org.deeplearning4j.text.movingwindow.WordConverter 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.deeplearning4j.models.word2vec.Word2Vec;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.util.FeatureUtil;
import java.util.ArrayList;
import java.util.List;
public class WordConverter {
private List sentences = new ArrayList<>();
private Word2Vec vec;
private List windows;
public WordConverter(List sentences, Word2Vec vec) {
this.sentences = sentences;
this.vec = vec;
}
public static INDArray toInputMatrix(List windows, Word2Vec vec) {
int columns = vec.lookupTable().layerSize() * vec.getWindow();
int rows = windows.size();
INDArray ret = Nd4j.create(rows, columns);
for (int i = 0; i < rows; i++) {
ret.putRow(i, WindowConverter.asExampleMatrix(windows.get(i), vec));
}
return ret;
}
public INDArray toInputMatrix() {
List windows = allWindowsForAllSentences();
return toInputMatrix(windows, vec);
}
public static INDArray toLabelMatrix(List labels, List windows) {
int columns = labels.size();
INDArray ret = Nd4j.create(windows.size(), columns);
for (int i = 0; i < ret.rows(); i++) {
ret.putRow(i, FeatureUtil.toOutcomeVector(labels.indexOf(windows.get(i).getLabel()), labels.size()));
}
return ret;
}
public INDArray toLabelMatrix(List labels) {
List windows = allWindowsForAllSentences();
return toLabelMatrix(labels, windows);
}
private List allWindowsForAllSentences() {
if (windows != null)
return windows;
windows = new ArrayList<>();
for (String s : sentences)
if (!s.isEmpty())
windows.addAll(Windows.windows(s));
return windows;
}
}