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📄 api.go // Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT. package machinelearning import ( "fmt" "time" "github.com/aws/aws-sdk-go/aws" "github.com/aws/aws-sdk-go/aws/awsutil" "github.com/aws/aws-sdk-go/aws/request" "github.com/aws/aws-sdk-go/private/protocol" ) const opAddTags = "AddTags" // AddTagsRequest generates a "aws/request.Request" representing the // client's request for the AddTags operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See AddTags for more information on using the AddTags // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the AddTagsRequest method. // req, resp := client.AddTagsRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) AddTagsRequest(input AddTagsInput) (req request.Request, output AddTagsOutput) { op := &request.Operation{ Name: opAddTags, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &AddTagsInput{} } output = &AddTagsOutput{} req = c.newRequest(op, input, output) return } // AddTags API operation for Amazon Machine Learning. // // Adds one or more tags to an object, up to a limit of 10. Each tag consists // of a key and an optional value. If you add a tag using a key that is already // associated with the ML object, AddTags updates the tag's value. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation AddTags for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InvalidTagException // // - TagLimitExceededException // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) AddTags(input AddTagsInput) (AddTagsOutput, error) { req, out := c.AddTagsRequest(input) return out, req.Send() } // AddTagsWithContext is the same as AddTags with the addition of // the ability to pass a context and additional request options. // // See AddTags for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) AddTagsWithContext(ctx aws.Context, input AddTagsInput, opts ...request.Option) (AddTagsOutput, error) { req, out := c.AddTagsRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateBatchPrediction = "CreateBatchPrediction" // CreateBatchPredictionRequest generates a "aws/request.Request" representing the // client's request for the CreateBatchPrediction operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateBatchPrediction for more information on using the CreateBatchPrediction // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateBatchPredictionRequest method. // req, resp := client.CreateBatchPredictionRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateBatchPredictionRequest(input CreateBatchPredictionInput) (req request.Request, output CreateBatchPredictionOutput) { op := &request.Operation{ Name: opCreateBatchPrediction, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateBatchPredictionInput{} } output = &CreateBatchPredictionOutput{} req = c.newRequest(op, input, output) return } // CreateBatchPrediction API operation for Amazon Machine Learning. // // Generates predictions for a group of observations. The observations to process // exist in one or more data files referenced by a DataSource. This operation // creates a new BatchPrediction, and uses an MLModel and the data files referenced // by the DataSource as information sources. // // CreateBatchPrediction is an asynchronous operation. In response to CreateBatchPrediction, // Amazon Machine Learning (Amazon ML) immediately returns and sets the BatchPrediction // status to PENDING. After the BatchPrediction completes, Amazon ML sets the // status to COMPLETED. // // You can poll for status updates by using the GetBatchPrediction operation // and checking the Status parameter of the result. After the COMPLETED status // appears, the results are available in the location specified by the OutputUri // parameter. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateBatchPrediction for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - IdempotentParameterMismatchException // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. func (c MachineLearning) CreateBatchPrediction(input CreateBatchPredictionInput) (CreateBatchPredictionOutput, error) { req, out := c.CreateBatchPredictionRequest(input) return out, req.Send() } // CreateBatchPredictionWithContext is the same as CreateBatchPrediction with the addition of // the ability to pass a context and additional request options. // // See CreateBatchPrediction for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateBatchPredictionWithContext(ctx aws.Context, input CreateBatchPredictionInput, opts ...request.Option) (CreateBatchPredictionOutput, error) { req, out := c.CreateBatchPredictionRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateDataSourceFromRDS = "CreateDataSourceFromRDS" // CreateDataSourceFromRDSRequest generates a "aws/request.Request" representing the // client's request for the CreateDataSourceFromRDS operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateDataSourceFromRDS for more information on using the CreateDataSourceFromRDS // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateDataSourceFromRDSRequest method. // req, resp := client.CreateDataSourceFromRDSRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateDataSourceFromRDSRequest(input CreateDataSourceFromRDSInput) (req request.Request, output CreateDataSourceFromRDSOutput) { op := &request.Operation{ Name: opCreateDataSourceFromRDS, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateDataSourceFromRDSInput{} } output = &CreateDataSourceFromRDSOutput{} req = c.newRequest(op, input, output) return } // CreateDataSourceFromRDS API operation for Amazon Machine Learning. // // Creates a DataSource object from an Amazon Relational Database Service (http://aws.amazon.com/rds/) // (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, // CreateEvaluation, or CreateBatchPrediction operations. // // CreateDataSourceFromRDS is an asynchronous operation. In response to CreateDataSourceFromRDS, // Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource // status to PENDING. After the DataSource is created and ready for use, Amazon // ML sets the Status parameter to COMPLETED. DataSource in the COMPLETED or // PENDING state can be used only to perform >CreateMLModel>, CreateEvaluation, // or CreateBatchPrediction operations. // // If Amazon ML cannot accept the input source, it sets the Status parameter // to FAILED and includes an error message in the Message attribute of the GetDataSource // operation response. