deploy_config: Export Airflow deploy config from a SageMaker model

In DyfanJones/sagemaker-r-workflow: sagemaker pipeline and workflows

Export Airflow deploy config from a SageMaker model

Description

Export Airflow deploy config from a SageMaker model

Usage

deploy_config(
  model,
  initial_instance_count,
  instance_type,
  endpoint_name = NULL,
  tags = NULL
)

Arguments

model	(sagemaker.model.Model): The SageMaker model to export the Airflow config from.
initial_instance_count	(int): The initial number of instances to run in the “Endpoint“ created from this “Model“.
instance_type	(str): The EC2 instance type to deploy this Model to. For example, 'ml.p2.xlarge'.
endpoint_name	(str): The name of the endpoint to create (default: None). If not specified, a unique endpoint name will be created.
tags	(list[dict]): List of tags for labeling a training job. For more, see https://docs.aws.amazon.com/sagemaker/latest/dg/API_Tag.html.

Value

dict: Deploy config that can be directly used by SageMakerEndpointOperator in Airflow.

DyfanJones/sagemaker-r-workflow documentation built on April 3, 2022, 11:28 p.m.