MXNetPredictor: MXNetPredictor Class

In DyfanJones/sagemaker-r-mlframework: sagemaker machine learning developed by amazon

MXNetPredictor Class

Description

A Predictor for inference against MXNet Endpoints. This is able to serialize Python lists, dictionaries, and numpy arrays to multidimensional tensors for MXNet inference.

Super classes

sagemaker.mlcore::PredictorBase -> sagemaker.mlcore::Predictor -> MXNetPredictor

Methods

Public methods

• MXNetPredictor$new()

• MXNetPredictor$clone()

Inherited methods

• sagemaker.mlcore::Predictor$delete_endpoint()

• sagemaker.mlcore::Predictor$delete_model()

• sagemaker.mlcore::Predictor$delete_predictor()

• sagemaker.mlcore::Predictor$disable_data_capture()

• sagemaker.mlcore::Predictor$enable_data_capture()

• sagemaker.mlcore::Predictor$endpoint_context()

• sagemaker.mlcore::Predictor$format()

• sagemaker.mlcore::Predictor$list_monitors()

• sagemaker.mlcore::Predictor$predict()

• sagemaker.mlcore::Predictor$update_data_capture_config()

• sagemaker.mlcore::Predictor$update_endpoint()

---

Method new()

Initialize an “MXNetPredictor“.

Usage

MXNetPredictor$new(
  endpoint_name,
  sagemaker_session = NULL,
  serializer = JSONSerializer$new(),
  deserializer = JSONDeserializer$new()
)

Arguments

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

(callable): Optional. Default serializes input data to json. Handles dicts, lists, and numpy arrays.

deserializer

(callable): Optional. Default parses the response using “json.load(...)“.

---

Method clone()

The objects of this class are cloneable with this method.

Usage

MXNetPredictor$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/sagemaker-r-mlframework documentation built on March 18, 2022, 7:41 a.m.