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api_op_CreateTransformJob.go
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api_op_CreateTransformJob.go
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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/service/sagemaker/types"
"github.com/aws/smithy-go/middleware"
smithyhttp "github.com/aws/smithy-go/transport/http"
)
// Starts a transform job. A transform job uses a trained model to get inferences
// on a dataset and saves these results to an Amazon S3 location that you specify.
//
// To perform batch transformations, you create a transform job and use the data
// that you have readily available.
//
// In the request body, you provide the following:
//
// - TransformJobName - Identifies the transform job. The name must be unique
// within an Amazon Web Services Region in an Amazon Web Services account.
//
// - ModelName - Identifies the model to use. ModelName must be the name of an
// existing Amazon SageMaker model in the same Amazon Web Services Region and
// Amazon Web Services account. For information on creating a model, see [CreateModel].
//
// - TransformInput - Describes the dataset to be transformed and the Amazon S3
// location where it is stored.
//
// - TransformOutput - Identifies the Amazon S3 location where you want Amazon
// SageMaker to save the results from the transform job.
//
// - TransformResources - Identifies the ML compute instances for the transform
// job.
//
// For more information about how batch transformation works, see [Batch Transform].
//
// [CreateModel]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateModel.html
// [Batch Transform]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform.html
func (c *Client) CreateTransformJob(ctx context.Context, params *CreateTransformJobInput, optFns ...func(*Options)) (*CreateTransformJobOutput, error) {
if params == nil {
params = &CreateTransformJobInput{}
}
result, metadata, err := c.invokeOperation(ctx, "CreateTransformJob", params, optFns, c.addOperationCreateTransformJobMiddlewares)
if err != nil {
return nil, err
}
out := result.(*CreateTransformJobOutput)
out.ResultMetadata = metadata
return out, nil
}
type CreateTransformJobInput struct {
// The name of the model that you want to use for the transform job. ModelName
// must be the name of an existing Amazon SageMaker model within an Amazon Web
// Services Region in an Amazon Web Services account.
//
// This member is required.
ModelName *string
// Describes the input source and the way the transform job consumes it.
//
// This member is required.
TransformInput *types.TransformInput
// The name of the transform job. The name must be unique within an Amazon Web
// Services Region in an Amazon Web Services account.
//
// This member is required.
TransformJobName *string
// Describes the results of the transform job.
//
// This member is required.
TransformOutput *types.TransformOutput
// Describes the resources, including ML instance types and ML instance count, to
// use for the transform job.
//
// This member is required.
TransformResources *types.TransformResources
// Specifies the number of records to include in a mini-batch for an HTTP
// inference request. A record is a single unit of input data that inference can be
// made on. For example, a single line in a CSV file is a record.
//
// To enable the batch strategy, you must set the SplitType property to Line ,
// RecordIO , or TFRecord .
//
// To use only one record when making an HTTP invocation request to a container,
// set BatchStrategy to SingleRecord and SplitType to Line .
//
// To fit as many records in a mini-batch as can fit within the MaxPayloadInMB
// limit, set BatchStrategy to MultiRecord and SplitType to Line .
BatchStrategy types.BatchStrategy
// Configuration to control how SageMaker captures inference data.
DataCaptureConfig *types.BatchDataCaptureConfig
// The data structure used to specify the data to be used for inference in a batch
// transform job and to associate the data that is relevant to the prediction
// results in the output. The input filter provided allows you to exclude input
// data that is not needed for inference in a batch transform job. The output
// filter provided allows you to include input data relevant to interpreting the
// predictions in the output from the job. For more information, see [Associate Prediction Results with their Corresponding Input Records].
//
// [Associate Prediction Results with their Corresponding Input Records]: https://docs.aws.amazon.com/sagemaker/latest/dg/batch-transform-data-processing.html
DataProcessing *types.DataProcessing
// The environment variables to set in the Docker container. We support up to 16
// key and values entries in the map.
Environment map[string]string
// Associates a SageMaker job as a trial component with an experiment and trial.
