Create Ai Workload Config

sagemaker_create_ai_workload_config

R Documentation

Creates a reusable AI workload configuration that defines datasets, data sources, and benchmark tool settings for consistent performance testing of generative AI inference deployments on Amazon SageMaker AI

Description

Creates a reusable AI workload configuration that defines datasets, data sources, and benchmark tool settings for consistent performance testing of generative AI inference deployments on Amazon SageMaker AI.

Usage

sagemaker_create_ai_workload_config(AIWorkloadConfigName, DatasetConfig,
  AIWorkloadConfigs, Tags)

Arguments

AIWorkloadConfigName	[required] The name of the AI workload configuration. The name must be unique within your Amazon Web Services account in the current Amazon Web Services Region.
DatasetConfig	The dataset configuration for the workload. Specify input data channels with their data sources for benchmark workloads.
AIWorkloadConfigs	The benchmark tool configuration and workload specification. Provide the specification as an inline YAML or JSON string.
Tags	The metadata that you apply to Amazon Web Services resources to help you categorize and organize them. Each tag consists of a key and a value, both of which you define. For more information, see Tagging Amazon Web Services Resources in the Amazon Web Services General Reference.

Value

A list with the following syntax:

list(
  AIWorkloadConfigArn = "string"
)

Request syntax

svc$create_ai_workload_config(
  AIWorkloadConfigName = "string",
  DatasetConfig = list(
    InputDataConfig = list(
      list(
        ChannelName = "string",
        DataSource = list(
          S3DataSource = list(
            S3Uri = "string"
          )
        )
      )
    )
  ),
  AIWorkloadConfigs = list(
    WorkloadSpec = list(
      Inline = "string"
    )
  ),
  Tags = list(
    list(
      Key = "string",
      Value = "string"
    )
  )
)