fn stop_training_job(
        &self,
        input: StopTrainingJobRequest,
    ) -> RusotoFuture<(), StopTrainingJobError> {
        let mut request = SignedRequest::new("POST", "sagemaker", &self.region, "/");

        request.set_content_type("application/x-amz-json-1.1".to_owned());
        request.add_header("x-amz-target", "SageMaker.StopTrainingJob");
        let encoded = serde_json::to_string(&input).unwrap();
        request.set_payload(Some(encoded.into_bytes()));

        self.client.sign_and_dispatch(request, |response| {
            if response.status.is_success() {
                Box::new(future::ok(::std::mem::drop(response)))
            } else {
                Box::new(
                    response
                        .buffer()
                        .from_err()
                        .and_then(|response| Err(StopTrainingJobError::from_response(response))),
                )
            }
        })
    }
/// <p>Stops a training job. To stop a job, Amazon SageMaker sends the algorithm the <code>SIGTERM</code> 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. </p> <p>Training algorithms provided by Amazon SageMaker save the intermediate results of a model training job. This intermediate data is a valid model artifact. You can use the model artifacts that are saved when Amazon SageMaker stops a training job to create a model. </p> <p>When it receives a <code>StopTrainingJob</code> request, Amazon SageMaker changes the status of the job to <code>Stopping</code>. After Amazon SageMaker stops the job, it sets the status to <code>Stopped</code>.</p>
Stops a training job. To stop a job, Amazon 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.  Training algorithms provided by Amazon SageMaker save the intermediate results of a model training job. This intermediate data is a valid model artifact. You can use the model artifacts that are saved when Amazon SageMaker stops a training job to create a model.  When it receives a StopTrainingJob request, Amazon SageMaker changes the status of the job to Stopping. After Amazon SageMaker stops the job, it sets the status to Stopped.
Stops a training job . To stop a job Amazon 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 . Training algorithms provided by Amazon SageMaker save the intermediate results of a model training job . This intermediate data is a valid model artifact . You can use the model artifacts that are saved when Amazon SageMaker stops a training job to create a model . When it receives a StopTrainingJob request Amazon SageMaker changes the status of the job to Stopping . After Amazon SageMaker stops the job it sets the status to Stopped .
fn stop_training_job(
        &self,
        input: StopTrainingJobRequest,
    ) -> RusotoFuture<(), StopTrainingJobError> {
        let mut request = SignedRequest::new("POST", "sagemaker", &self.region, "/");
        request.set_content_type("application/x-amz-json-1.1".to_owned());
        request.add_header("x-amz-target", "SageMaker.StopTrainingJob");
        let encoded = serde_json::to_string(&input).unwrap();
        request.set_payload(Some(encoded.into_bytes()));
        self.client.sign_and_dispatch(request, |response| {
            if response.status.is_success() {
                Box::new(future::ok(::std::mem::drop(response)))
            } else {
                Box::new(
                    response
                        .buffer()
                        .from_err()
                        .and_then(|response| Err(StopTrainingJobError::from_response(response))),
                )
            }
        })
    }
fn stop_training_job ( & self , input : StopTrainingJobRequest , ) -> RusotoFuture < ( ) , StopTrainingJobError > { let mut request = SignedRequest :: new ( " " , " " , & self . region , " " ) ; request . set_content_type ( " " . to_owned ( ) ) ; request . add_header ( " " , " " ) ; let encoded = serde_json :: to_string ( & input ) . unwrap ( ) ; request . set_payload ( Some ( encoded . into_bytes ( ) ) ) ; self . client . sign_and_dispatch ( request , | response | { if response . status . is_success ( ) { Box :: new ( future :: ok ( :: std :: mem :: drop ( response ) ) ) } else { Box :: new ( response . buffer ( ) . from_err ( ) . and_then ( | response | Err ( StopTrainingJobError :: from_response ( response ) ) ) , ) } } ) }
<p>Stops a training job.
<p > Stops a training job .
&self
input
StopTrainingJobRequest
&self
input
StopTrainingJobRequest