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateDataSourceFromRDS for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - IdempotentParameterMismatchException // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. func (c MachineLearning) CreateDataSourceFromRDS(input CreateDataSourceFromRDSInput) (CreateDataSourceFromRDSOutput, error) { req, out := c.CreateDataSourceFromRDSRequest(input) return out, req.Send() } // CreateDataSourceFromRDSWithContext is the same as CreateDataSourceFromRDS with the addition of // the ability to pass a context and additional request options. // // See CreateDataSourceFromRDS for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateDataSourceFromRDSWithContext(ctx aws.Context, input CreateDataSourceFromRDSInput, opts ...request.Option) (CreateDataSourceFromRDSOutput, error) { req, out := c.CreateDataSourceFromRDSRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateDataSourceFromRedshift = "CreateDataSourceFromRedshift" // CreateDataSourceFromRedshiftRequest generates a "aws/request.Request" representing the // client's request for the CreateDataSourceFromRedshift operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateDataSourceFromRedshift for more information on using the CreateDataSourceFromRedshift // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateDataSourceFromRedshiftRequest method. // req, resp := client.CreateDataSourceFromRedshiftRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateDataSourceFromRedshiftRequest(input CreateDataSourceFromRedshiftInput) (req request.Request, output CreateDataSourceFromRedshiftOutput) { op := &request.Operation{ Name: opCreateDataSourceFromRedshift, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateDataSourceFromRedshiftInput{} } output = &CreateDataSourceFromRedshiftOutput{} req = c.newRequest(op, input, output) return } // CreateDataSourceFromRedshift API operation for Amazon Machine Learning. // // Creates a DataSource from a database hosted on an Amazon Redshift cluster. // A DataSource references data that can be used to perform either CreateMLModel, // CreateEvaluation, or CreateBatchPrediction operations. // // CreateDataSourceFromRedshift is an asynchronous operation. In response to // CreateDataSourceFromRedshift, Amazon Machine Learning (Amazon ML) immediately // returns and sets the DataSource status to PENDING. After the DataSource is // created and ready for use, Amazon ML sets the Status parameter to COMPLETED. // DataSource in COMPLETED or PENDING states can be used to perform only CreateMLModel, // CreateEvaluation, or CreateBatchPrediction operations. // // If Amazon ML can't accept the input source, it sets the Status parameter // to FAILED and includes an error message in the Message attribute of the GetDataSource // operation response. // // The observations should be contained in the database hosted on an Amazon // Redshift cluster and should be specified by a SelectSqlQuery query. Amazon // ML executes an Unload command in Amazon Redshift to transfer the result set // of the SelectSqlQuery query to S3StagingLocation. // // After the DataSource has been created, it's ready for use in evaluations // and batch predictions. If you plan to use the DataSource to train an MLModel, // the DataSource also requires a recipe. A recipe describes how each input // variable will be used in training an MLModel. Will the variable be included // or excluded from training? Will the variable be manipulated; for example, // will it be combined with another variable or will it be split apart into // word combinations? The recipe provides answers to these questions. // // You can't change an existing datasource, but you can copy and modify the // settings from an existing Amazon Redshift datasource to create a new datasource. // To do so, call GetDataSource for an existing datasource and copy the values // to a CreateDataSource call. Change the settings that you want to change and // make sure that all required fields have the appropriate values. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateDataSourceFromRedshift for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - IdempotentParameterMismatchException // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. func (c MachineLearning) CreateDataSourceFromRedshift(input CreateDataSourceFromRedshiftInput) (CreateDataSourceFromRedshiftOutput, error) { req, out := c.CreateDataSourceFromRedshiftRequest(input) return out, req.Send() } // CreateDataSourceFromRedshiftWithContext is the same as CreateDataSourceFromRedshift with the addition of // the ability to pass a context and additional request options. // // See CreateDataSourceFromRedshift for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateDataSourceFromRedshiftWithContext(ctx aws.Context, input CreateDataSourceFromRedshiftInput, opts ...request.Option) (CreateDataSourceFromRedshiftOutput, error) { req, out := c.CreateDataSourceFromRedshiftRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateDataSourceFromS3 = "CreateDataSourceFromS3" // CreateDataSourceFromS3Request generates a "aws/request.Request" representing the // client's request for the CreateDataSourceFromS3 operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateDataSourceFromS3 for more information on using the CreateDataSourceFromS3 // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateDataSourceFromS3Request method. // req, resp := client.CreateDataSourceFromS3Request(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateDataSourceFromS3Request(input CreateDataSourceFromS3Input) (req request.Request, output CreateDataSourceFromS3Output) { op := &request.Operation{ Name: opCreateDataSourceFromS3, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateDataSourceFromS3Input{} } output = &CreateDataSourceFromS3Output{} req = c.newRequest(op, input, output) return } // CreateDataSourceFromS3 API operation for Amazon Machine Learning. // // Creates a DataSource object. A DataSource references data that can be used // to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations. // // CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3, // Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource // status to PENDING. After the DataSource has been created and is ready for // use, Amazon ML sets the Status parameter to COMPLETED. DataSource in the // COMPLETED or PENDING state can be used to perform only CreateMLModel, CreateEvaluation // or CreateBatchPrediction operations. // // If Amazon ML can't accept the input source, it sets the Status parameter // to FAILED and includes an error message in the Message attribute of the GetDataSource // operation response. // // The observation data used in a DataSource should be ready to use; that is, // it should have a consistent structure, and missing data values should be // kept to a minimum. The observation data must reside in one or more .csv files // in an Amazon Simple Storage Service (Amazon S3) location, along with a schema // that describes the data items by name and type. The same schema must be used // for all of the data files referenced by the DataSource. // // After the DataSource has been created, it's ready to use in evaluations and // batch predictions. If you plan to use the DataSource to train an MLModel, // the DataSource also needs a recipe. A recipe describes how each input variable // will be used in training an MLModel. Will the variable be included or excluded // from training? Will the variable be manipulated; for example, will it be // combined with another variable or will it be split apart into word combinations? // The recipe provides answers to these questions. