class_docstr: Utility class to help create wrapper classes from Java/Scala
  implementations of pipeline components.
class_docstr_tok: ["Utility","class","to","help","create","wrapper","classes","from","Java\/Scala","implementations","of","pipeline","components","."]
docstr: Transforms the embedded params from the companion Java object.
docstr_tok: ["Transforms","the","embedded","params","from","the","companion","Java","object","."]
code: def _transfer_params_from_java(self) -> None:
      """
      Transforms the embedded params from the companion Java object.
      """
      sc = SparkContext._active_spark_context
      assert sc is not None and self._java_obj is not None
  
      for param in self.params:
          if self._java_obj.hasParam(param.name):
              java_param = self._java_obj.getParam(param.name)
              # SPARK-14931: Only check set params back to avoid default params mismatch.
              if self._java_obj.isSet(java_param):
                  java_value = self._java_obj.getOrDefault(java_param)
                  if param.typeConverter.__name__.startswith("toList"):
                      value = [
                          _java2py(sc, x) for x in list(java_value)
                      ]
                  else:
                      value = _java2py(sc, java_value)
                  self._set(**{param.name: value})
              # SPARK-10931: Temporary fix for params that have a default in Java
              if self._java_obj.hasDefault(
                  java_param
              ) and not self.isDefined(param):
                  value = _java2py(
                      sc, self._java_obj.getDefault(java_param)
                  ).get()
                  self._setDefault(**{param.name: value})
  
imports: from abc import ABCMeta, abstractmethod
  from typing import Any, Generic, Optional, List, Type, TypeVar, TYPE_CHECKING
  from pyspark import since
  from pyspark import SparkContext
  from pyspark.sql import DataFrame
  from pyspark.ml import Estimator, Predictor, PredictionModel, Transformer, Model
  from pyspark.ml.base import _PredictorParams
  from pyspark.ml.param import Param, Params
  from pyspark.ml.util import _jvm
  from pyspark.ml.common import inherit_doc, _java2py, _py2java
label_desc: Use image node_id 5 for calling the JavaParams obj's underlying member method code with example usage: obj._transfer_params_from_java() without return types