fn create_endpoint_config(
        &self,
        input: CreateEndpointConfigInput,
    ) -> RusotoFuture<CreateEndpointConfigOutput, CreateEndpointConfigError> {
        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.CreateEndpointConfig");
        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::<CreateEndpointConfigOutput>(
                        String::from_utf8_lossy(body.as_ref()).as_ref(),
                    )
                    .unwrap()
                }))
            } else {
                Box::new(
                    response.buffer().from_err().and_then(|response| {
                        Err(CreateEndpointConfigError::from_response(response))
                    }),
                )
            }
        })
    }
/// <p>Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the <code>CreateModel</code> API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the <a href="http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html">CreateEndpoint</a> API.</p> <note> <p> Use this API only if you want to use Amazon SageMaker hosting services to deploy models into production. </p> </note> <p>In the request, you define one or more <code>ProductionVariant</code>s, each of which identifies a model. Each <code>ProductionVariant</code> parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy. </p> <p>If you are hosting multiple models, you also assign a <code>VariantWeight</code> to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B. </p>
Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models. In the configuration, you identify one or more models, created using the CreateModel API, to deploy and the resources that you want Amazon SageMaker to provision. Then you call the CreateEndpoint API.   Use this API only if you want to use Amazon SageMaker hosting services to deploy models into production.   In the request, you define one or more ProductionVariants, each of which identifies a model. Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision. This includes the number and type of ML compute instances to deploy.  If you are hosting multiple models, you also assign a VariantWeight to specify how much traffic you want to allocate to each model. For example, suppose that you want to host two models, A and B, and you assign traffic weight 2 for model A and 1 for model B. Amazon SageMaker distributes two-thirds of the traffic to Model A, and one-third to model B.
Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models . In the configuration you identify one or more models created using the CreateModel API to deploy and the resources that you want Amazon SageMaker to provision . Then you call the CreateEndpoint API . Use this API only if you want to use Amazon SageMaker hosting services to deploy models into production . In the request you define one or more ProductionVariants each of which identifies a model . Each ProductionVariant parameter also describes the resources that you want Amazon SageMaker to provision . This includes the number and type of ML compute instances to deploy . If you are hosting multiple models you also assign a VariantWeight to specify how much traffic you want to allocate to each model . For example suppose that you want to host two models A and B and you assign traffic weight 2 for model A and 1 for model B . Amazon SageMaker distributes two - thirds of the traffic to Model A and one - third to model B .
fn create_endpoint_config(
        &self,
        input: CreateEndpointConfigInput,
    ) -> RusotoFuture<CreateEndpointConfigOutput, CreateEndpointConfigError> {
        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.CreateEndpointConfig");
        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::<CreateEndpointConfigOutput>(
                        String::from_utf8_lossy(body.as_ref()).as_ref(),
                    )
                    .unwrap()
                }))
            } else {
                Box::new(
                    response.buffer().from_err().and_then(|response| {
                        Err(CreateEndpointConfigError::from_response(response))
                    }),
                )
            }
        })
    }
fn create_endpoint_config ( & self , input : CreateEndpointConfigInput , ) -> RusotoFuture < CreateEndpointConfigOutput , CreateEndpointConfigError > { 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 :: < CreateEndpointConfigOutput > ( String :: from_utf8_lossy ( body . as_ref ( ) ) . as_ref ( ) , ) . unwrap ( ) } ) ) } else { Box :: new ( response . buffer ( ) . from_err ( ) . and_then ( | response | { Err ( CreateEndpointConfigError :: from_response ( response ) ) } ) , ) } } ) }
<p>Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models.
<p > Creates an endpoint configuration that Amazon SageMaker hosting services uses to deploy models .
&self
input
CreateEndpointConfigInput
&self
input
CreateEndpointConfigInput