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateDataSourceFromS3 for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - IdempotentParameterMismatchException // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. func (c MachineLearning) CreateDataSourceFromS3(input CreateDataSourceFromS3Input) (CreateDataSourceFromS3Output, error) { req, out := c.CreateDataSourceFromS3Request(input) return out, req.Send() } // CreateDataSourceFromS3WithContext is the same as CreateDataSourceFromS3 with the addition of // the ability to pass a context and additional request options. // // See CreateDataSourceFromS3 for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateDataSourceFromS3WithContext(ctx aws.Context, input CreateDataSourceFromS3Input, opts ...request.Option) (CreateDataSourceFromS3Output, error) { req, out := c.CreateDataSourceFromS3Request(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateEvaluation = "CreateEvaluation" // CreateEvaluationRequest generates a "aws/request.Request" representing the // client's request for the CreateEvaluation operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateEvaluation for more information on using the CreateEvaluation // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateEvaluationRequest method. // req, resp := client.CreateEvaluationRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateEvaluationRequest(input CreateEvaluationInput) (req request.Request, output CreateEvaluationOutput) { op := &request.Operation{ Name: opCreateEvaluation, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateEvaluationInput{} } output = &CreateEvaluationOutput{} req = c.newRequest(op, input, output) return } // CreateEvaluation API operation for Amazon Machine Learning. // // Creates a new Evaluation of an MLModel. An MLModel is evaluated on a set // of observations associated to a DataSource. Like a DataSource for an MLModel, // the DataSource for an Evaluation contains values for the Target Variable. // The Evaluation compares the predicted result for each observation to the // actual outcome and provides a summary so that you know how effective the // MLModel functions on the test data. Evaluation generates a relevant performance // metric, such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on // the corresponding MLModelType: BINARY, REGRESSION or MULTICLASS. // // CreateEvaluation is an asynchronous operation. In response to CreateEvaluation, // Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation // status to PENDING. After the Evaluation is created and ready for use, Amazon // ML sets the status to COMPLETED. // // You can use the GetEvaluation operation to check progress of the evaluation // during the creation operation. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateEvaluation for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - IdempotentParameterMismatchException // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. func (c MachineLearning) CreateEvaluation(input CreateEvaluationInput) (CreateEvaluationOutput, error) { req, out := c.CreateEvaluationRequest(input) return out, req.Send() } // CreateEvaluationWithContext is the same as CreateEvaluation with the addition of // the ability to pass a context and additional request options. // // See CreateEvaluation for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateEvaluationWithContext(ctx aws.Context, input CreateEvaluationInput, opts ...request.Option) (CreateEvaluationOutput, error) { req, out := c.CreateEvaluationRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateMLModel = "CreateMLModel" // CreateMLModelRequest generates a "aws/request.Request" representing the // client's request for the CreateMLModel operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateMLModel for more information on using the CreateMLModel // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateMLModelRequest method. // req, resp := client.CreateMLModelRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateMLModelRequest(input CreateMLModelInput) (req request.Request, output CreateMLModelOutput) { op := &request.Operation{ Name: opCreateMLModel, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateMLModelInput{} } output = &CreateMLModelOutput{} req = c.newRequest(op, input, output) return } // CreateMLModel API operation for Amazon Machine Learning. // // Creates a new MLModel using the DataSource and the recipe as information // sources. // // An MLModel is nearly immutable. Users can update only the MLModelName and // the ScoreThreshold in an MLModel without creating a new MLModel. // // CreateMLModel is an asynchronous operation. In response to CreateMLModel, // Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel // status to PENDING. After the MLModel has been created and ready is for use, // Amazon ML sets the status to COMPLETED. // // You can use the GetMLModel operation to check the progress of the MLModel // during the creation operation. // // CreateMLModel requires a DataSource with computed statistics, which can be // created by setting ComputeStatistics to true in CreateDataSourceFromRDS, // CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateMLModel for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - IdempotentParameterMismatchException // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. func (c MachineLearning) CreateMLModel(input CreateMLModelInput) (CreateMLModelOutput, error) { req, out := c.CreateMLModelRequest(input) return out, req.Send() } // CreateMLModelWithContext is the same as CreateMLModel with the addition of // the ability to pass a context and additional request options. // // See CreateMLModel for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateMLModelWithContext(ctx aws.Context, input CreateMLModelInput, opts ...request.Option) (CreateMLModelOutput, error) { req, out := c.CreateMLModelRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opCreateRealtimeEndpoint = "CreateRealtimeEndpoint" // CreateRealtimeEndpointRequest generates a "aws/request.Request" representing the // client's request for the CreateRealtimeEndpoint operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See CreateRealtimeEndpoint for more information on using the CreateRealtimeEndpoint // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the CreateRealtimeEndpointRequest method. // req, resp := client.CreateRealtimeEndpointRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) CreateRealtimeEndpointRequest(input CreateRealtimeEndpointInput) (req request.Request, output CreateRealtimeEndpointOutput) { op := &request.Operation{ Name: opCreateRealtimeEndpoint, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &CreateRealtimeEndpointInput{} } output = &CreateRealtimeEndpointOutput{} req = c.newRequest(op, input, output) return } // CreateRealtimeEndpoint API operation for Amazon Machine Learning. // // Creates a real-time endpoint for the MLModel. The endpoint contains the URI // of the MLModel; that is, the location to send real-time prediction requests // for the specified MLModel. