Source code for RankingTrainValidationSplit

# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in the project root for information.

import sys
from mmlspark.RankingTrainValidationSplitModel import RankingTrainValidationSplitModel as tvmodel
from mmlspark._RankingTrainValidationSplit import _RankingTrainValidationSplit
from pyspark import keyword_only
from pyspark.ml.param import Params
from pyspark.ml.tuning import ValidatorParams
from pyspark.ml.util import *

if sys.version >= '3':
    basestring = str


@inherit_doc
class RankingTrainValidationSplit(_RankingTrainValidationSplit, ValidatorParams):
    @keyword_only
    def __init__(self, estimator=None, estimatorParamMaps=None, evaluator=None, seed=None):
        """
        __init__(self, estimator=None, estimatorParamMaps=None, evaluator=None, numFolds=3,\
                 seed=None)
        """
        super(RankingTrainValidationSplit, self).__init__()
        kwargs = self._input_kwargs
        self._set(**kwargs)

    @keyword_only
    def setParams(self, estimator=None, estimatorParamMaps=None, evaluator=None, seed=None):
        """
        setParams(self, estimator=None, estimatorParamMaps=None, evaluator=None, numFolds=3,\
                  seed=None):
        Sets params for cross validator.
        """
        kwargs = self._input_kwargs
        return self._set(**kwargs)

    def copy(self, extra=None):
        """
        Creates a copy of this instance with a randomly generated uid
        and some extra params. This copies creates a deep copy of
        the embedded paramMap, and copies the embedded and extra parameters over.

        :param extra: Extra parameters to copy to the new instance
        :return: Copy of this instance
        """
        if extra is None:
            extra = dict()
        newCV = Params.copy(self, extra)
        if self.isSet(self.estimator):
            newCV.setEstimator(self.getEstimator().copy(extra))
        # estimatorParamMaps remain the same
        if self.isSet(self.evaluator):
            newCV.setEvaluator(self.getEvaluator().copy(extra))
        return newCV

    def _create_model(self, java_model):
        model = tvmodel()
        model._java_obj = java_model
        model._transfer_params_from_java()
        return model

    def _to_java(self):
        """
        Transfer this instance to a Java TrainValidationSplit. Used for ML persistence.
        :return: Java object equivalent to this instance.
        """

        estimator, epms, evaluator = super(RankingTrainValidationSplit, self)._to_java_impl()

        _java_obj = JavaParams._new_java_obj("mmlspark.RankingTrainValidationSplitModel",
                                             self.uid)
        _java_obj.setEstimatorParamMaps(epms)
        _java_obj.setEvaluator(evaluator)
        _java_obj.setEstimator(estimator)
        _java_obj.setTrainRatio(self.getTrainRatio())
        _java_obj.setSeed(self.getSeed())
        _java_obj.setParallelism(self.getParallelism())
        _java_obj.setCollectSubModels(self.getCollectSubModels())
        return _java_obj

    def _fit(self, dataset):
        return self._to_java()._call_java("fit", dataset)