zero323 commented on a change in pull request #30471:
URL: https://github.com/apache/spark/pull/30471#discussion_r534487321
##########
File path: python/pyspark/ml/classification.py
##########
@@ -2991,8 +2994,59 @@ def _to_java(self):
_java_obj.setRawPredictionCol(self.getRawPredictionCol())
return _java_obj
+ @classmethod
+ def read(cls):
+ return OneVsRestReader(cls)
+
+ def write(self):
+ if isinstance(self.getClassifier(), JavaMLWritable):
+ return JavaMLWriter(self)
+ else:
+ return OneVsRestWriter(self)
+
+
+class OneVsRestSharedReadWrite:
+ @staticmethod
+ def saveImpl(instance, sc, path, extraMetadata=None):
+ skipParams = ['classifier']
+ jsonParams = DefaultParamsWriter.extractJsonParams(instance,
skipParams)
+ DefaultParamsWriter.saveMetadata(instance, path, sc,
paramMap=jsonParams,
+ extraMetadata=extraMetadata)
+ classifierPath = os.path.join(path, 'classifier')
+ instance.getClassifier().save(classifierPath)
+
+ @staticmethod
+ def loadClassifier(path, sc):
+ classifierPath = os.path.join(path, 'classifier')
+ return DefaultParamsReader.loadParamsInstance(classifierPath, sc)
+
+
+class OneVsRestReader(MLReader):
+ def __init__(self, cls):
+ super(OneVsRestReader, self).__init__()
+ self.cls = cls
+
+ def load(self, path):
+ metadata = DefaultParamsReader.loadMetadata(path, self.sc)
+ if not DefaultParamsReader.isPythonParamsInstance(metadata):
+ return JavaMLReader(self.cls).load(path)
+ else:
+ classifier = OneVsRestSharedReadWrite.loadClassifier(path, self.sc)
+ ova = OneVsRest(classifier=classifier)._resetUid(metadata['uid'])
+ DefaultParamsReader.getAndSetParams(ova, metadata,
skipParams=['classifier'])
+ return ova
+
+
+class OneVsRestWriter(MLWriter):
+ def __init__(self, instance):
+ super(OneVsRestWriter, self).__init__()
+ self.instance = instance
+
+ def saveImpl(self, path):
+ OneVsRestSharedReadWrite.saveImpl(self.instance, self.sc, path)
Review comment:
> Except OneVsRestSharedReadWrite, other Reader/Writer should be public,
similar to Pipeline Reader/Writer
My point was that the particular implementation of `Reader` / `Writer` is
completely irrelevant to the end user. In terms of types we still expect
`MLReader` / `MLWriter` and `OneVsRest` variants are unlikely to be useful for
anyone by devs.
I believe that for the same reason we mark `PipelineReader` and
`PipelineModelWriter` as private in comments:
https://github.com/apache/spark/blob/92bfbcb2e372e8fecfe65bc582c779d9df4036bb/python/pyspark/ml/pipeline.py#L197
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