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation CreateRealtimeEndpoint for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) CreateRealtimeEndpoint(input CreateRealtimeEndpointInput) (CreateRealtimeEndpointOutput, error) { req, out := c.CreateRealtimeEndpointRequest(input) return out, req.Send() } // CreateRealtimeEndpointWithContext is the same as CreateRealtimeEndpoint with the addition of // the ability to pass a context and additional request options. // // See CreateRealtimeEndpoint for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) CreateRealtimeEndpointWithContext(ctx aws.Context, input CreateRealtimeEndpointInput, opts ...request.Option) (CreateRealtimeEndpointOutput, error) { req, out := c.CreateRealtimeEndpointRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDeleteBatchPrediction = "DeleteBatchPrediction" // DeleteBatchPredictionRequest generates a "aws/request.Request" representing the // client's request for the DeleteBatchPrediction operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DeleteBatchPrediction for more information on using the DeleteBatchPrediction // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DeleteBatchPredictionRequest method. // req, resp := client.DeleteBatchPredictionRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DeleteBatchPredictionRequest(input DeleteBatchPredictionInput) (req request.Request, output DeleteBatchPredictionOutput) { op := &request.Operation{ Name: opDeleteBatchPrediction, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DeleteBatchPredictionInput{} } output = &DeleteBatchPredictionOutput{} req = c.newRequest(op, input, output) return } // DeleteBatchPrediction API operation for Amazon Machine Learning. // // Assigns the DELETED status to a BatchPrediction, rendering it unusable. // // After using the DeleteBatchPrediction operation, you can use the GetBatchPrediction // operation to verify that the status of the BatchPrediction changed to DELETED. // // Caution: The result of the DeleteBatchPrediction operation is irreversible. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DeleteBatchPrediction for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DeleteBatchPrediction(input DeleteBatchPredictionInput) (DeleteBatchPredictionOutput, error) { req, out := c.DeleteBatchPredictionRequest(input) return out, req.Send() } // DeleteBatchPredictionWithContext is the same as DeleteBatchPrediction with the addition of // the ability to pass a context and additional request options. // // See DeleteBatchPrediction for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DeleteBatchPredictionWithContext(ctx aws.Context, input DeleteBatchPredictionInput, opts ...request.Option) (DeleteBatchPredictionOutput, error) { req, out := c.DeleteBatchPredictionRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDeleteDataSource = "DeleteDataSource" // DeleteDataSourceRequest generates a "aws/request.Request" representing the // client's request for the DeleteDataSource operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DeleteDataSource for more information on using the DeleteDataSource // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DeleteDataSourceRequest method. // req, resp := client.DeleteDataSourceRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DeleteDataSourceRequest(input DeleteDataSourceInput) (req request.Request, output DeleteDataSourceOutput) { op := &request.Operation{ Name: opDeleteDataSource, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DeleteDataSourceInput{} } output = &DeleteDataSourceOutput{} req = c.newRequest(op, input, output) return } // DeleteDataSource API operation for Amazon Machine Learning. // // Assigns the DELETED status to a DataSource, rendering it unusable. // // After using the DeleteDataSource operation, you can use the GetDataSource // operation to verify that the status of the DataSource changed to DELETED. // // Caution: The results of the DeleteDataSource operation are irreversible. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DeleteDataSource for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DeleteDataSource(input DeleteDataSourceInput) (DeleteDataSourceOutput, error) { req, out := c.DeleteDataSourceRequest(input) return out, req.Send() } // DeleteDataSourceWithContext is the same as DeleteDataSource with the addition of // the ability to pass a context and additional request options. // // See DeleteDataSource for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DeleteDataSourceWithContext(ctx aws.Context, input DeleteDataSourceInput, opts ...request.Option) (DeleteDataSourceOutput, error) { req, out := c.DeleteDataSourceRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDeleteEvaluation = "DeleteEvaluation" // DeleteEvaluationRequest generates a "aws/request.Request" representing the // client's request for the DeleteEvaluation operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DeleteEvaluation for more information on using the DeleteEvaluation // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DeleteEvaluationRequest method. // req, resp := client.DeleteEvaluationRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DeleteEvaluationRequest(input DeleteEvaluationInput) (req request.Request, output DeleteEvaluationOutput) { op := &request.Operation{ Name: opDeleteEvaluation, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DeleteEvaluationInput{} } output = &DeleteEvaluationOutput{} req = c.newRequest(op, input, output) return } // DeleteEvaluation API operation for Amazon Machine Learning. // // Assigns the DELETED status to an Evaluation, rendering it unusable. // // After invoking the DeleteEvaluation operation, you can use the GetEvaluation // operation to verify that the status of the Evaluation changed to DELETED. // // Caution: The results of the DeleteEvaluation operation are irreversible. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DeleteEvaluation for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DeleteEvaluation(input DeleteEvaluationInput) (DeleteEvaluationOutput, error) { req, out := c.DeleteEvaluationRequest(input) return out, req.Send() } // DeleteEvaluationWithContext is the same as DeleteEvaluation with the addition of // the ability to pass a context and additional request options. // // See DeleteEvaluation for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DeleteEvaluationWithContext(ctx aws.Context, input DeleteEvaluationInput, opts ...request.Option) (DeleteEvaluationOutput, error) { req, out := c.DeleteEvaluationRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDeleteMLModel = "DeleteMLModel" // DeleteMLModelRequest generates a "aws/request.Request" representing the // client's request for the DeleteMLModel operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DeleteMLModel for more information on using the DeleteMLModel // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DeleteMLModelRequest method. // req, resp := client.DeleteMLModelRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DeleteMLModelRequest(input DeleteMLModelInput) (req request.Request, output DeleteMLModelOutput) { op := &request.Operation{ Name: opDeleteMLModel, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DeleteMLModelInput{} } output = &DeleteMLModelOutput{} req = c.newRequest(op, input, output) return } // DeleteMLModel API operation for Amazon Machine Learning. // // Assigns the DELETED status to an MLModel, rendering it unusable. // // After using the DeleteMLModel operation, you can use the GetMLModel operation // to verify that the status of the MLModel changed to DELETED. // // Caution: The result of the DeleteMLModel operation is irreversible. