def __init__(
self,
endpoint_name,
sagemaker_session=None,
serializer=LibSVMSerializer(),
deserializer=CSVDeserializer(),
):
"""Initialize an ``XGBoostPredictor``.
Args:
endpoint_name (str): The name of the endpoint to perform inference on.
sagemaker_session (sagemaker.session.Session): Session object which manages
interactions with Amazon SageMaker APIs and any other AWS services needed.
If not specified, the estimator creates one using the default AWS configuration
chain.
serializer (sagemaker.serializers.BaseSerializer): Optional. Default
serializes input data to LibSVM format
deserializer (sagemaker.deserializers.BaseDeserializer): Optional.
Default parses the response from text/csv to a Python list.
"""
super(XGBoostPredictor, self).__init__(
endpoint_name,
sagemaker_session,
serializer=serializer,
deserializer=deserializer,
)
def __init__(self, endpoint_name, sagemaker_session=None):
"""Initialize an ``XGBoostPredictor``.
Args:
endpoint_name (str): The name of the endpoint to perform inference on.
sagemaker_session (sagemaker.session.Session): Session object which manages
interactions with Amazon SageMaker APIs and any other AWS services needed.
If not specified, the estimator creates one using the default AWS configuration
chain.
"""
super(XGBoostPredictor, self).__init__(endpoint_name,
sagemaker_session,
LibSVMSerializer(),
CSVDeserializer())
def libsvm_serializer():
return LibSVMSerializer()