comprehend_create_endpoint: Creates a model-specific endpoint for synchronous inference...

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see Managing endpoints

Description

Creates a model-specific endpoint for synchronous inference for a previously trained custom model For information about endpoints, see Managing endpoints.

See https://paws-r.github.io/docs/comprehend/create_endpoint.html for full documentation.

Usage

comprehend_create_endpoint(
  EndpointName,
  ModelArn,
  DesiredInferenceUnits,
  ClientRequestToken = NULL,
  Tags = NULL,
  DataAccessRoleArn = NULL
)

Arguments

EndpointName	[required] This is the descriptive suffix that becomes part of the EndpointArn used for all subsequent requests to this resource.
ModelArn	[required] The Amazon Resource Number (ARN) of the model to which the endpoint will be attached.
DesiredInferenceUnits	[required] The desired number of inference units to be used by the model using this endpoint. Each inference unit represents of a throughput of 100 characters per second.
ClientRequestToken	An idempotency token provided by the customer. If this token matches a previous endpoint creation request, Amazon Comprehend will not return a ResourceInUseException.
Tags	Tags associated with the endpoint being created. A tag is a key-value pair that adds metadata to the endpoint. For example, a tag with "Sales" as the key might be added to an endpoint to indicate its use by the sales department.
DataAccessRoleArn	The Amazon Resource Name (ARN) of the AWS identity and Access Management (IAM) role that grants Amazon Comprehend read access to trained custom models encrypted with a customer managed key (ModelKmsKeyId).

paws.machine.learning documentation built on Feb. 16, 2023, 5:24 p.m.