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DeleteMLModel for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DeleteMLModel(input DeleteMLModelInput) (DeleteMLModelOutput, error) { req, out := c.DeleteMLModelRequest(input) return out, req.Send() } // DeleteMLModelWithContext is the same as DeleteMLModel with the addition of // the ability to pass a context and additional request options. // // See DeleteMLModel for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DeleteMLModelWithContext(ctx aws.Context, input DeleteMLModelInput, opts ...request.Option) (DeleteMLModelOutput, error) { req, out := c.DeleteMLModelRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDeleteRealtimeEndpoint = "DeleteRealtimeEndpoint" // DeleteRealtimeEndpointRequest generates a "aws/request.Request" representing the // client's request for the DeleteRealtimeEndpoint operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DeleteRealtimeEndpoint for more information on using the DeleteRealtimeEndpoint // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DeleteRealtimeEndpointRequest method. // req, resp := client.DeleteRealtimeEndpointRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DeleteRealtimeEndpointRequest(input DeleteRealtimeEndpointInput) (req request.Request, output DeleteRealtimeEndpointOutput) { op := &request.Operation{ Name: opDeleteRealtimeEndpoint, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DeleteRealtimeEndpointInput{} } output = &DeleteRealtimeEndpointOutput{} req = c.newRequest(op, input, output) return } // DeleteRealtimeEndpoint API operation for Amazon Machine Learning. // // Deletes a real time endpoint of an MLModel. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DeleteRealtimeEndpoint for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DeleteRealtimeEndpoint(input DeleteRealtimeEndpointInput) (DeleteRealtimeEndpointOutput, error) { req, out := c.DeleteRealtimeEndpointRequest(input) return out, req.Send() } // DeleteRealtimeEndpointWithContext is the same as DeleteRealtimeEndpoint with the addition of // the ability to pass a context and additional request options. // // See DeleteRealtimeEndpoint for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DeleteRealtimeEndpointWithContext(ctx aws.Context, input DeleteRealtimeEndpointInput, opts ...request.Option) (DeleteRealtimeEndpointOutput, error) { req, out := c.DeleteRealtimeEndpointRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDeleteTags = "DeleteTags" // DeleteTagsRequest generates a "aws/request.Request" representing the // client's request for the DeleteTags operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DeleteTags for more information on using the DeleteTags // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DeleteTagsRequest method. // req, resp := client.DeleteTagsRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DeleteTagsRequest(input DeleteTagsInput) (req request.Request, output DeleteTagsOutput) { op := &request.Operation{ Name: opDeleteTags, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DeleteTagsInput{} } output = &DeleteTagsOutput{} req = c.newRequest(op, input, output) return } // DeleteTags API operation for Amazon Machine Learning. // // Deletes the specified tags associated with an ML object. After this operation // is complete, you can't recover deleted tags. // // If you specify a tag that doesn't exist, Amazon ML ignores it. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DeleteTags for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InvalidTagException // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DeleteTags(input DeleteTagsInput) (DeleteTagsOutput, error) { req, out := c.DeleteTagsRequest(input) return out, req.Send() } // DeleteTagsWithContext is the same as DeleteTags with the addition of // the ability to pass a context and additional request options. // // See DeleteTags for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DeleteTagsWithContext(ctx aws.Context, input DeleteTagsInput, opts ...request.Option) (DeleteTagsOutput, error) { req, out := c.DeleteTagsRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opDescribeBatchPredictions = "DescribeBatchPredictions" // DescribeBatchPredictionsRequest generates a "aws/request.Request" representing the // client's request for the DescribeBatchPredictions operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DescribeBatchPredictions for more information on using the DescribeBatchPredictions // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DescribeBatchPredictionsRequest method. // req, resp := client.DescribeBatchPredictionsRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DescribeBatchPredictionsRequest(input DescribeBatchPredictionsInput) (req request.Request, output DescribeBatchPredictionsOutput) { op := &request.Operation{ Name: opDescribeBatchPredictions, HTTPMethod: "POST", HTTPPath: "/", Paginator: &request.Paginator{ InputTokens: []string{"NextToken"}, OutputTokens: []string{"NextToken"}, LimitToken: "Limit", TruncationToken: "", }, } if input == nil { input = &DescribeBatchPredictionsInput{} } output = &DescribeBatchPredictionsOutput{} req = c.newRequest(op, input, output) return } // DescribeBatchPredictions API operation for Amazon Machine Learning. // // Returns a list of BatchPrediction operations that match the search criteria // in the request. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DescribeBatchPredictions for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DescribeBatchPredictions(input DescribeBatchPredictionsInput) (DescribeBatchPredictionsOutput, error) { req, out := c.DescribeBatchPredictionsRequest(input) return out, req.Send() } // DescribeBatchPredictionsWithContext is the same as DescribeBatchPredictions with the addition of // the ability to pass a context and additional request options. // // See DescribeBatchPredictions for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeBatchPredictionsWithContext(ctx aws.Context, input DescribeBatchPredictionsInput, opts ...request.Option) (DescribeBatchPredictionsOutput, error) { req, out := c.DescribeBatchPredictionsRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } // DescribeBatchPredictionsPages iterates over the pages of a DescribeBatchPredictions operation, // calling the "fn" function with the response data for each page. To stop // iterating, return false from the fn function. // // See DescribeBatchPredictions method for more information on how to use this operation. // // Note: This operation can generate multiple requests to a service. // // // Example iterating over at most 3 pages of a DescribeBatchPredictions operation. // pageNum := 0 // err := client.DescribeBatchPredictionsPages(params, // func(page machinelearning.DescribeBatchPredictionsOutput, lastPage bool) bool { // pageNum++ // fmt.Println(page) // return pageNum <= 3 // }) func (c MachineLearning) DescribeBatchPredictionsPages(input DescribeBatchPredictionsInput, fn func(DescribeBatchPredictionsOutput, bool) bool) error { return c.DescribeBatchPredictionsPagesWithContext(aws.BackgroundContext(), input, fn) } // DescribeBatchPredictionsPagesWithContext same as DescribeBatchPredictionsPages except // it takes a Context and allows setting request options on the pages. