code: def _mml_from_java(java_stage):
      """
      Given a Java object, create and return a Python wrapper of it.
      Used for ML persistence.
  
      Meta-algorithms such as Pipeline should override this method as a classmethod.
      """
  
      def __get_class(clazz):
          """
          Loads Python class from its name.
          """
          parts = clazz.split(".")
          module = ".".join(parts[:-1])
          m = __import__(module)
          for comp in parts[1:]:
              m = getattr(m, comp)
          return m
  
      stage_name = (
          java_stage.getClass()
          .getName()
          .replace("org.apache.spark", "pyspark")
      )
      stage_name = stage_name.replace(
          "com.microsoft.azure.synapse.ml", "synapse.ml"
      )
      # Generate a default new instance from the stage_name class.
      py_type = __get_class(stage_name)
      if issubclass(py_type, JavaParams):
          # Load information from java_stage to the instance.
          py_stage = py_type()
          py_stage._java_obj = java_stage
          py_stage._resetUid(java_stage.uid())
          py_stage._transfer_params_from_java()
      elif hasattr(py_type, "_from_java"):
          py_stage = py_type._from_java(java_stage)
      else:
          raise NotImplementedError(
              "This Java stage cannot be loaded into Python currently: %r"
              % stage_name,
          )
      return py_stage
  
file_path: SynapseML/core/src/main/python/synapse/ml/core/serialize/java_params_patch.py
imports: from pyspark.ml.wrapper import JavaParams, JavaWrapper
  from py4j.java_gateway import JavaObject
  from pyspark import RDD, SparkContext
  from pyspark.serializers import PickleSerializer, AutoBatchedSerializer
  from pyspark.sql import DataFrame, SQLContext
  from pyspark.ml.common import _to_java_object_rdd, _java2py
  import pyspark
  from pyspark.ml import PipelineModel
  from pyspark.sql.types import DataType
label_desc: Use image node_id 1 for calling a global function with example usage: _mml_from_java(java_stage) and returns: py_stage, m