Source code for synapse.ml.stages.StratifiedRepartition

# 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 import SparkContext, SQLContext
from pyspark.sql import DataFrame
from pyspark.ml.param.shared import *
from pyspark import keyword_only
from pyspark.ml.util import JavaMLReadable, JavaMLWritable
from synapse.ml.core.platform import running_on_synapse_internal
from synapse.ml.core.serialize.java_params_patch import *
from pyspark.ml.wrapper import JavaTransformer, JavaEstimator, JavaModel
from pyspark.ml.evaluation import JavaEvaluator
from pyspark.ml.common import inherit_doc
from synapse.ml.core.schema.Utils import *
from pyspark.ml.param import TypeConverters
from synapse.ml.core.schema.TypeConversionUtils import generateTypeConverter, complexTypeConverter


[docs]@inherit_doc class StratifiedRepartition(ComplexParamsMixin, JavaMLReadable, JavaMLWritable, JavaTransformer): """ Args: labelCol (str): The name of the label column mode (str): Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic seed (long): random seed """ labelCol = Param(Params._dummy(), "labelCol", "The name of the label column", typeConverter=TypeConverters.toString) mode = Param(Params._dummy(), "mode", "Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic", typeConverter=TypeConverters.toString) seed = Param(Params._dummy(), "seed", "random seed") @keyword_only def __init__( self, java_obj=None, labelCol=None, mode="mixed", seed=1518410069 ): super(StratifiedRepartition, self).__init__() if java_obj is None: self._java_obj = self._new_java_obj("com.microsoft.azure.synapse.ml.stages.StratifiedRepartition", self.uid) else: self._java_obj = java_obj self._setDefault(mode="mixed") self._setDefault(seed=1518410069) if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs if java_obj is None: for k,v in kwargs.items(): if v is not None: getattr(self, "set" + k[0].upper() + k[1:])(v)
[docs] @keyword_only def setParams( self, labelCol=None, mode="mixed", seed=1518410069 ): """ Set the (keyword only) parameters """ if hasattr(self, "_input_kwargs"): kwargs = self._input_kwargs else: kwargs = self.__init__._input_kwargs return self._set(**kwargs)
[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.azure.synapse.ml.stages.StratifiedRepartition"
@staticmethod def _from_java(java_stage): module_name=StratifiedRepartition.__module__ module_name=module_name.rsplit(".", 1)[0] + ".StratifiedRepartition" return from_java(java_stage, module_name)
[docs] def setLabelCol(self, value): """ Args: labelCol: The name of the label column """ self._set(labelCol=value) return self
[docs] def setMode(self, value): """ Args: mode: Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic """ self._set(mode=value) return self
[docs] def setSeed(self, value): """ Args: seed: random seed """ self._set(seed=value) return self
[docs] def getLabelCol(self): """ Returns: labelCol: The name of the label column """ return self.getOrDefault(self.labelCol)
[docs] def getMode(self): """ Returns: mode: Specify equal to repartition with replacement across all labels, specify original to keep the ratios in the original dataset, or specify mixed to use a heuristic """ return self.getOrDefault(self.mode)
[docs] def getSeed(self): """ Returns: seed: random seed """ return self.getOrDefault(self.seed)