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeBatchPredictionsPagesWithContext(ctx aws.Context, input DescribeBatchPredictionsInput, fn func(DescribeBatchPredictionsOutput, bool) bool, opts ...request.Option) error { p := request.Pagination{ NewRequest: func() (request.Request, error) { var inCpy DescribeBatchPredictionsInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeBatchPredictionsRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } for p.Next() { if !fn(p.Page().(DescribeBatchPredictionsOutput), !p.HasNextPage()) { break } } return p.Err() } const opDescribeDataSources = "DescribeDataSources" // DescribeDataSourcesRequest generates a "aws/request.Request" representing the // client's request for the DescribeDataSources operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DescribeDataSources for more information on using the DescribeDataSources // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DescribeDataSourcesRequest method. // req, resp := client.DescribeDataSourcesRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DescribeDataSourcesRequest(input DescribeDataSourcesInput) (req request.Request, output DescribeDataSourcesOutput) { op := &request.Operation{ Name: opDescribeDataSources, HTTPMethod: "POST", HTTPPath: "/", Paginator: &request.Paginator{ InputTokens: []string{"NextToken"}, OutputTokens: []string{"NextToken"}, LimitToken: "Limit", TruncationToken: "", }, } if input == nil { input = &DescribeDataSourcesInput{} } output = &DescribeDataSourcesOutput{} req = c.newRequest(op, input, output) return } // DescribeDataSources API operation for Amazon Machine Learning. // // Returns a list of DataSource that match the search criteria in the request. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DescribeDataSources for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DescribeDataSources(input DescribeDataSourcesInput) (DescribeDataSourcesOutput, error) { req, out := c.DescribeDataSourcesRequest(input) return out, req.Send() } // DescribeDataSourcesWithContext is the same as DescribeDataSources with the addition of // the ability to pass a context and additional request options. // // See DescribeDataSources for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeDataSourcesWithContext(ctx aws.Context, input DescribeDataSourcesInput, opts ...request.Option) (DescribeDataSourcesOutput, error) { req, out := c.DescribeDataSourcesRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } // DescribeDataSourcesPages iterates over the pages of a DescribeDataSources operation, // calling the "fn" function with the response data for each page. To stop // iterating, return false from the fn function. // // See DescribeDataSources method for more information on how to use this operation. // // Note: This operation can generate multiple requests to a service. // // // Example iterating over at most 3 pages of a DescribeDataSources operation. // pageNum := 0 // err := client.DescribeDataSourcesPages(params, // func(page machinelearning.DescribeDataSourcesOutput, lastPage bool) bool { // pageNum++ // fmt.Println(page) // return pageNum <= 3 // }) func (c MachineLearning) DescribeDataSourcesPages(input DescribeDataSourcesInput, fn func(DescribeDataSourcesOutput, bool) bool) error { return c.DescribeDataSourcesPagesWithContext(aws.BackgroundContext(), input, fn) } // DescribeDataSourcesPagesWithContext same as DescribeDataSourcesPages except // it takes a Context and allows setting request options on the pages. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeDataSourcesPagesWithContext(ctx aws.Context, input DescribeDataSourcesInput, fn func(DescribeDataSourcesOutput, bool) bool, opts ...request.Option) error { p := request.Pagination{ NewRequest: func() (request.Request, error) { var inCpy DescribeDataSourcesInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeDataSourcesRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } for p.Next() { if !fn(p.Page().(DescribeDataSourcesOutput), !p.HasNextPage()) { break } } return p.Err() } const opDescribeEvaluations = "DescribeEvaluations" // DescribeEvaluationsRequest generates a "aws/request.Request" representing the // client's request for the DescribeEvaluations operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DescribeEvaluations for more information on using the DescribeEvaluations // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DescribeEvaluationsRequest method. // req, resp := client.DescribeEvaluationsRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DescribeEvaluationsRequest(input DescribeEvaluationsInput) (req request.Request, output DescribeEvaluationsOutput) { op := &request.Operation{ Name: opDescribeEvaluations, HTTPMethod: "POST", HTTPPath: "/", Paginator: &request.Paginator{ InputTokens: []string{"NextToken"}, OutputTokens: []string{"NextToken"}, LimitToken: "Limit", TruncationToken: "", }, } if input == nil { input = &DescribeEvaluationsInput{} } output = &DescribeEvaluationsOutput{} req = c.newRequest(op, input, output) return } // DescribeEvaluations API operation for Amazon Machine Learning. // // Returns a list of DescribeEvaluations that match the search criteria in the // request. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DescribeEvaluations for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DescribeEvaluations(input DescribeEvaluationsInput) (DescribeEvaluationsOutput, error) { req, out := c.DescribeEvaluationsRequest(input) return out, req.Send() } // DescribeEvaluationsWithContext is the same as DescribeEvaluations with the addition of // the ability to pass a context and additional request options. // // See DescribeEvaluations for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeEvaluationsWithContext(ctx aws.Context, input DescribeEvaluationsInput, opts ...request.Option) (DescribeEvaluationsOutput, error) { req, out := c.DescribeEvaluationsRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } // DescribeEvaluationsPages iterates over the pages of a DescribeEvaluations operation, // calling the "fn" function with the response data for each page. To stop // iterating, return false from the fn function. // // See DescribeEvaluations method for more information on how to use this operation. // // Note: This operation can generate multiple requests to a service. // // // Example iterating over at most 3 pages of a DescribeEvaluations operation. // pageNum := 0 // err := client.DescribeEvaluationsPages(params, // func(page machinelearning.DescribeEvaluationsOutput, lastPage bool) bool { // pageNum++ // fmt.Println(page) // return pageNum <= 3 // }) func (c MachineLearning) DescribeEvaluationsPages(input DescribeEvaluationsInput, fn func(DescribeEvaluationsOutput, bool) bool) error { return c.DescribeEvaluationsPagesWithContext(aws.BackgroundContext(), input, fn) } // DescribeEvaluationsPagesWithContext same as DescribeEvaluationsPages except // it takes a Context and allows setting request options on the pages. