code: package zemberek.embedding;
  
  import java.io.DataInputStream;
  import java.io.DataOutputStream;
  import java.io.IOException;
  import java.io.RandomAccessFile;
  import java.nio.MappedByteBuffer;
  import java.nio.channels.FileChannel;
  import java.nio.file.Files;
  import java.nio.file.Path;
  import java.util.ArrayList;
  import java.util.Collections;
  import java.util.List;
  import java.util.PriorityQueue;
  import zemberek.core.collections.IntFloatMap;
  import zemberek.core.collections.UIntMap;
  import zemberek.core.io.IOUtil;
  import zemberek.core.logging.Log;
  import zemberek.core.math.FloatArrays;
  import zemberek.lm.LmVocabulary;
  
  public class WordVectorLookup {
  
    private LmVocabulary vocabulary;
    private UIntMap<Vector> vectors;
    private int dimension;
  
    private WordVectorLookup(LmVocabulary vocabulary, UIntMap<Vector> vectors) {
      this.vocabulary = vocabulary;
      this.vectors = vectors;
      this.dimension = vectors.get(0).data.length;
    }
  
    private WordVectorLookup(LmVocabulary vocabulary, Vector[] vectorArray) {
      this.vocabulary = vocabulary;
      this.vectors = new UIntMap<>(vocabulary.size());
      for (Vector vector : vectorArray) {
        vectors.put(vector.wordIndex, vector);
      }
      this.dimension = vectors.get(0).data.length;
    }
  
    public static WordVectorLookup loadFromText(Path txtFile, boolean skipFirstLine)
        throws IOException {
  
      List<String> lines = Files.readAllLines(txtFile);
      // generate vocabulary
      LmVocabulary.Builder builder = new LmVocabulary.Builder();
      int lineCount = 0;
      for (String line : lines) {
        if (lineCount++ == 0 && skipFirstLine) { // skip first line.
          continue;
        }
        int index = line.indexOf(' ');
        String word = line.substring(0, index);
        builder.add(word);
      }
      LmVocabulary vocabulary = builder.generate();
  
      UIntMap<Vector> vectors = new UIntMap<>(lines.size());
      lineCount = 0;
  
      for (String line : lines) {
        if (lineCount++ == 0 && skipFirstLine) { // skip first line.
          continue;
        }
        line = line.trim();
        int index = line.indexOf(' ');
        String word = line.substring(0, index);
        String floats = line.substring(index + 1);
        float[] vector = FloatArrays.fromString(floats, " ");
        int wordIndex = vocabulary.indexOf(word);
        vectors.put(wordIndex, new Vector(wordIndex, vector));
      }
      return new WordVectorLookup(vocabulary, vectors);
    }
  
    public static WordVectorLookup loadFromBinaryFast(Path vectorFile, Path vocabularyFile)
        throws IOException {
  
      LmVocabulary vocabulary = LmVocabulary.loadFromBinary(vocabularyFile.toFile());
  
      int wordCount;
      int vectorDimension;
      try (DataInputStream dis = IOUtil.getDataInputStream(vectorFile)) {
        wordCount = dis.readInt();
        vectorDimension = dis.readInt();
      }
  
      RandomAccessFile aFile = new RandomAccessFile(vectorFile.toFile(), "r");
      FileChannel inChannel = aFile.getChannel();
  
      long start = 8, size;
      int blockSize = 4 + vectorDimension * 4;
  
      Vector[] vectors = new Vector[wordCount];
  
      int wordCounter = 0;
      int wordBlockSize = 100_000;
  
      while (wordCounter < wordCount) {
  
        if (wordCounter + wordBlockSize > wordCount) {
          wordBlockSize = (wordCount - wordCounter);
        }
        size = blockSize * wordBlockSize;
  
        MappedByteBuffer buffer = inChannel.map(FileChannel.MapMode.READ_ONLY, start, size);
        buffer.load();
  
        start += size;
  
        int blockCounter = 0;
        while (blockCounter < wordBlockSize) {
          int wordIndex = buffer.getInt();
          float[] data = new float[vectorDimension];
          buffer.asFloatBuffer().get(data);
          vectors[wordCounter] = new Vector(wordIndex, data);
          wordCounter++;
          blockCounter++;
          buffer.position(blockCounter * blockSize);
        }
      }
      return new WordVectorLookup(vocabulary, vectors);
    }
  
    public static WordVectorLookup loadFromBinary(Path vectorFile, Path vocabularyFile)
        throws IOException {
  
