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From jkbradley <...@git.apache.org>
Subject [GitHub] spark pull request: [SPARK-13786][ML][Pyspark] Add save/load for p...
Date Tue, 05 Apr 2016 19:42:02 GMT
Github user jkbradley commented on a diff in the pull request:

    https://github.com/apache/spark/pull/12020#discussion_r58602540
  
    --- Diff: python/pyspark/ml/tuning.py ---
    @@ -480,19 +653,87 @@ def copy(self, extra=None):
                 extra = dict()
             return TrainValidationSplitModel(self.bestModel.copy(extra))
     
    +    @since("2.0.0")
    +    def write(self):
    +        """Returns an JavaMLWriter instance for this ML instance."""
    +        return JavaMLWriter(self)
    +
    +    @since("2.0.0")
    +    def save(self, path):
    +        """Save this ML instance to the given path, a shortcut of `write().save(path)`."""
    +        self.write().save(path)
    +
    +    @classmethod
    +    @since("2.0.0")
    +    def read(cls):
    +        """Returns an MLReader instance for this class."""
    +        return JavaMLReader(cls)
    +
    +    @classmethod
    +    def _from_java(cls, java_stage):
    +        """
    +        Given a Java TrainValidationSplitModel, create and return a Python wrapper of
it.
    +        Used for ML persistence.
    +        """
    +
    +        # Load information from java_stage to the instance.
    +        bestModel = JavaWrapper._from_java(java_stage.bestModel())
    +        estimator, epms, evaluator = super(TrainValidationSplitModel, cls)._from_java(java_stage)
    +        # Create a new instance of this stage.
    +        py_stage = cls(bestModel=bestModel)\
    +            .setEstimator(estimator).setEstimatorParamMaps(epms).setEvaluator(evaluator)
    --- End diff --
    
    Use _copyValues


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