def _get_java_obj(self, **kwargs):
return self._new_java_obj(
PCASageMakerEstimator._wrapped_class, kwargs['sagemakerRole'],
kwargs['trainingInstanceType'], kwargs['trainingInstanceCount'],
kwargs['endpointInstanceType'],
kwargs['endpointInitialInstanceCount'],
kwargs['requestRowSerializer'], kwargs['responseRowDeserializer'],
kwargs['trainingInputS3DataPath'],
kwargs['trainingOutputS3DataPath'],
kwargs['trainingInstanceVolumeSizeInGB'],
Option(kwargs['trainingProjectedColumns']),
kwargs['trainingChannelName'], Option(
kwargs['trainingContentType']),
kwargs['trainingS3DataDistribution'],
kwargs['trainingSparkDataFormat'],
kwargs['trainingSparkDataFormatOptions'],
kwargs['trainingInputMode'],
Option(kwargs['trainingCompressionCodec']),
kwargs['trainingMaxRuntimeInSeconds'],
Option(kwargs['trainingKmsKeyId']),
kwargs['modelEnvironmentVariables'],
kwargs['endpointCreationPolicy'], kwargs['sagemakerClient'],
Option(kwargs['region']), kwargs['s3Client'], kwargs['stsClient'],
kwargs['modelPrependInputRowsToTransformationRows'],
kwargs['deleteStagingDataAfterTraining'],
kwargs['namePolicyFactory'], kwargs['uid'])
def _to_java(self):
if self._java_obj is None:
self._java_obj = self._new_java_obj(
self._wrapped_class, Option(self.model_name),
Option(self.endpoint_config_name), Option(self.endpoint_name))
return self._java_obj
def _to_java(self):
if self._java_obj is None:
self._java_obj = self._new_java_obj(
ProtobufRequestRowSerializer._wrapped_class,
Option(self.schema), self.featuresColumnName)
return self._java_obj
def __init__(self,
endpointInstanceType,
endpointInitialInstanceCount,
requestRowSerializer,
responseRowDeserializer,
existingEndpointName=None,
modelImage=None,
modelPath=None,
modelEnvironmentVariables=None,
modelExecutionRoleARN=None,
endpointCreationPolicy=EndpointCreationPolicy.CREATE_ON_CONSTRUCT,
sagemakerClient=SageMakerClients.create_sagemaker_client(),
prependResultRows=True,
namePolicy=RandomNamePolicy(),
uid=None,
javaObject=None):
super(SageMakerModel, self).__init__()
if modelEnvironmentVariables is None:
modelEnvironmentVariables = {}
if javaObject:
self._java_obj = javaObject
else:
if uid is None:
uid = Identifiable._randomUID()
self._java_obj = self._new_java_obj(
SageMakerModel._wrapped_class,
Option(endpointInstanceType),
Option(endpointInitialInstanceCount),
requestRowSerializer,
responseRowDeserializer,
Option(existingEndpointName),
Option(modelImage),
Option(modelPath),
modelEnvironmentVariables,
Option(modelExecutionRoleARN),
endpointCreationPolicy,
sagemakerClient,
prependResultRows,
namePolicy,
uid
)
self._resetUid(self._call_java("uid"))