Github user jkbradley commented on a diff in the pull request:
https://github.com/apache/spark/pull/18742#discussion_r131516889
--- Diff: python/pyspark/ml/util.py ---
@@ -283,3 +333,204 @@ def numFeatures(self):
Returns the number of features the model was trained on. If
unknown, returns -1
"""
return self._call_java("numFeatures")
+
+
+@inherit_doc
+class DefaultParamsWritable(MLWritable):
+ """
+ .. note:: DeveloperApi
+
+ Helper trait for making simple `Params` types writable. If a `Params`
class stores
+ all data as [[pyspark.ml.param.Param]] values, then extending this
trait will provide
+ a default implementation of writing saved instances of the class.
+ This only handles simple [[pyspark.ml.param.Param]] types; e.g., it
will not handle
+ [[pyspark.sql.Dataset]].
+
+ @see `DefaultParamsReadable`, the counterpart to this trait
+
+ .. versionadded:: 2.3.0
+ """
+
+ def write(self):
+ """Returns a DefaultParamsWriter instance for this class."""
+ from pyspark.ml.param import Params
+
+ if isinstance(self, Params):
+ return DefaultParamsWriter(self)
+ else:
+ raise TypeError("Cannot use DefautParamsWritable with type %s
because it does not " +
+ " extend Params.", type(self))
+
+
+@inherit_doc
+class DefaultParamsWriter(MLWriter):
+ """
+ .. note:: DeveloperApi
+
+ Specialization of :py:class:`MLWriter` for :py:class:`Params` types
+
+ Class for writing Estimators and Transformers whose parameters are
JSON-serializable.
+
+ .. versionadded:: 2.3.0
+ """
+
+ def __init__(self, instance):
+ super(DefaultParamsWriter, self).__init__()
+ self.instance = instance
+
+ def saveImpl(self, path):
+ DefaultParamsWriter.saveMetadata(self.instance, path, self.sc)
+
+ @staticmethod
+ def saveMetadata(instance, path, sc, extraMetadata=None,
paramMap=None):
+ """
+ Saves metadata + Params to: path + "/metadata"
+ - class
+ - timestamp
+ - sparkVersion
+ - uid
+ - paramMap
+ - (optionally, extra metadata)
+ @param extraMetadata Extra metadata to be saved at same level as
uid, paramMap, etc.
+ @param paramMap If given, this is saved in the "paramMap" field.
+ """
+ metadataPath = os.path.join(path, "metadata")
+ metadataJson = DefaultParamsWriter._get_metadata_to_save(instance,
+ sc,
+
extraMetadata,
+ paramMap)
+ sc.parallelize([metadataJson], 1).saveAsTextFile(metadataPath)
+
+ @staticmethod
+ def _get_metadata_to_save(instance, sc, extraMetadata=None,
paramMap=None):
+ """
+ Helper for [[saveMetadata()]] which extracts the JSON to save.
+ This is useful for ensemble models which need to save metadata for
many sub-models.
+
+ @see [[saveMetadata()]] for details on what this includes.
+ """
+ uid = instance.uid
+ cls = instance.__module__ + '.' + instance.__class__.__name__
+ params = instance.extractParamMap()
+ jsonParams = {}
+ if paramMap is not None:
+ jsonParams = paramMap
+ else:
+ for p in params:
+ jsonParams[p.name] = params[p]
+ basicMetadata = {"class": cls, "timestamp": long(round(time.time()
* 1000)),
+ "sparkVersion": sc.version, "uid": uid,
"paramMap": jsonParams}
+ if extraMetadata is not None:
+ basicMetadata.update(extraMetadata)
+ return json.dumps(basicMetadata, separators=[',', ':'])
+
+
+@inherit_doc
+class DefaultParamsReadable(MLReadable):
+ """
+ .. note:: DeveloperApi
+
+ Helper trait for making simple `Params` types readable. If a `Params`
class stores
+ all data as [[pyspark.ml.param.Param]] values, then extending this
trait will provide
+ a default implementation of reading saved instances of the class.
+ This only handles simple [[pyspark.ml.param.Param]] types; e.g., it
will not handle
+ [[pyspark.sql.Dataset]].
+
+ @see `DefaultParamsWritable`, the counterpart to this trait
+
+ .. versionadded:: 2.3.0
+ """
+
+ @classmethod
+ def read(cls):
+ """Returns a DefaultParamsReader instance for this class."""
+ return DefaultParamsReader(cls)
+
+
+@inherit_doc
+class DefaultParamsReader(MLReader):
+ """
+ .. note:: DeveloperApi
+
+ Specialization of :py:class:`MLReader` for :py:class:`Params` types
+
+ Default `MLReader` implementation for transformers and estimators that
+ contain basic (json-serializable) params and no data. This will not
handle
+ more complex params or types with data (e.g., models with
coefficients).
+
+ .. versionadded:: 2.3.0
+ """
+
+ def __init__(self, cls):
+ super(DefaultParamsReader, self).__init__()
+ self.cls = cls
+
+ @staticmethod
+ def __get_class(clazz):
+ """
+ Loads Python class from its name.
+ """
+ parts = clazz.split('.')
+ module = ".".join(parts[:-1])
+ m = __import__(module)
+ for comp in parts[1:]:
+ m = getattr(m, comp)
+ return m
+
+ def load(self, path):
+ metadata = DefaultParamsReader.loadMetadata(path, self.sc)
+ py_type = DefaultParamsReader.__get_class(metadata['class'])
+ instance = py_type()
+ instance._resetUid(metadata['uid'])
+ DefaultParamsReader.getAndSetParams(instance, metadata)
+ return instance
+
+ @staticmethod
+ def loadMetadata(path, sc, expectedClassName=""):
+ """
+ Load metadata saved using [[DefaultParamsWriter.saveMetadata()]]
+
+ @param expectedClassName If non empty, this is checked against
the loaded metadata.
--- End diff --
I missed this before: the Scala-style ```@param``` and ```@see``` do not
work in Python. Look in other file like pipeline.py for examples of
```:param```, and maybe use ```.. note::``` to replace ```@see```
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