def loadMetadataAndInstance(pyspark_xgb_cls, path, sc, logger):
"""
Load the metadata and the instance of an xgboost.spark._SparkXGBEstimator or
xgboost.spark._SparkXGBModel.
:return: a tuple of (metadata, instance)
"""
metadata = DefaultParamsReader.loadMetadata(
path, sc, expectedClassName=get_class_name(pyspark_xgb_cls))
pyspark_xgb = pyspark_xgb_cls()
DefaultParamsReader.getAndSetParams(pyspark_xgb, metadata)
if "serialized_callbacks" in metadata:
serialized_callbacks = metadata["serialized_callbacks"]
try:
callbacks = cloudpickle.loads(
base64.decodebytes(serialized_callbacks.encode("ascii")))
pyspark_xgb.set(pyspark_xgb.callbacks, callbacks)
except Exception as e: # pylint: disable=W0703
logger.warning(
f"Fails to load the callbacks param due to {e}. Please set the "
"callbacks param manually for the loaded estimator.")
if "init_booster" in metadata:
load_path = os.path.join(path, metadata["init_booster"])
ser_init_booster = (_get_spark_session().read.parquet(
load_path).collect()[0].init_booster)
init_booster = deserialize_booster(ser_init_booster)
pyspark_xgb.set(pyspark_xgb.xgb_model, init_booster)
pyspark_xgb._resetUid(metadata["uid"]) # pylint: disable=protected-access
return metadata, pyspark_xgb
def load(self, path):
metadata = DefaultParamsReader.loadMetadata(path, self.sc)
metadata['paramMap'] = self._deserialize_dict(metadata['paramMap'])
metadata['defaultParamMap'] = self._deserialize_dict(metadata['defaultParamMap'])
py_type = DefaultParamsReader._DefaultParamsReader__get_class(metadata['class'])
instance = py_type()
instance._resetUid(metadata['uid'])
DefaultParamsReader.getAndSetParams(instance, metadata)
return instance
def load(self, path: str) -> "PipelineModel":
metadata = DefaultParamsReader.loadMetadata(path, self.sc)
if "language" not in metadata["paramMap"] or metadata["paramMap"]["language"] != "Python":
return JavaMLReader(cast(Type["JavaMLReadable[PipelineModel]"], self.cls)).load(path)
else:
uid, stages = PipelineSharedReadWrite.load(metadata, self.sc, path)
return PipelineModel(stages=cast(List[Transformer], stages))._resetUid(uid)
def load(self, path):
metadata = DefaultParamsReader.loadMetadata(path, self.sc)
if 'language' not in metadata['paramMap'] or metadata['paramMap']['language'] != 'Python':
return JavaMLReader(self.cls).load(path)
else:
uid, stages = PipelineSharedReadWrite.load(metadata, self.sc, path)
return PipelineModel(stages=stages)._resetUid(uid)
def load(self, path):
metadata = DefaultParamsReader.loadMetadata(path, self.sc)
if "language" not in metadata[
"paramMap"] or metadata["paramMap"]["language"] != "Python":
return JavaMLReader(self.cls).load(path)
else:
uid, stages = PipelineSharedReadWrite.load(metadata, self.sc, path)
return PipelineModel(stages=stages)._resetUid(uid)
def load(metadata, sc, path):
"""
Load metadata and stages for a :py:class:`Pipeline` or :py:class:`PipelineModel`
:return: (UID, list of stages)
"""
stagesDir = os.path.join(path, "stages")
stageUids = metadata['paramMap']['stageUids']
stages = []
for index, stageUid in enumerate(stageUids):
stagePath = \
PipelineSharedReadWrite.getStagePath(stageUid, index, len(stageUids), stagesDir)
stage = DefaultParamsReader.loadParamsInstance(stagePath, sc)
stages.append(stage)
return (metadata['uid'], stages)
def load(metadata: Dict[str, Any], sc: SparkContext,
path: str) -> Tuple[str, List["PipelineStage"]]:
"""
Load metadata and stages for a :py:class:`Pipeline` or :py:class:`PipelineModel`
Returns
-------
tuple
(UID, list of stages)
"""
stagesDir = os.path.join(path, "stages")
stageUids = metadata["paramMap"]["stageUids"]
stages = []
for index, stageUid in enumerate(stageUids):
stagePath = PipelineSharedReadWrite.getStagePath(
stageUid, index, len(stageUids), stagesDir)
stage: "PipelineStage" = DefaultParamsReader.loadParamsInstance(
stagePath, sc)
stages.append(stage)
return (metadata["uid"], stages)
def load(self, path):
metadata = DefaultParamsReader.loadMetadata(path, self.sc)
uid, stages = PipelineSharedReadWrite.load(metadata, self.sc, path)
return AddResidualConnection(stages=stages)._resetUid(uid)
