org.deeplearning4j.models.word2vec.VocabWord 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.models.word2vec;
import com.fasterxml.jackson.databind.ObjectMapper;
import lombok.Getter;
import lombok.Setter;
import org.deeplearning4j.models.sequencevectors.sequence.SequenceElement;
import java.io.Serializable;
/**
* Intermediate layers of the neural network
*
* @author Adam Gibson
*/
public class VocabWord extends SequenceElement implements Serializable {
private static final long serialVersionUID = 2223750736522624256L;
//for my sanity
private String word;
/*
Used for Joint/Distributed vocabs mechanics
*/
@Getter @Setter protected Long vocabId;
@Getter @Setter protected Long affinityId;
public static VocabWord none() {
return new VocabWord(0,"none");
}
/**
*
* @param wordFrequency count of the word
*/
public VocabWord(double wordFrequency,String word) {
if(word == null || word.isEmpty())
throw new IllegalArgumentException("Word must not be null or empty");
this.word = word;
this.elementFrequency.set(wordFrequency);
}
public VocabWord() {}
public String getLabel() {
return this.word;
}
/*
public void write(DataOutputStream dos) throws IOException {
dos.writeDouble(this.elementFrequency.get());
}
public VocabWord read(DataInputStream dos) throws IOException {
this.elementFrequency.set(dos.readDouble());
return this;
}
*/
public String getWord() {
return word;
}
public void setWord(String word) {
this.word = word;
}
@Override
public boolean equals(Object o) {
if (this == o) return true;
if (!(o instanceof VocabWord)) return false;
final VocabWord vocabWord = (VocabWord) o;
if (this.word == null)
return vocabWord.word == null;
return this.word.equals(vocabWord.getWord());
/*
if (codeLength != vocabWord.codeLength) return false;
if (index != vocabWord.index) return false;
if (!codes.equals(vocabWord.codes)) return false;
if (historicalGradient != null ? !historicalGradient.equals(vocabWord.historicalGradient) : vocabWord.historicalGradient != null)
return false;
if (!points.equals(vocabWord.points)) return false;
if (!word.equals(vocabWord.word)) return false;
return this.elementFrequency.get() == vocabWord.elementFrequency.get();
*/
}
@Override
public int hashCode() {
final int result = this.word == null ? 0 : this.word.hashCode(); //this.elementFrequency.hashCode();
/*result = 31 * result + index;
result = 31 * result + codes.hashCode();
result = 31 * result + word.hashCode();
result = 31 * result + (historicalGradient != null ? historicalGradient.hashCode() : 0);
result = 31 * result + points.hashCode();
result = 31 * result + codeLength;*/
return result;
}
@Override
public String toString() {
return "VocabWord{" +
"wordFrequency=" + this.elementFrequency +
", index=" + index +
", word='" + word + '\'' +
", codeLength=" + codeLength +
'}';
}
@Override
public String toJSON() {
ObjectMapper mapper = mapper();
try {
/*
we need JSON as single line to save it at first line of the CSV model file
*/
return mapper.writeValueAsString(this);
} catch (com.fasterxml.jackson.core.JsonProcessingException e) {
throw new RuntimeException(e);
}
}
}