class Aws::SageMaker::Types::StoppingCondition
Specifies a limit to how long a model training job, model compilation job, or hyperparameter tuning job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, Amazon SageMaker
ends the training or compilation job. Use this API to cap model training costs.
To stop a training job, Amazon SageMaker
sends the algorithm the `SIGTERM` signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.
The training algorithms provided by Amazon SageMaker
automatically save the intermediate results of a model training job when possible. This attempt to save artifacts is only a best effort case as model might not be in a state from which it can be saved. For example, if training has just started, the model might not be ready to save. When saved, this intermediate data is a valid model artifact. You can use it to create a model with `CreateModel`.
<note markdown=“1”> The Neural Topic Model (NTM) currently does not support saving intermediate model artifacts. When training NTMs, make sure that the maximum runtime is sufficient for the training job to complete.
</note>
@note When making an API call, you may pass StoppingCondition
data as a hash: { max_runtime_in_seconds: 1, max_wait_time_in_seconds: 1, }
@!attribute [rw] max_runtime_in_seconds
The maximum length of time, in seconds, that a training or compilation job can run. For compilation jobs, if the job does not complete during this time, you will receive a `TimeOut` error. We recommend starting with 900 seconds and increase as necessary based on your model. For all other jobs, if the job does not complete during this time, Amazon SageMaker ends the job. When `RetryStrategy` is specified in the job request, `MaxRuntimeInSeconds` specifies the maximum time for all of the attempts in total, not each individual attempt. The default value is 1 day. The maximum value is 28 days. @return [Integer]
@!attribute [rw] max_wait_time_in_seconds
The maximum length of time, in seconds, that a managed Spot training job has to complete. It is the amount of time spent waiting for Spot capacity plus the amount of time the job can run. It must be equal to or greater than `MaxRuntimeInSeconds`. If the job does not complete during this time, Amazon SageMaker ends the job. When `RetryStrategy` is specified in the job request, `MaxWaitTimeInSeconds` specifies the maximum time for all of the attempts in total, not each individual attempt. @return [Integer]
@see docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/StoppingCondition AWS API Documentation
Constants
- SENSITIVE