stanfordnlp/CoreNLP · error · NoSuchElementException

CrossValidatorIterator exhausted.

Error message

CrossValidatorIterator exhausted.

What it means

NoSuchElementException thrown by CrossValidationIterator.next() when next() is called after all kFold folds have already been returned (iter == kFold). It indicates the caller ignored hasNext() and over-iterated the fold sequence.

Solutions

1. Guard next() calls with hasNext()
2. Loop with `while (iterator.hasNext())` instead of a fixed count larger than kFold
3. Re-create the CrossValidator if more passes over folds are needed

When it happens

Trigger: Thrown at src/edu/stanford/nlp/classify/CrossValidator.java:75 when the library encounters an invalid state.

Common situations: See trigger scenarios.

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/36ec35623b978066. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/classify/CrossValidator.java:75

    return sum / kFold;
  }


  class CrossValidationIterator implements Iterator<Triple<GeneralDataset<L, F>,GeneralDataset<L, F>,SavedState>> {

    private int iter = 0;

    @Override
    public boolean hasNext() { return iter < kFold; }

    @Override
    public void remove() {
      throw new UnsupportedOperationException("CrossValidationIterator doesn't support remove()");
    }

    @Override
    public Triple<GeneralDataset<L, F>,GeneralDataset<L, F>,SavedState> next() {
      if (iter == kFold) throw new NoSuchElementException("CrossValidatorIterator exhausted.");
      int start = originalTrainData.size() * iter / kFold;
      int end = originalTrainData.size() * (iter + 1) / kFold;
      //Logging.logger(this.getClass()).info("##train data size: " +  originalTrainData.size() + " start " + start + " end " + end);
      Pair<GeneralDataset<L, F>, GeneralDataset<L, F>> split = originalTrainData.split(start, end);

      return new Triple<>(split.first(), split.second(), savedStates[iter++]);
    }

  } // end class CrossValidationIterator


  public static class SavedState {
    public Object state;
  }

  public static void main(String[] args) {
    Dataset<String, String> d = Dataset.readSVMLightFormat(args[0]);
    Iterator<Triple<GeneralDataset<String, String>,GeneralDataset<String, String>,SavedState>> it = (new CrossValidator<>(d)).iterator();

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