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeEvaluationsPagesWithContext(ctx aws.Context, input DescribeEvaluationsInput, fn func(DescribeEvaluationsOutput, bool) bool, opts ...request.Option) error { p := request.Pagination{ NewRequest: func() (request.Request, error) { var inCpy DescribeEvaluationsInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeEvaluationsRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } for p.Next() { if !fn(p.Page().(DescribeEvaluationsOutput), !p.HasNextPage()) { break } } return p.Err() } const opDescribeMLModels = "DescribeMLModels" // DescribeMLModelsRequest generates a "aws/request.Request" representing the // client's request for the DescribeMLModels operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DescribeMLModels for more information on using the DescribeMLModels // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DescribeMLModelsRequest method. // req, resp := client.DescribeMLModelsRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DescribeMLModelsRequest(input DescribeMLModelsInput) (req request.Request, output DescribeMLModelsOutput) { op := &request.Operation{ Name: opDescribeMLModels, HTTPMethod: "POST", HTTPPath: "/", Paginator: &request.Paginator{ InputTokens: []string{"NextToken"}, OutputTokens: []string{"NextToken"}, LimitToken: "Limit", TruncationToken: "", }, } if input == nil { input = &DescribeMLModelsInput{} } output = &DescribeMLModelsOutput{} req = c.newRequest(op, input, output) return } // DescribeMLModels API operation for Amazon Machine Learning. // // Returns a list of MLModel that match the search criteria in the request. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DescribeMLModels for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DescribeMLModels(input DescribeMLModelsInput) (DescribeMLModelsOutput, error) { req, out := c.DescribeMLModelsRequest(input) return out, req.Send() } // DescribeMLModelsWithContext is the same as DescribeMLModels with the addition of // the ability to pass a context and additional request options. // // See DescribeMLModels for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeMLModelsWithContext(ctx aws.Context, input DescribeMLModelsInput, opts ...request.Option) (DescribeMLModelsOutput, error) { req, out := c.DescribeMLModelsRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } // DescribeMLModelsPages iterates over the pages of a DescribeMLModels operation, // calling the "fn" function with the response data for each page. To stop // iterating, return false from the fn function. // // See DescribeMLModels method for more information on how to use this operation. // // Note: This operation can generate multiple requests to a service. // // // Example iterating over at most 3 pages of a DescribeMLModels operation. // pageNum := 0 // err := client.DescribeMLModelsPages(params, // func(page machinelearning.DescribeMLModelsOutput, lastPage bool) bool { // pageNum++ // fmt.Println(page) // return pageNum <= 3 // }) func (c MachineLearning) DescribeMLModelsPages(input DescribeMLModelsInput, fn func(DescribeMLModelsOutput, bool) bool) error { return c.DescribeMLModelsPagesWithContext(aws.BackgroundContext(), input, fn) } // DescribeMLModelsPagesWithContext same as DescribeMLModelsPages except // it takes a Context and allows setting request options on the pages. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeMLModelsPagesWithContext(ctx aws.Context, input DescribeMLModelsInput, fn func(DescribeMLModelsOutput, bool) bool, opts ...request.Option) error { p := request.Pagination{ NewRequest: func() (request.Request, error) { var inCpy DescribeMLModelsInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeMLModelsRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } for p.Next() { if !fn(p.Page().(DescribeMLModelsOutput), !p.HasNextPage()) { break } } return p.Err() } const opDescribeTags = "DescribeTags" // DescribeTagsRequest generates a "aws/request.Request" representing the // client's request for the DescribeTags operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See DescribeTags for more information on using the DescribeTags // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the DescribeTagsRequest method. // req, resp := client.DescribeTagsRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) DescribeTagsRequest(input DescribeTagsInput) (req request.Request, output DescribeTagsOutput) { op := &request.Operation{ Name: opDescribeTags, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &DescribeTagsInput{} } output = &DescribeTagsOutput{} req = c.newRequest(op, input, output) return } // DescribeTags API operation for Amazon Machine Learning. // // Describes one or more of the tags for your Amazon ML object. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation DescribeTags for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) DescribeTags(input DescribeTagsInput) (DescribeTagsOutput, error) { req, out := c.DescribeTagsRequest(input) return out, req.Send() } // DescribeTagsWithContext is the same as DescribeTags with the addition of // the ability to pass a context and additional request options. // // See DescribeTags for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) DescribeTagsWithContext(ctx aws.Context, input DescribeTagsInput, opts ...request.Option) (DescribeTagsOutput, error) { req, out := c.DescribeTagsRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opGetBatchPrediction = "GetBatchPrediction" // GetBatchPredictionRequest generates a "aws/request.Request" representing the // client's request for the GetBatchPrediction operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See GetBatchPrediction for more information on using the GetBatchPrediction // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the GetBatchPredictionRequest method. // req, resp := client.GetBatchPredictionRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) GetBatchPredictionRequest(input GetBatchPredictionInput) (req request.Request, output GetBatchPredictionOutput) { op := &request.Operation{ Name: opGetBatchPrediction, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &GetBatchPredictionInput{} } output = &GetBatchPredictionOutput{} req = c.newRequest(op, input, output) return } // GetBatchPrediction API operation for Amazon Machine Learning. // // Returns a BatchPrediction that includes detailed metadata, status, and data // file information for a Batch Prediction request. