def __init__()

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

• 44 lines of code
• 5 McCabe index (conditional complexity)

    def __init__(self,
                 trainingImage,
                 modelImage,
                 trainingInstanceType,
                 trainingInstanceCount,
                 endpointInstanceType,
                 endpointInitialInstanceCount,
                 requestRowSerializer,
                 responseRowDeserializer,
                 hyperParameters=None,
                 trainingInputS3DataPath=S3AutoCreatePath(),
                 trainingOutputS3DataPath=S3AutoCreatePath(),
                 trainingInstanceVolumeSizeInGB=1024,
                 trainingProjectedColumns=None,
                 trainingChannelName="train",
                 trainingContentType=None,
                 trainingS3DataDistribution="ShardedByS3Key",
                 trainingSparkDataFormat="sagemaker",
                 trainingSparkDataFormatOptions=None,
                 trainingInputMode="File",
                 trainingCompressionCodec=None,
                 trainingMaxRuntimeInSeconds=24*60*60,
                 trainingKmsKeyId=None,
                 modelEnvironmentVariables=None,
                 endpointCreationPolicy=EndpointCreationPolicy.CREATE_ON_CONSTRUCT,
                 sagemakerClient=SageMakerClients.create_sagemaker_client(),
                 sagemakerRole=IAMRoleFromConfig(),
                 s3Client=SageMakerClients.create_s3_default_client(),
                 stsClient=SageMakerClients.create_sts_default_client(),
                 modelPrependInputRowsToTransformationRows=True,
                 deleteStagingDataAfterTraining=True,
                 namePolicyFactory=RandomNamePolicyFactory(),
                 uid=None):

        if trainingSparkDataFormatOptions is None:
            trainingSparkDataFormatOptions = {}

        if modelEnvironmentVariables is None:
            modelEnvironmentVariables = {}

        if hyperParameters is None:
            hyperParameters = {}

        if uid is None:
            uid = Identifiable._randomUID()

        kwargs = locals().copy()
        del kwargs['self']

        super(SageMakerEstimator, self).__init__(**kwargs)