fn stop_hyper_parameter_tuning_job(
        &self,
        input: StopHyperParameterTuningJobRequest,
    ) -> RusotoFuture<(), StopHyperParameterTuningJobError> {
        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.StopHyperParameterTuningJob");
        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(StopHyperParameterTuningJobError::from_response(response))
                }))
            }
        })
    }
/// <p>Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.</p> <p>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 <code>Stopped</code> state, it releases all reserved resources for the tuning job.</p>
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.
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 .
fn stop_hyper_parameter_tuning_job(
        &self,
        input: StopHyperParameterTuningJobRequest,
    ) -> RusotoFuture<(), StopHyperParameterTuningJobError> {
        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.StopHyperParameterTuningJob");
        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(StopHyperParameterTuningJobError::from_response(response))
                }))
            }
        })
    }
fn stop_hyper_parameter_tuning_job ( & self , input : StopHyperParameterTuningJobRequest , ) -> RusotoFuture < ( ) , StopHyperParameterTuningJobError > { 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 ( StopHyperParameterTuningJobError :: from_response ( response ) ) } ) ) } } ) }
<p>Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched.</p> <p>All model artifacts output from the training jobs are stored in Amazon Simple Storage Service (Amazon S3).
<p > Stops a running hyperparameter tuning job and all running training jobs that the tuning job launched . < / p > <p > All model artifacts output from the training jobs are stored in Amazon Simple Storage Service ( Amazon S3 ) .
&self
input
StopHyperParameterTuningJobRequest
&self
input
StopHyperParameterTuningJobRequest