Onnxmltools

* Fix early stopping for XGBClassifier and xgboost > 2, 597
* Fix discrepancies with XGBRegressor and xgboost > 2, 670
* Support count:poisson for XGBRegressor, 666
* Supports XGBRFClassifier and XGBRFRegressor, 665
* ONNX_DFS_PATH to be set in the spark config, 653 (by Ironwood-Cyber)
* Sparkml converter: support type StringType and StringType(), 639
* Add check for base_score in _get_attributes function 637, 626 (by tolleybot)
* Support for lightgbm >= 4.0, 634

- 608 fix: Spark Imputer conversion with multiple input cols
- 607 fix: getTensorTypeFromSpark fails for Spark 3.3.0+
- 606 Add onnxruntime==1.14.0 to CI
- 605 Replace real images by dummy ones
- 602 Update CI with latext onnxruntime, xgboost
- 606 convert_lightgbm: Add shape to FloatTensor probabilities

- feat: add support for SparkML CountVectorizer conversion 560
- docs: update sparkml doc; cleanups. 559
- fix: 'SparkSession' object has no attribute 'util' 557
- feat: add support for SparkML KMeansModel conversion 556
- fix: SparkML StandardScaler conversion fails when withStd or withMean is set to true 555
- fix: Converter for SparkML VectorAssembler does not support vector inputs correctly 554
- fix: ONNX conversion for Spark OneHotEncoder model 552

- Fix conversion of XGBoost model after being restored 520
- Fix test case condition for onnx=1.11.0 527
- Update CI for ORT 1.11.0 539
- Adjust author and email 539

* Replace 507 + fix bug with XGBoost converter when base_score is None 510
* Use assertRegex instead of assertRegexpMatches for Python 3.11 compatibility. 508
* Support for opset 15 and update version to 1.10.0 505
* add support for quantile objective for LGBM models 503
* Support parameter shape_override and other options for convert_tensorflow 497
* Implement option split to reduce discrepancies for lightgbm regressors 496

* Add requirements.txt to MANIFEST.in 493