[ aws . sagemaker ]

search-training-plan-offerings

Description

Searches for available training plan offerings based on specified criteria.

  • Users search for available plan offerings based on their requirements (e.g., instance type, count, start time, duration).
  • And then, they create a plan that best matches their needs using the ID of the plan offering they want to use.

For more information about how to reserve GPU capacity for your SageMaker training jobs or SageMaker HyperPod clusters using Amazon SageMaker Training Plan , see `` CreateTrainingPlan `` .

See also: AWS API Documentation

Synopsis

  search-training-plan-offerings
--instance-type <value>
--instance-count <value>
[--start-time-after <value>]
[--end-time-before <value>]
[--duration-hours <value>]
--target-resources <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--instance-type (string)

The type of instance you want to search for in the available training plan offerings. This field allows you to filter the search results based on the specific compute resources you require for your SageMaker training jobs or SageMaker HyperPod clusters. When searching for training plan offerings, specifying the instance type helps you find Reserved Instances that match your computational needs.

Possible values:

  • ml.p4d.24xlarge
  • ml.p5.48xlarge
  • ml.p5e.48xlarge
  • ml.p5en.48xlarge
  • ml.trn2.48xlarge

--instance-count (integer)

The number of instances you want to reserve in the training plan offerings. This allows you to specify the quantity of compute resources needed for your SageMaker training jobs or SageMaker HyperPod clusters, helping you find reserved capacity offerings that match your requirements.

--start-time-after (timestamp)

A filter to search for training plan offerings with a start time after a specified date.

--end-time-before (timestamp)

A filter to search for reserved capacity offerings with an end time before a specified date.

--duration-hours (long)

The desired duration in hours for the training plan offerings.

--target-resources (list)

The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) to search for in the offerings.

Training plans are specific to their target resource.

  • A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
  • A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster’s instance group.

(string)

Syntax:

"string" "string" ...

Where valid values are:
  training-job
  hyperpod-cluster

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

  • json
  • text
  • table
  • yaml
  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on
  • off
  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64
  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Output

TrainingPlanOfferings -> (list)

A list of training plan offerings that match the search criteria.

(structure)

Details about a training plan offering.

For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see `` CreateTrainingPlan `` .

TrainingPlanOfferingId -> (string)

The unique identifier for this training plan offering.

TargetResources -> (list)

The target resources (e.g., SageMaker Training Jobs, SageMaker HyperPod) for this training plan offering.

Training plans are specific to their target resource.

  • A training plan designed for SageMaker training jobs can only be used to schedule and run training jobs.
  • A training plan for HyperPod clusters can be used exclusively to provide compute resources to a cluster’s instance group.

(string)

RequestedStartTimeAfter -> (timestamp)

The requested start time that the user specified when searching for the training plan offering.

RequestedEndTimeBefore -> (timestamp)

The requested end time that the user specified when searching for the training plan offering.

DurationHours -> (long)

The number of whole hours in the total duration for this training plan offering.

DurationMinutes -> (long)

The additional minutes beyond whole hours in the total duration for this training plan offering.

UpfrontFee -> (string)

The upfront fee for this training plan offering.

CurrencyCode -> (string)

The currency code for the upfront fee (e.g., USD).

ReservedCapacityOfferings -> (list)

A list of reserved capacity offerings associated with this training plan offering.

(structure)

Details about a reserved capacity offering for a training plan offering.

For more information about how to reserve GPU capacity for your SageMaker HyperPod clusters using Amazon SageMaker Training Plan, see `` CreateTrainingPlan `` .

InstanceType -> (string)

The instance type for the reserved capacity offering.

InstanceCount -> (integer)

The number of instances in the reserved capacity offering.

AvailabilityZone -> (string)

The availability zone for the reserved capacity offering.

DurationHours -> (long)

The number of whole hours in the total duration for this reserved capacity offering.

DurationMinutes -> (long)

The additional minutes beyond whole hours in the total duration for this reserved capacity offering.

StartTime -> (timestamp)

The start time of the reserved capacity offering.

EndTime -> (timestamp)

The end time of the reserved capacity offering.