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 a Python ParamMap into a Java ParamMap.
docstr_tok: ["Transforms","a","Python","ParamMap","into","a","Java","ParamMap","."]
code: def _transfer_param_map_to_java(
      self, pyParamMap: "ParamMap"
  ) -> "JavaObject":
      """
      Transforms a Python ParamMap into a Java ParamMap.
      """
      paramMap = JavaWrapper._new_java_obj(
          "org.apache.spark.ml.param.ParamMap"
      )
      for param in self.params:
          if param in pyParamMap:
              pair = self._make_java_param_pair(
                  param, pyParamMap[param]
              )
              paramMap.put([pair])
      return paramMap
  
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 3 for calling the JavaParams obj's underlying member method code with example usage: obj._transfer_param_map_to_java(pyParamMap) and returns: paramMap