class_docstr: Args:
  
      inputCol (str): The name of the input column (default: )
      outputCol (str): The name of the output column
      udf (object): User Defined Python Function to be applied to the DF input col
      udfScala (object): User Defined Function to be applied to the DF input col
class_docstr_tok: ["Args",":","inputCol","(","str",")",":","The","name","of","the","input","column","(","default",":",")","outputCol","(","str",")",":","The","name","of","the","output","column","udf","(","object",")",":","User","Defined","Python","Function","to","be","applied","to","the","DF","input","col","udfScala","(","object",")",":","User","Defined","Function","to","be","applied","to","the","DF","input","col"]
docstr: Returns package name String.
docstr_tok: ["Returns","package","name","String","."]
code: def getJavaPackage():
      """Returns package name String."""
      return "com.microsoft.azure.synapse.ml.stages.UDFTransformer"
  
imports: import sys
  from pyspark.ml.param.shared import *
  from synapse.ml.stages._UDFTransformer import _UDFTransformer
  from pyspark import keyword_only
  from pyspark.ml.util import JavaMLReadable, JavaMLWritable
  from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
  from pyspark.ml.common import inherit_doc
  from pyspark.sql.functions import UserDefinedFunction
  from pyspark.ml.common import inherit_doc
  from synapse.ml.core.schema.Utils import *
label_desc: Use image node_id 11 for calling the UDFTransformer obj's underlying member method code with example usage: obj.getJavaPackage() and returns: str