      LmVocabulary vocabulary = LmVocabulary.loadFromBinary(vocabularyFile.toFile());
  
      try (DataInputStream dis = IOUtil.getDataInputStream(vectorFile)) {
        int wordCount = dis.readInt();
        int vectorDimension = dis.readInt();
        Vector[] vectors = new Vector[wordCount];
  
        for(int  i = 0; i < wordCount ; i++) {
          int index = dis.readInt();
          if(index>wordCount || index<0) {
            throw new IllegalStateException("Bad word index " + index);
          }
          float[] vec = FloatArrays.deserializeRaw(dis, vectorDimension);
          vectors[i] = new Vector(index, vec);
        }
        return new WordVectorLookup(vocabulary, vectors);
      }
    }
  
  
    public Iterable<Vector> getVectors() {
      return vectors.getValues();
    }
  
    public void saveToFolder(Path out, String id) throws IOException {
      Files.createDirectories(out);
      Path vocab = out.resolve(id + ".vocab");
      vocabulary.saveBinary(vocab.toFile());
      Log.info("Vocabulary %s is written.", vocab);
      Path vecPath = out.resolve(id + ".vec.bin");
      try (DataOutputStream dos = IOUtil.getDataOutputStream(vecPath)) {
        dos.writeInt(vectors.size());
        dos.writeInt(dimension);
        for (Vector ve : vectors.getValuesSortedByKey()) {
          if(ve.wordIndex<0 || ve.wordIndex>vocabulary.size()) {
            throw new IllegalStateException("Negative index!");
          }
          dos.writeInt(ve.wordIndex);
          FloatArrays.serializeRaw(dos, ve.data);
        }
      }
      Log.info("Binary Vector file %s is written.", vecPath);
  
    }
  
    public Vector getVector(String word) {
      return vectors.get(vocabulary.indexOf(word));
    }
  
    public boolean containsWord(String word) {
      return vocabulary.contains(word);
    }
  
    public int getDimension() {
      return dimension;
    }
  
    public static class Vector {
  
      int wordIndex;
      float[] data;
  
      Vector(int wordIndex, float[] vector) {
        this.wordIndex = wordIndex;
        this.data = vector;
      }
  
      public int getWordIndex() {
        return wordIndex;
      }
  
      public float[] getData() {
        return data;
      }
  
      float c() {
        float sum = 0;
        for (float v : data) {
          sum += v * v;
        }
        return (float) Math.sqrt(sum);
      }
    }
  
    public static class DistanceMatcher {
  
      WordVectorLookup lookup;
      private IntFloatMap cMap;
  
      public DistanceMatcher(WordVectorLookup lookup) {
        this.lookup = lookup;
        this.cMap = new IntFloatMap(lookup.vectors.size());
        for (int i : lookup.vectors.getKeys()) {
          cMap.put(i, lookup.vectors.get(i).c());
        }
      }
  
      float cosDistance(Vector v1, Vector v2) {
        float sum = 0;
        for (int i = 0; i < v1.data.length; i++) {
          sum += (v1.data[i] * v2.data[i]);
        }
        return sum / (cMap.get(v1.wordIndex) * cMap.get(v1.wordIndex));
      }
  
      public List<WordDistances.Distance> nearestK(String word, int k) {
        if (!lookup.vocabulary.contains(word)) {
          return Collections.emptyList();
        }
        int index = lookup.vocabulary.indexOf(word);
        Vector v = lookup.vectors.get(index);
  
        PriorityQueue<WordDistances.Distance> queue = new PriorityQueue<>(k * 2);
  
        for (Vector other : lookup.vectors.getValues()) {
          // skip self.
          if (v == other) {
            continue;
          }
          float distance = cosDistance(v, other);
          if (queue.size() < k) {
            queue.add(
                new WordDistances.Distance(lookup.vocabulary.getWord(other.wordIndex), distance));
          } else {
            WordDistances.Distance weakest = queue.peek();
            if (weakest.distance < distance) {
              queue.remove();
              queue.add(
                  new WordDistances.Distance(lookup.vocabulary.getWord(other.wordIndex), distance));
            }
          }
        }
  
        ArrayList<WordDistances.Distance> result = new ArrayList<>(queue);
        Collections.reverse(result);
        return result;
      }
    }
  }
  