// Specified when you call the following APIs:
//
// [CreateProcessingJob]
//
// [CreateTrainingJob]
//
// [CreateTransformJob]
//
// [CreateTransformJob]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTransformJob.html
// [CreateTrainingJob]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateTrainingJob.html
// [CreateProcessingJob]: https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateProcessingJob.html
ExperimentConfig *types.ExperimentConfig
// The maximum number of parallel requests that can be sent to each instance in a
// transform job. If MaxConcurrentTransforms is set to 0 or left unset, Amazon
// SageMaker checks the optional execution-parameters to determine the settings for
// your chosen algorithm. If the execution-parameters endpoint is not enabled, the
// default value is 1 . For more information on execution-parameters, see [How Containers Serve Requests]. For
// built-in algorithms, you don't need to set a value for MaxConcurrentTransforms .
//
// [How Containers Serve Requests]: https://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms-batch-code.html#your-algorithms-batch-code-how-containe-serves-requests
MaxConcurrentTransforms *int32
// The maximum allowed size of the payload, in MB. A payload is the data portion
// of a record (without metadata). The value in MaxPayloadInMB must be greater
// than, or equal to, the size of a single record. To estimate the size of a record
// in MB, divide the size of your dataset by the number of records. To ensure that
// the records fit within the maximum payload size, we recommend using a slightly
// larger value. The default value is 6 MB.
//
// The value of MaxPayloadInMB cannot be greater than 100 MB. If you specify the
// MaxConcurrentTransforms parameter, the value of (MaxConcurrentTransforms *
// MaxPayloadInMB) also cannot exceed 100 MB.
//
// For cases where the payload might be arbitrarily large and is transmitted using
// HTTP chunked encoding, set the value to 0 . This feature works only in supported
// algorithms. Currently, Amazon SageMaker built-in algorithms do not support HTTP
// chunked encoding.
MaxPayloadInMB *int32
// Configures the timeout and maximum number of retries for processing a transform
// job invocation.
ModelClientConfig *types.ModelClientConfig
// (Optional) An array of key-value pairs. For more information, see [Using Cost Allocation Tags] in the
// Amazon Web Services Billing and Cost Management User Guide.
//
// [Using Cost Allocation Tags]: https://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what
Tags []types.Tag
noSmithyDocumentSerde
}
type CreateTransformJobOutput struct {
// The Amazon Resource Name (ARN) of the transform job.
//
// This member is required.
TransformJobArn *string
// Metadata pertaining to the operation's result.
ResultMetadata middleware.Metadata
noSmithyDocumentSerde
}
func (c *Client) addOperationCreateTransformJobMiddlewares(stack *middleware.Stack, options Options) (err error) {
if err := stack.Serialize.Add(&setOperationInputMiddleware{}, middleware.After); err != nil {
return err
}
err = stack.Serialize.Add(&awsAwsjson11_serializeOpCreateTransformJob{}, middleware.After)
if err != nil {
return err
}
err = stack.Deserialize.Add(&awsAwsjson11_deserializeOpCreateTransformJob{}, middleware.After)
if err != nil {
return err
}
if err := addProtocolFinalizerMiddlewares(stack, options, "CreateTransformJob"); 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 = addClientRequestID(stack); err != nil {
return err
}
if err = addComputeContentLength(stack); err != nil {
return err
}
if err = addResolveEndpointMiddleware(stack, options); err != nil {
return err
}
if err = addComputePayloadSHA256(stack); err != nil {
return err
}
if err = addRetry(stack, options); err != nil {
return err
}
if err = addRawResponseToMetadata(stack); err != nil {
return err
}
if err = 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 = addOpCreateTransformJobValidationMiddleware(stack); err != nil {
return err
}
if err = stack.Initialize.Add(newServiceMetadataMiddleware_opCreateTransformJob(options.Region), middleware.Before); err != nil {
return err
}
if err = 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_opCreateTransformJob(region string) *awsmiddleware.RegisterServiceMetadata {
return &awsmiddleware.RegisterServiceMetadata{
Region: region,
ServiceID: ServiceID,
OperationName: "CreateTransformJob",
}
}