SageMaker / Client / create_training_plan

create_training_plan#

SageMaker.Client.create_training_plan(**kwargs)#

Creates a new training plan in SageMaker to reserve compute capacity.

Amazon SageMaker Training Plan is a capability within SageMaker that allows customers to reserve and manage GPU capacity for large-scale AI model training. It provides a way to secure predictable access to computational resources within specific timelines and budgets, without the need to manage underlying infrastructure.

How it works

Plans can be created for specific resources such as SageMaker Training Jobs or SageMaker HyperPod clusters, automatically provisioning resources, setting up infrastructure, executing workloads, and handling infrastructure failures.

Plan creation workflow

  • Users search for available plan offerings based on their requirements (e.g., instance type, count, start time, duration) using the SearchTrainingPlanOfferings API operation.

  • They create a plan that best matches their needs using the ID of the plan offering they want to use.

  • After successful upfront payment, the plan’s status becomes Scheduled.

  • The plan can be used to:

    • Queue training jobs.

    • Allocate to an instance group of a SageMaker HyperPod cluster.

  • When the plan start date arrives, it becomes Active. Based on available reserved capacity:

    • Training jobs are launched.

    • Instance groups are provisioned.

Plan composition

A plan can consist of one or more Reserved Capacities, each defined by a specific instance type, quantity, Availability Zone, duration, and start and end times. For more information about Reserved Capacity, see ``ReservedCapacitySummary ``.

See also: AWS API Documentation

Request Syntax

response = client.create_training_plan(
    TrainingPlanName='string',
    TrainingPlanOfferingId='string',
    Tags=[
        {
            'Key': 'string',
            'Value': 'string'
        },
    ]
)
Parameters:

  • TrainingPlanName (string) –

    [REQUIRED]

    The name of the training plan to create.

  • TrainingPlanOfferingId (string) –

    [REQUIRED]

    The unique identifier of the training plan offering to use for creating this plan.

  • Tags (list) –

    An array of key-value pairs to apply to this training plan.

    • (dict) –

      A tag object that consists of a key and an optional value, used to manage metadata for SageMaker Amazon Web Services resources.

      You can add tags to notebook instances, training jobs, hyperparameter tuning jobs, batch transform jobs, models, labeling jobs, work teams, endpoint configurations, and endpoints. For more information on adding tags to SageMaker resources, see AddTags.

      For more information on adding metadata to your Amazon Web Services resources with tagging, see Tagging Amazon Web Services resources. For advice on best practices for managing Amazon Web Services resources with tagging, see Tagging Best Practices: Implement an Effective Amazon Web Services Resource Tagging Strategy.

      • Key (string) – [REQUIRED]

        The tag key. Tag keys must be unique per resource.

      • Value (string) – [REQUIRED]

        The tag value.

Return type:

dict

Returns:

Response Syntax

{
    'TrainingPlanArn': 'string'
}

Response Structure

  • (dict) –

    • TrainingPlanArn (string) –

      The Amazon Resource Name (ARN); of the created training plan.

Exceptions