package com.walker.embedding;
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import ai.djl.ModelException;
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import ai.djl.translate.TranslateException;
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import com.walker.embedding.util.FeatureComparison;
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import com.walker.embedding.util.WordEncoder;
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import org.slf4j.Logger;
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import org.slf4j.LoggerFactory;
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import java.io.IOException;
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import java.nio.file.Path;
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import java.nio.file.Paths;
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import java.util.Arrays;
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public final class WordEncoderExample7 {
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private static final Logger logger = LoggerFactory.getLogger(WordEncoderExample7.class);
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private WordEncoderExample7() {}
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public static void main(String[] args) throws IOException, ModelException, TranslateException {
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Path vocabPath = Paths.get("d:/dev_tools/ai/w2v_sogou_dim300_vocab.txt");
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Path embeddingPath = Paths.get("d:/dev_tools/ai/w2v_sogou_dim300.npy");
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// Path vocabPath = Paths.get("src/test/resources/w2v_sogou_dim300_vocab.txt");
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// Path embeddingPath = Paths.get("src/test/resources/w2v_sogou_dim300.npy");
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WordEncoder encoder = new WordEncoder(vocabPath, embeddingPath);
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// 获取单词的特征值embedding
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// float[] embedding1 = encoder.search("搜索");
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float[] embedding1 = encoder.search("搜索");
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logger.info("搜索-特征值: " + Arrays.toString(embedding1));
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// System.out.println("搜索-特征值: " + Arrays.toString(embedding1));
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float[] embedding2 = encoder.search("检索");
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logger.info("检索-特征值: " + Arrays.toString(embedding2));
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// System.out.println("检索-特征值: " + Arrays.toString(embedding2));
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// 计算两个词向量的余弦相似度
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float cosineSim = FeatureComparison.cosineSim(embedding1, embedding2);
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logger.info("余弦相似度: "+ Float.toString(cosineSim));
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System.out.println("余弦相似度: "+ Float.toString(cosineSim));
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// 计算两个词向量的内积
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float dot = FeatureComparison.dot(embedding1, embedding2);
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logger.info("内积: "+ Float.toString(dot));
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System.out.println("内积: "+ Float.toString(dot));
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}
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}
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