fn create_endpoint(
        &self,
        input: CreateEndpointInput,
    ) -> RusotoFuture<CreateEndpointOutput, CreateEndpointError> {
        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.CreateEndpoint");
        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(response.buffer().from_err().map(|response| {
                    let mut body = response.body;

                    if body.is_empty() || body == b"null" {
                        body = b"{}".to_vec();
                    }

                    serde_json::from_str::<CreateEndpointOutput>(
                        String::from_utf8_lossy(body.as_ref()).as_ref(),
                    )
                    .unwrap()
                }))
            } else {
                Box::new(
                    response
                        .buffer()
                        .from_err()
                        .and_then(|response| Err(CreateEndpointError::from_response(response))),
                )
            }
        })
    }
/// <p>Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the <a href="http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpointConfig.html">CreateEndpointConfig</a> API. </p> <note> <p> Use this API only for hosting models using Amazon SageMaker hosting services. </p> </note> <p>The endpoint name must be unique within an AWS Region in your AWS account. </p> <p>When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them. </p> <p>When Amazon SageMaker receives the request, it sets the endpoint status to <code>Creating</code>. After it creates the endpoint, it sets the status to <code>InService</code>. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the <a href="http://docs.aws.amazon.com/sagemaker/latest/dg/API_DescribeEndpoint.html">DescribeEndpoint</a> API.</p> <p>For an example, see <a href="http://docs.aws.amazon.com/sagemaker/latest/dg/ex1.html">Exercise 1: Using the K-Means Algorithm Provided by Amazon SageMaker</a>. </p> <p>If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see <a href="http://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html">Activating and Deactivating AWS STS i an AWS Region</a> in the <i>AWS Identity and Access Management User Guide</i>.</p>
Creates an endpoint using the endpoint configuration specified in the request. Amazon SageMaker uses the endpoint to provision resources and deploy models. You create the endpoint configuration with the CreateEndpointConfig API.    Use this API only for hosting models using Amazon SageMaker hosting services.   The endpoint name must be unique within an AWS Region in your AWS account.  When it receives the request, Amazon SageMaker creates the endpoint, launches the resources (ML compute instances), and deploys the model(s) on them.  When Amazon SageMaker receives the request, it sets the endpoint status to Creating. After it creates the endpoint, it sets the status to InService. Amazon SageMaker can then process incoming requests for inferences. To check the status of an endpoint, use the DescribeEndpoint API. For an example, see Exercise 1: Using the K-Means Algorithm Provided by Amazon SageMaker.  If any of the models hosted at this endpoint get model data from an Amazon S3 location, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS i an AWS Region in the AWS Identity and Access Management User Guide.
Creates an endpoint using the endpoint configuration specified in the request . Amazon SageMaker uses the endpoint to provision resources and deploy models . You create the endpoint configuration with the CreateEndpointConfig API . Use this API only for hosting models using Amazon SageMaker hosting services . The endpoint name must be unique within an AWS Region in your AWS account . When it receives the request Amazon SageMaker creates the endpoint launches the resources ( ML compute instances ) and deploys the model ( s ) on them . When Amazon SageMaker receives the request it sets the endpoint status to Creating . After it creates the endpoint it sets the status to InService . Amazon SageMaker can then process incoming requests for inferences . To check the status of an endpoint use the DescribeEndpoint API . For an example see Exercise 1 : Using the K - Means Algorithm Provided by Amazon SageMaker . If any of the models hosted at this endpoint get model data from an Amazon S3 location Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provided . AWS STS is activated in your IAM user account by default . If you previously deactivated AWS STS for a region you need to reactivate AWS STS for that region . For more information see Activating and Deactivating AWS STS i an AWS Region in the AWS Identity and Access Management User Guide .
fn create_endpoint(
        &self,
        input: CreateEndpointInput,
    ) -> RusotoFuture<CreateEndpointOutput, CreateEndpointError> {
        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.CreateEndpoint");
        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(response.buffer().from_err().map(|response| {
                    let mut body = response.body;
                    if body.is_empty() || body == b"null" {
                        body = b"{}".to_vec();
                    }
                    serde_json::from_str::<CreateEndpointOutput>(
                        String::from_utf8_lossy(body.as_ref()).as_ref(),
                    )
                    .unwrap()
                }))
            } else {
                Box::new(
                    response
                        .buffer()
                        .from_err()
                        .and_then(|response| Err(CreateEndpointError::from_response(response))),
                )
            }
        })
    }
fn create_endpoint ( & self , input : CreateEndpointInput , ) -> RusotoFuture < CreateEndpointOutput , CreateEndpointError > { 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 ( response . buffer ( ) . from_err ( ) . map ( | response | { let mut body = response . body ; if body . is_empty ( ) || body == b" " { body = b" " . to_vec ( ) ; } serde_json :: from_str :: < CreateEndpointOutput > ( String :: from_utf8_lossy ( body . as_ref ( ) ) . as_ref ( ) , ) . unwrap ( ) } ) ) } else { Box :: new ( response . buffer ( ) . from_err ( ) . and_then ( | response | Err ( CreateEndpointError :: from_response ( response ) ) ) , ) } } ) }
<p>Creates an endpoint using the endpoint configuration specified in the request.
<p > Creates an endpoint using the endpoint configuration specified in the request .
&self
input
CreateEndpointInput
&self
input
CreateEndpointInput