Source code for mmlspark.io.http.CustomOutputParser

# Copyright (C) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See LICENSE in project root for information.


import sys
if sys.version >= '3':
    basestring = str

from pyspark.ml.param.shared import *
from pyspark import keyword_only
from pyspark.ml.util import JavaMLReadable, JavaMLWritable
from mmlspark.core.serialize.java_params_patch import *
from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
from pyspark.ml.common import inherit_doc
from mmlspark.core.schema.Utils import *
from mmlspark.core.schema.TypeConversionUtils import generateTypeConverter, complexTypeConverter

[docs]@inherit_doc class CustomOutputParser(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer): """ Args: inputCol (str): The name of the input column outputCol (str): The name of the output column udfPython (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 """ @keyword_only def __init__(self, inputCol=None, outputCol=None, udfPython=None, udfScala=None): super(CustomOutputParser, self).__init__() self._java_obj = self._new_java_obj("com.microsoft.ml.spark.io.http.CustomOutputParser") self._cache = {} self.inputCol = Param(self, "inputCol", "inputCol: The name of the input column") self.outputCol = Param(self, "outputCol", "outputCol: The name of the output column") self.udfPython = Param(self, "udfPython", "udfPython: User Defined Python Function to be applied to the DF input col") self.udfScala = Param(self, "udfScala", "udfScala: User Defined Function to be applied to the DF input col", generateTypeConverter("udfScala", self._cache, complexTypeConverter)) if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs self.setParams(**kwargs)
[docs] @keyword_only def setParams(self, inputCol=None, outputCol=None, udfPython=None, udfScala=None): """ Set the (keyword only) parameters Args: inputCol (str): The name of the input column outputCol (str): The name of the output column udfPython (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 """ if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs return self._set(**kwargs)
[docs] def setInputCol(self, value): """ Args: inputCol (str): The name of the input column """ self._set(inputCol=value) return self
[docs] def getInputCol(self): """ Returns: str: The name of the input column """ return self.getOrDefault(self.inputCol)
[docs] def setOutputCol(self, value): """ Args: outputCol (str): The name of the output column """ self._set(outputCol=value) return self
[docs] def getOutputCol(self): """ Returns: str: The name of the output column """ return self.getOrDefault(self.outputCol)
[docs] def setUdfPython(self, value): """ Args: udfPython (object): User Defined Python Function to be applied to the DF input col """ self._set(udfPython=value) return self
[docs] def getUdfPython(self): """ Returns: object: User Defined Python Function to be applied to the DF input col """ return self.getOrDefault(self.udfPython)
[docs] def setUdfScala(self, value): """ Args: udfScala (object): User Defined Function to be applied to the DF input col """ self._set(udfScala=value) return self
[docs] def getUdfScala(self): """ Returns: object: User Defined Function to be applied to the DF input col """ return self._cache.get("udfScala", None)
[docs] @classmethod def read(cls): """ Returns an MLReader instance for this class. """ return JavaMMLReader(cls)
[docs] @staticmethod def getJavaPackage(): """ Returns package name String. """ return "com.microsoft.ml.spark.io.http.CustomOutputParser"
@staticmethod def _from_java(java_stage): module_name=CustomOutputParser.__module__ module_name=module_name.rsplit(".", 1)[0] + ".CustomOutputParser" return from_java(java_stage, module_name)