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[ aws . sagemaker ]

stop-hyper-parameter-tuning-job

Description

Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.

All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3). All data that the training jobs write to Amazon CloudWatch Logs are still available in CloudWatch. After the tuning job moves to the Stopped state, it releases all reserved resources for the tuning job.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.

Synopsis

  stop-hyper-parameter-tuning-job
--hyper-parameter-tuning-job-name <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]

Options

--hyper-parameter-tuning-job-name (string)

The name of the tuning job to stop.

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI 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.

--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. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.

Output

None