Package opennlp.tools.cmdline

Examples of opennlp.tools.cmdline.TerminateToolException

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          errorListener);
     
      validator.evaluate(sampleStream, params.getFolds());
    }
    catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: " +
          e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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    System.out.print("Evaluating ... ");
    try {
    evaluator.evaluate(sampleStream);
    }
    catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: " +
          e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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      InputStream bytesIn = CmdLineUtil.openInFile(featureGenDescriptorFile);

      try {
        featureGeneratorBytes = ModelUtil.read(bytesIn);
      } catch (IOException e) {
        throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
            + e.getMessage(), e);
      } finally {
        try {
          bytesIn.close();
        } catch (IOException e) {
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      model = opennlp.tools.namefind.NameFinderME.train(
          params.getLang(), params.getType(), sampleStream,
          mlParams, featureGeneratorBytes, resources);
    }
    catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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      validator = new TokenNameFinderCrossValidator(params.getLang(),
          params.getType(), mlParams, featureGeneratorBytes, resources,
          listeners.toArray(new TokenNameFinderEvaluationMonitor[listeners.size()]));
      validator.evaluate(sampleStream, params.getFolds());
    } catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    } finally {
      try {
        sampleStream.close();
      } catch (IOException e) {
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    mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), false);

    if (mlParams != null) {
      if (TrainUtil.isSequenceTraining(mlParams.getSettings())) {
        throw new TerminateToolException(1, "Sequence training is not supported!");
      }
    }

    if(mlParams == null) {
      mlParams = ModelUtil.createTrainingParameters(params.getIterations(), params.getCutoff());
    }

    File modelOutFile = params.getModel();
    CmdLineUtil.checkOutputFile("sentence detector model", modelOutFile);

    char[] eos = null;
    if (params.getEosChars() != null)
      eos = params.getEosChars().toCharArray();

    SentenceModel model;

    try {
      Dictionary dict = loadDict(params.getAbbDict());
      SentenceDetectorFactory sdFactory = SentenceDetectorFactory.create(
          params.getFactory(), params.getLang(), true, dict, eos);
      model = SentenceDetectorME.train(params.getLang(), sampleStream,
          sdFactory, mlParams);
    } catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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    mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), false);

    if (mlParams != null) {
      if (!TrainUtil.isValid(mlParams.getSettings())) {
        throw new TerminateToolException(1, "Training parameters file '" + params.getParams() +
            "' is invalid!");
      }

      if (TrainUtil.isSequenceTraining(mlParams.getSettings())) {
        throw new TerminateToolException(1, "Sequence training is not supported!");
      }
    }

    if(mlParams == null) {
      mlParams = ModelUtil.createTrainingParameters(params.getIterations(), params.getCutoff());
    }

    File modelOutFile = params.getModel();
    CmdLineUtil.checkOutputFile("tokenizer model", modelOutFile);

    TokenizerModel model;
    try {
      Dictionary dict = loadDict(params.getAbbDict());

      TokenizerFactory tokFactory = TokenizerFactory.create(
          params.getFactory(), params.getLang(), dict,
          params.getAlphaNumOpt(), null);
      model = opennlp.tools.tokenize.TokenizerME.train(sampleStream,
          tokFactory, mlParams);

    } catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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      try {
        reportOutputStream = new FileOutputStream(reportFile);
        reportListener = new POSTaggerFineGrainedReportListener(
            reportOutputStream);
      } catch (FileNotFoundException e) {
        throw new TerminateToolException(-1,
            "IO error while creating POS Tagger fine-grained report file: "
                + e.getMessage());
      }
    }

