# 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 *
[docs]@inherit_doc
class RecommendationIndexer(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaEstimator):
"""
Args:
itemInputCol (str): Item Input Col
itemOutputCol (str): Item Output Col
ratingCol (str): Rating Col
userInputCol (str): User Input Col
userOutputCol (str): User Output Col
"""
@keyword_only
def __init__(self, itemInputCol=None, itemOutputCol=None, ratingCol=None, userInputCol=None, userOutputCol=None):
super(RecommendationIndexer, self).__init__()
self._java_obj = self._new_java_obj("com.microsoft.ml.spark.recommendation.RecommendationIndexer")
self.itemInputCol = Param(self, "itemInputCol", "itemInputCol: Item Input Col")
self.itemOutputCol = Param(self, "itemOutputCol", "itemOutputCol: Item Output Col")
self.ratingCol = Param(self, "ratingCol", "ratingCol: Rating Col")
self.userInputCol = Param(self, "userInputCol", "userInputCol: User Input Col")
self.userOutputCol = Param(self, "userOutputCol", "userOutputCol: User Output Col")
if hasattr(self, "_input_kwargs"):
kwargs = self._input_kwargs
else:
kwargs = self.__init__._input_kwargs
self.setParams(**kwargs)
[docs] @keyword_only
def setParams(self, itemInputCol=None, itemOutputCol=None, ratingCol=None, userInputCol=None, userOutputCol=None):
"""
Set the (keyword only) parameters
Args:
itemInputCol (str): Item Input Col
itemOutputCol (str): Item Output Col
ratingCol (str): Rating Col
userInputCol (str): User Input Col
userOutputCol (str): User Output Col
"""
if hasattr(self, "_input_kwargs"):
kwargs = self._input_kwargs
else:
kwargs = self.__init__._input_kwargs
return self._set(**kwargs)
[docs] def setItemOutputCol(self, value):
"""
Args:
itemOutputCol (str): Item Output Col
"""
self._set(itemOutputCol=value)
return self
[docs] def getItemOutputCol(self):
"""
Returns:
str: Item Output Col
"""
return self.getOrDefault(self.itemOutputCol)
[docs] def setRatingCol(self, value):
"""
Args:
ratingCol (str): Rating Col
"""
self._set(ratingCol=value)
return self
[docs] def getRatingCol(self):
"""
Returns:
str: Rating Col
"""
return self.getOrDefault(self.ratingCol)
[docs] def setUserOutputCol(self, value):
"""
Args:
userOutputCol (str): User Output Col
"""
self._set(userOutputCol=value)
return self
[docs] def getUserOutputCol(self):
"""
Returns:
str: User Output Col
"""
return self.getOrDefault(self.userOutputCol)
[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.recommendation.RecommendationIndexer"
@staticmethod
def _from_java(java_stage):
module_name=RecommendationIndexer.__module__
module_name=module_name.rsplit(".", 1)[0] + ".RecommendationIndexer"
return from_java(java_stage, module_name)
def _create_model(self, java_model):
return RecommendationIndexerModel(java_model)
[docs]class RecommendationIndexerModel(ComplexParamsMixin, JavaModel, JavaMLWritable, JavaMLReadable):
"""
Model fitted by :class:`RecommendationIndexer`.
This class is left empty on purpose.
All necessary methods are exposed through inheritance.
"""
[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.recommendation.RecommendationIndexerModel"
@staticmethod
def _from_java(java_stage):
module_name=RecommendationIndexerModel.__module__
module_name=module_name.rsplit(".", 1)[0] + ".RecommendationIndexerModel"
return from_java(java_stage, module_name)