Package edu.stanford.nlp.io

Examples of edu.stanford.nlp.io.OutDataStreamFile.writeInt()

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  /** Currently unused */
  @SuppressWarnings({"UnusedDeclaration","unused"})
  private void save(String filename) {
    try {
      OutDataStreamFile rF = new OutDataStreamFile(filename);
      rF.writeInt(xSize);
      rF.writeInt(ySize);
      rF.writeInt(vArray.length);
      for (int i = 0; i < xSize; i++) {
        rF.writeInt(px[i]);
      }
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  @SuppressWarnings({"UnusedDeclaration","unused"})
  private void save(String filename) {
    try {
      OutDataStreamFile rF = new OutDataStreamFile(filename);
      rF.writeInt(xSize);
      rF.writeInt(ySize);
      rF.writeInt(vArray.length);
      for (int i = 0; i < xSize; i++) {
        rF.writeInt(px[i]);
      }
      for (int j = 0; j < ySize; j++) {
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  private void save(String filename) {
    try {
      OutDataStreamFile rF = new OutDataStreamFile(filename);
      rF.writeInt(xSize);
      rF.writeInt(ySize);
      rF.writeInt(vArray.length);
      for (int i = 0; i < xSize; i++) {
        rF.writeInt(px[i]);
      }
      for (int j = 0; j < ySize; j++) {
        rF.writeInt(py[j]);
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      OutDataStreamFile rF = new OutDataStreamFile(filename);
      rF.writeInt(xSize);
      rF.writeInt(ySize);
      rF.writeInt(vArray.length);
      for (int i = 0; i < xSize; i++) {
        rF.writeInt(px[i]);
      }
      for (int j = 0; j < ySize; j++) {
        rF.writeInt(py[j]);
      }
      for (int i = 0; i < xSize; i++) {
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      rF.writeInt(vArray.length);
      for (int i = 0; i < xSize; i++) {
        rF.writeInt(px[i]);
      }
      for (int j = 0; j < ySize; j++) {
        rF.writeInt(py[j]);
      }
      for (int i = 0; i < xSize; i++) {
        for (int j = 0; j < dim; j++) {
          rF.writeInt(pxy[i][j]);
        }
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      for (int j = 0; j < ySize; j++) {
        rF.writeInt(py[j]);
      }
      for (int i = 0; i < xSize; i++) {
        for (int j = 0; j < dim; j++) {
          rF.writeInt(pxy[i][j]);
        }
      }

      rF.close();
    } catch (Exception e) {
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  protected static void saveModel(String filename, TaggerConfig config) {
    try {
      OutDataStreamFile file = new OutDataStreamFile(filename);
      config.saveConfig(file);
      file.writeInt(xSize);
      file.writeInt(ySize);
      dict.save(file);
      tags.save(file);

      saveExtractors(file);
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  protected static void saveModel(String filename, TaggerConfig config) {
    try {
      OutDataStreamFile file = new OutDataStreamFile(filename);
      config.saveConfig(file);
      file.writeInt(xSize);
      file.writeInt(ySize);
      dict.save(file);
      tags.save(file);

      saveExtractors(file);
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      dict.save(file);
      tags.save(file);

      saveExtractors(file);

      file.writeInt(fAssociations.size());
      for (Map.Entry<FeatureKey,Integer> item : fAssociations.entrySet()) {
        int numF = item.getValue();
        file.writeInt(numF);
        FeatureKey fk = item.getKey();
        fk.save(file);
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      saveExtractors(file);

      file.writeInt(fAssociations.size());
      for (Map.Entry<FeatureKey,Integer> item : fAssociations.entrySet()) {
        int numF = item.getValue();
        file.writeInt(numF);
        FeatureKey fk = item.getKey();
        fk.save(file);
      }

      LambdaSolve.save_lambdas(file, prob.lambda);
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