EndpointConfigStep: Sagemaker EndpointConfigStep task class

In DyfanJones/aws-step-functions-data-science-sdk-r: R SDK for `AWS Stepfunctions`

Description

Creates a Task State to 'create an endpoint configuration in SageMaker' https://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpointConfig.html.

Super classes

stepfunctions::Block -> stepfunctions::State -> stepfunctions::Task -> EndpointConfigStep

Methods

Public methods

• EndpointConfigStep$new()

• EndpointConfigStep$clone()

Inherited methods

• stepfunctions::Block$is_field_allowed()

• stepfunctions::Block$to_json()

• stepfunctions::State$.next()

• stepfunctions::State$accept()

• stepfunctions::State$add_catch()

• stepfunctions::State$add_retry()

• stepfunctions::State$format()

• stepfunctions::State$output()

• stepfunctions::State$to_list()

• stepfunctions::State$update_parameters()

• stepfunctions::Task$allowed_fields()

---

Method new()

Initialize EndpointConfigStep class

Usage

EndpointConfigStep$new(
  state_id,
  endpoint_config_name,
  model_name,
  initial_instance_count,
  instance_type,
  variant_name = "AllTraffic",
  data_capture_config = NULL,
  tags = NULL,
  ...
)

Arguments

state_id

(str): State name whose length **must be** less than or equal to 128 unicode characters. State names **must be** unique within the scope of the whole state machine.

endpoint_config_name

(str or Placeholder): The name of the endpoint configuration to create. We recommend to use :py:class: '~stepfunctions.inputs.ExecutionInput' placeholder collection to pass the value dynamically in each execution.

model_name

(str or Placeholder): The name of the SageMaker model to attach to the endpoint configuration. We recommend to use :py:class: '~stepfunctions.inputs.ExecutionInput' placeholder collection to pass the value dynamically in each execution.

initial_instance_count

(int or Placeholder): The initial number of instances to run in the “Endpoint“ created from this “Model“.

instance_type

(str or Placeholder): The EC2 instance type to deploy this Model to. For example, 'ml.p2.xlarge'.

variant_name

(str, optional): The name of the production variant.

data_capture_config

(sagemaker.model_monitor.DataCaptureConfig, optional): Specifies configuration related to Endpoint data capture for use with Amazon SageMaker Model Monitoring. Default: None.

tags

(list[list], optional): 'List to tags' https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html to associate with the resource.

...

: Extra Fields passed to Task class

---

Method clone()

The objects of this class are cloneable with this method.

Usage

EndpointConfigStep$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

DyfanJones/aws-step-functions-data-science-sdk-r documentation built on Dec. 17, 2021, 5:31 p.m.