endLabel != null)
throw new IllegalStateException(
"Tried parsing sentence; found an end label when the begin label has not been cleared");
currLabel = token;
//no labels; add these as NONE and begin the new label
if (!currTokens.isEmpty()) {
tokensWithSameLabel.add(new Pair<>("NONE", (List) new ArrayList<>(currTokens)));
currTokens.clear();
}
} else if (token.matches(END_LABEL)) {
if (currLabel == null)
throw new IllegalStateException("Found an ending label with no matching begin label");
endLabel = token;
} else
currTokens.add(token);
if (currLabel != null && endLabel != null) {
currLabel = currLabel.replaceAll("[<>/]", "");
endLabel = endLabel.replaceAll("[<>/]", "");
Preconditions.checkState(!currLabel.isEmpty(), "Current label is empty!");
Preconditions.checkState(!endLabel.isEmpty(), "End label is empty!");
Preconditions.checkState(currLabel.equals(endLabel), "Current label begin and end did not match for the parse. Was: %s ending with %s", currLabel, endLabel);
tokensWithSameLabel.add(new Pair<>(currLabel, (List) new ArrayList<>(currTokens)));
currTokens.clear();
//clear out the tokens
currLabel = null;
endLabel = null;
}
}
//no labels; add these as NONE and begin the new label
if (!currTokens.isEmpty()) {
tokensWithSameLabel.add(new Pair<>("none", (List) new ArrayList<>(currTokens)));
currTokens.clear();
}
//now join the output
StringBuilder strippedSentence = new StringBuilder();
for (Pair> tokensWithLabel : tokensWithSameLabel) {
String joinedSentence = StringUtils.join(tokensWithLabel.getSecond(), " ");
//spaces between separate parts of the sentence
if (!(strippedSentence.length() < 1))
strippedSentence.append(" ");
strippedSentence.append(joinedSentence);
int begin = strippedSentence.toString().indexOf(joinedSentence);
int end = begin + joinedSentence.length();
map.put(begin, end, tokensWithLabel.getFirst());
}
return new Pair<>(strippedSentence.toString(), map);
}
}