    POSTaggerCrossValidator validator;
    try {
      validator = new POSTaggerCrossValidator(params.getLang(), mlParams,
          params.getDict(), params.getNgram(), params.getTagDictCutoff(),
          params.getFactory(), missclassifiedListener, reportListener);
     
      validator.evaluate(sampleStream, params.getFolds());
    } catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    } finally {
      try {
        sampleStream.close();
      } catch (IOException e) {
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          tokFactory, listener);

      validator.evaluate(sampleStream, params.getFolds());
    }
    catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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  public void run(String format, String[] args) {
    super.run(format, args);

    mlParams = CmdLineUtil.loadTrainingParameters(params.getParams(), true);
    if (mlParams != null && !TrainUtil.isValid(mlParams.getSettings())) {
      throw new TerminateToolException(1, "Training parameters file '" + params.getParams() +
          "' is invalid!");
    }

    if(mlParams == null) {
      mlParams = ModelUtil.createTrainingParameters(params.getIterations(), params.getCutoff());
      mlParams.put(TrainingParameters.ALGORITHM_PARAM, getModelType(params.getType()).toString());
    }

    File modelOutFile = params.getModel();
    CmdLineUtil.checkOutputFile("pos tagger model", modelOutFile);

    Dictionary ngramDict = null;
   
    Integer ngramCutoff = params.getNgram();
   
    if (ngramCutoff != null) {
      System.err.print("Building ngram dictionary ... ");
      try {
        ngramDict = POSTaggerME.buildNGramDictionary(sampleStream, ngramCutoff);
        sampleStream.reset();
      } catch (IOException e) {
        throw new TerminateToolException(-1,
            "IO error while building NGram Dictionary: " + e.getMessage(), e);
      }
      System.err.println("done");
    }

    POSTaggerFactory postaggerFactory = null;
    try {
      postaggerFactory = POSTaggerFactory.create(params.getFactory(), ngramDict, null);
    } catch (InvalidFormatException e) {
      throw new TerminateToolException(-1, e.getMessage(), e);
    }

    if (params.getDict() != null) {
      try {
        postaggerFactory.setTagDictionary(postaggerFactory
            .createTagDictionary(params.getDict()));
      } catch (IOException e) {
        throw new TerminateToolException(-1,
            "IO error while loading POS Dictionary: " + e.getMessage(), e);
      }
    }

    if (params.getTagDictCutoff() != null) {
      try {
        TagDictionary dict = postaggerFactory.getTagDictionary();
        if (dict == null) {
          dict = postaggerFactory.createEmptyTagDictionary();
          postaggerFactory.setTagDictionary(dict);
        }
        if (dict instanceof MutableTagDictionary) {
          POSTaggerME.populatePOSDictionary(sampleStream, (MutableTagDictionary)dict,
              params.getTagDictCutoff());
        } else {
          throw new IllegalArgumentException(
              "Can't extend a POSDictionary that does not implement MutableTagDictionary.");
        }
        sampleStream.reset();
      } catch (IOException e) {
        throw new TerminateToolException(-1,
            "IO error while creating/extending POS Dictionary: "
                + e.getMessage(), e);
      }
    }

    POSModel model;
    try {
      model = opennlp.tools.postag.POSTaggerME.train(params.getLang(),
          sampleStream, mlParams, postaggerFactory);
    }
    catch (IOException e) {
      throw new TerminateToolException(-1, "IO error while reading training data or indexing data: "
          + e.getMessage(), e);
    }
    finally {
      try {
        sampleStream.close();
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Related Classes of opennlp.tools.cmdline.TerminateToolException

  • opennlp.tools.cmdline.chunker.ChunkerCrossValidatorTool
  • opennlp.tools.cmdline.chunker.ChunkerEvaluatorTool
  • opennlp.tools.cmdline.chunker.ChunkerMETool
  • opennlp.tools.cmdline.chunker.ChunkerTrainerTool
  • opennlp.tools.cmdline.coref.CoreferencerTool
  • opennlp.tools.cmdline.coref.CoreferencerTrainerTool
  • opennlp.tools.cmdline.dictionary.DictionaryBuilderTool
  • opennlp.tools.cmdline.doccat.DoccatCrossValidatorTool
  • opennlp.tools.cmdline.doccat.DoccatEvaluatorTool
  • opennlp.tools.cmdline.doccat.DoccatTool
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