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stop_training_job(**kwargs)¶Stops a training job. To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination for 120 seconds. Algorithms might use this 120-second window to save the model artifacts, so the results of the training is not lost.
When it receives a StopTrainingJob request, SageMaker changes the status of the job to Stopping . After SageMaker stops the job, it sets the status to Stopped .
See also: AWS API Documentation
Request Syntax
response = client.stop_training_job(
TrainingJobName='string'
)
[REQUIRED]
The name of the training job to stop.
Exceptions
SageMaker.Client.exceptions.ResourceNotFound