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// Code generated by smithy-go-codegen DO NOT EDIT.
package sagemaker
import (
"context"
"fmt"
awsmiddleware "github.com/aws/aws-sdk-go-v2/aws/middleware"
"github.com/aws/aws-sdk-go-v2/aws/signer/v4"
"github.com/aws/aws-sdk-go-v2/service/sagemaker/types"
"github.com/aws/smithy-go/middleware"
smithyhttp "github.com/aws/smithy-go/transport/http"
)
// Creates a model in SageMaker. In the request, you name the model and describe a
// primary container. For the primary container, you specify the Docker image that
// contains inference code, artifacts (from prior training), and a custom
// environment map that the inference code uses when you deploy the model for
// predictions. Use this API to create a model if you want to use SageMaker hosting
// services or run a batch transform job. To host your model, you create an
// endpoint configuration with the CreateEndpointConfig API, and then create an
// endpoint with the CreateEndpoint API. SageMaker then deploys all of the
// containers that you defined for the model in the hosting environment. For an
// example that calls this method when deploying a model to SageMaker hosting
// services, see Create a Model (Amazon Web Services SDK for Python (Boto 3)). (https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints-deployment.html#realtime-endpoints-deployment-create-model)
// To run a batch transform using your model, you start a job with the
// CreateTransformJob API. SageMaker uses your model and your dataset to get
// inferences which are then saved to a specified S3 location. In the request, you
// also provide an IAM role that SageMaker can assume to access model artifacts and
// docker image for deployment on ML compute hosting instances or for batch
// transform jobs. In addition, you also use the IAM role to manage permissions the
// inference code needs. For example, if the inference code access any other Amazon
// Web Services resources, you grant necessary permissions via this role.
func (c *Client) CreateModel(ctx context.Context, params *CreateModelInput, optFns ...func(*Options)) (*CreateModelOutput, error) {
if params == nil {
params = &CreateModelInput{}
}
result, metadata, err := c.invokeOperation(ctx, "CreateModel", params, optFns, c.addOperationCreateModelMiddlewares)
if err != nil {
return nil, err
}
out := result.(*CreateModelOutput)
out.ResultMetadata = metadata
return out, nil
}
type CreateModelInput struct {
// The name of the new model.
//
// This member is required.
ModelName *string
// Specifies the containers in the inference pipeline.
Containers []types.ContainerDefinition
// Isolates the model container. No inbound or outbound network calls can be made
// to or from the model container.
EnableNetworkIsolation *bool
// The Amazon Resource Name (ARN) of the IAM role that SageMaker can assume to
// access model artifacts and docker image for deployment on ML compute instances
// or for batch transform jobs. Deploying on ML compute instances is part of model
// hosting. For more information, see SageMaker Roles (https://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html)
// . To be able to pass this role to SageMaker, the caller of this API must have
// the iam:PassRole permission.
ExecutionRoleArn *string
// Specifies details of how containers in a multi-container endpoint are called.
InferenceExecutionConfig *types.InferenceExecutionConfig
// The location of the primary docker image containing inference code, associated
// artifacts, and custom environment map that the inference code uses when the
// model is deployed for predictions.
PrimaryContainer *types.ContainerDefinition
// An array of key-value pairs. You can use tags to categorize your Amazon Web
// Services resources in different ways, for example, by purpose, owner, or
// environment. For more information, see Tagging Amazon Web Services Resources (https://docs.aws.amazon.com/general/latest/gr/aws_tagging.html)
// .
Tags []types.Tag
// A VpcConfig (https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_VpcConfig.html)
// object that specifies the VPC that you want your model to connect to. Control
// access to and from your model container by configuring the VPC. VpcConfig is
// used in hosting services and in batch transform. For more information, see
// Protect Endpoints by Using an Amazon Virtual Private Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/host-vpc.html)
// and Protect Data in Batch Transform Jobs by Using an Amazon Virtual Private
// Cloud (https://docs.aws.amazon.com/sagemaker/latest/dg/batch-vpc.html) .
VpcConfig *types.VpcConfig
noSmithyDocumentSerde
}
type CreateModelOutput struct {
// The ARN of the model created in SageMaker.
//
// This member is required.
ModelArn *string
// Metadata pertaining to the operation's result.
ResultMetadata middleware.Metadata
noSmithyDocumentSerde
}
func (c *Client) addOperationCreateModelMiddlewares(stack *middleware.Stack, options Options) (err error) {
if err := stack.Serialize.Add(&setOperationInputMiddleware{}, middleware.After); err != nil {
return err
}
err = stack.Serialize.Add(&awsAwsjson11_serializeOpCreateModel{}, middleware.After)
if err != nil {
return err
}
err = stack.Deserialize.Add(&awsAwsjson11_deserializeOpCreateModel{}, middleware.After)
if err != nil {
return err
}
if err := addProtocolFinalizerMiddlewares(stack, options, "CreateModel"); err != nil {
return fmt.Errorf("add protocol finalizers: %v", err)
}
if err = addlegacyEndpointContextSetter(stack, options); err != nil {
return err
}
if err = addSetLoggerMiddleware(stack, options); err != nil {
return err
}
if err = awsmiddleware.AddClientRequestIDMiddleware(stack); err != nil {
return err
}
if err = smithyhttp.AddComputeContentLengthMiddleware(stack); err != nil {
return err
}
if err = addResolveEndpointMiddleware(stack, options); err != nil {
return err
}
if err = v4.AddComputePayloadSHA256Middleware(stack); err != nil {
return err
}
if err = addRetryMiddlewares(stack, options); err != nil {
return err
}
if err = awsmiddleware.AddRawResponseToMetadata(stack); err != nil {
return err
}
if err = awsmiddleware.AddRecordResponseTiming(stack); err != nil {
return err
}
if err = addClientUserAgent(stack, options); err != nil {
return err
}
if err = smithyhttp.AddErrorCloseResponseBodyMiddleware(stack); err != nil {
return err
}
if err = smithyhttp.AddCloseResponseBodyMiddleware(stack); err != nil {
return err
}
if err = addSetLegacyContextSigningOptionsMiddleware(stack); err != nil {
return err
}
if err = addOpCreateModelValidationMiddleware(stack); err != nil {
return err
}
if err = stack.Initialize.Add(newServiceMetadataMiddleware_opCreateModel(options.Region), middleware.Before); err != nil {
return err
}
if err = awsmiddleware.AddRecursionDetection(stack); err != nil {
return err
}
if err = addRequestIDRetrieverMiddleware(stack); err != nil {
return err
}
if err = addResponseErrorMiddleware(stack); err != nil {
return err
}
if err = addRequestResponseLogging(stack, options); err != nil {
return err
}
if err = addDisableHTTPSMiddleware(stack, options); err != nil {
return err
}
return nil
}
func newServiceMetadataMiddleware_opCreateModel(region string) *awsmiddleware.RegisterServiceMetadata {
return &awsmiddleware.RegisterServiceMetadata{
Region: region,
ServiceID: ServiceID,
OperationName: "CreateModel",
}
}
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