def _get_java_obj()

in sagemaker-pyspark-sdk/src/sagemaker_pyspark/algorithms/LinearLearnerSageMakerEstimator.py [0:0]

• 37 lines of code
• 3 McCabe index (conditional complexity)

    def _get_java_obj(self, **kwargs):
        if 'javaObject' in kwargs and kwargs['javaObject'] is not None:
            return kwargs['javaObject']
        else:
            return self._new_java_obj(
                LinearLearnerMultiClassClassifier._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']
            )