View training plan details - Amazon SageMaker AI

View training plan details

To monitor the status or retrieve details of a training plan, you can use the DescribeTrainingPlan API. The API response includes a Status field, which reflects the current state of the training plan:

  • If the plan purchase fails, the status is set to Failed.

  • Upon successful payment, the status transitions from Pending to Scheduled, based on the plan's start date.

  • When the plan reaches its start date, the status changes to Active.

  • For plans with multiple discontinuous reserved capacities, the status reverts to Scheduled between active periods, until the start date of the next reserved capacity.

  • After the plan's end date, the status becomes Expired.

Once the status is Scheduled, you can utilize the capacity reserved in the plan for your SageMaker training jobs or HyperPod cluster workloads.

Note
  • Training jobs associated with the plan remain in Pending status until the plan becomes Active.

  • For HyperPod clusters using a training plan for compute capacity, the instance group status appears as InService once created.

The following example uses an AWS CLI command to retrieve the details of a training plan by its name.

aws sagemaker describe-training-plan \ --training-plan-name "name"

This JSON document is a sample response from the SageMaker training plans API. This response provides details about a training plan that has been successfully created.

{ "AvailableInstanceCount": 2, "CurrencyCode": "USD", "DurationHours": 48, "DurationMinutes": 0, "EndTime": "2024-09-28T04:30:00-07:00", "InUseInstanceCount": 2, "ReservedCapacitySummaries": [ { "AvailabilityZone": "string", "DurationHours": 48, "DurationMinutes": 0, "EndTime": "2024-09-28T04:30:00-07:00", "InstanceType": "ml.p5.48xlarge", "ReservedCapacityArn": "arn:aws:sagemaker:us-east-1:123456789123:reserved-capacity/large-models-fine-tuning-rc1", "StartTime": "2024-09-26T04:30:00-07:00", "Status": "Scheduled", "TotalInstanceCount": 4 } ], "StartTime": "2024-09-26T04:30:00-07:00", "Status": "Scheduled", "StatusMessage": "Payment confirmed, training plan scheduled." "TargetResources": [ "training-job" ], "TotalInstanceCount": 4, "TrainingPlanArn": "arn:aws:sagemaker:us-east-1:123456789123:training-plan/large-models-fine-tuning", "TrainingPlanName": "large-models-fine-tuning", "UpfrontFee": "xxxx.xx" }

The following sections define the mandatory input request parameter for the DescribeTrainingPlan API operation.

Required parameters

  • TrainingPlanName: The name of the training plan you want to describe.