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation GetBatchPrediction for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) GetBatchPrediction(input GetBatchPredictionInput) (GetBatchPredictionOutput, error) { req, out := c.GetBatchPredictionRequest(input) return out, req.Send() } // GetBatchPredictionWithContext is the same as GetBatchPrediction with the addition of // the ability to pass a context and additional request options. // // See GetBatchPrediction for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) GetBatchPredictionWithContext(ctx aws.Context, input GetBatchPredictionInput, opts ...request.Option) (GetBatchPredictionOutput, error) { req, out := c.GetBatchPredictionRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opGetDataSource = "GetDataSource" // GetDataSourceRequest generates a "aws/request.Request" representing the // client's request for the GetDataSource operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See GetDataSource for more information on using the GetDataSource // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the GetDataSourceRequest method. // req, resp := client.GetDataSourceRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) GetDataSourceRequest(input GetDataSourceInput) (req request.Request, output GetDataSourceOutput) { op := &request.Operation{ Name: opGetDataSource, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &GetDataSourceInput{} } output = &GetDataSourceOutput{} req = c.newRequest(op, input, output) return } // GetDataSource API operation for Amazon Machine Learning. // // Returns a DataSource that includes metadata and data file information, as // well as the current status of the DataSource. // // GetDataSource provides results in normal or verbose format. The verbose format // adds the schema description and the list of files pointed to by the DataSource // to the normal format. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation GetDataSource for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) GetDataSource(input GetDataSourceInput) (GetDataSourceOutput, error) { req, out := c.GetDataSourceRequest(input) return out, req.Send() } // GetDataSourceWithContext is the same as GetDataSource with the addition of // the ability to pass a context and additional request options. // // See GetDataSource for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) GetDataSourceWithContext(ctx aws.Context, input GetDataSourceInput, opts ...request.Option) (GetDataSourceOutput, error) { req, out := c.GetDataSourceRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opGetEvaluation = "GetEvaluation" // GetEvaluationRequest generates a "aws/request.Request" representing the // client's request for the GetEvaluation operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See GetEvaluation for more information on using the GetEvaluation // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the GetEvaluationRequest method. // req, resp := client.GetEvaluationRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) GetEvaluationRequest(input GetEvaluationInput) (req request.Request, output GetEvaluationOutput) { op := &request.Operation{ Name: opGetEvaluation, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &GetEvaluationInput{} } output = &GetEvaluationOutput{} req = c.newRequest(op, input, output) return } // GetEvaluation API operation for Amazon Machine Learning. // // Returns an Evaluation that includes metadata as well as the current status // of the Evaluation. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation GetEvaluation for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) GetEvaluation(input GetEvaluationInput) (GetEvaluationOutput, error) { req, out := c.GetEvaluationRequest(input) return out, req.Send() } // GetEvaluationWithContext is the same as GetEvaluation with the addition of // the ability to pass a context and additional request options. // // See GetEvaluation for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) GetEvaluationWithContext(ctx aws.Context, input GetEvaluationInput, opts ...request.Option) (GetEvaluationOutput, error) { req, out := c.GetEvaluationRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opGetMLModel = "GetMLModel" // GetMLModelRequest generates a "aws/request.Request" representing the // client's request for the GetMLModel operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See GetMLModel for more information on using the GetMLModel // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the GetMLModelRequest method. // req, resp := client.GetMLModelRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) GetMLModelRequest(input GetMLModelInput) (req request.Request, output GetMLModelOutput) { op := &request.Operation{ Name: opGetMLModel, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &GetMLModelInput{} } output = &GetMLModelOutput{} req = c.newRequest(op, input, output) return } // GetMLModel API operation for Amazon Machine Learning. // // Returns an MLModel that includes detailed metadata, data source information, // and the current status of the MLModel. // // GetMLModel provides results in normal or verbose format. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation GetMLModel for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) GetMLModel(input GetMLModelInput) (GetMLModelOutput, error) { req, out := c.GetMLModelRequest(input) return out, req.Send() } // GetMLModelWithContext is the same as GetMLModel with the addition of // the ability to pass a context and additional request options. // // See GetMLModel for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) GetMLModelWithContext(ctx aws.Context, input GetMLModelInput, opts ...request.Option) (GetMLModelOutput, error) { req, out := c.GetMLModelRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opPredict = "Predict" // PredictRequest generates a "aws/request.Request" representing the // client's request for the Predict operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See Predict for more information on using the Predict // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the PredictRequest method. // req, resp := client.PredictRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) PredictRequest(input PredictInput) (req request.Request, output PredictOutput) { op := &request.Operation{ Name: opPredict, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &PredictInput{} } output = &PredictOutput{} req = c.newRequest(op, input, output) return } // Predict API operation for Amazon Machine Learning. // // Generates a prediction for the observation using the specified ML Model. // // Note: Not all response parameters will be populated. Whether a response parameter // is populated depends on the type of model requested. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation Predict for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - LimitExceededException // The subscriber exceeded the maximum number of operations. This exception // can occur when listing objects such as DataSource. // // - InternalServerException // An error on the server occurred when trying to process a request. // // - PredictorNotMountedException // The exception is thrown when a predict request is made to an unmounted MLModel. func (c MachineLearning) Predict(input PredictInput) (PredictOutput, error) { req, out := c.PredictRequest(input) return out, req.Send() } // PredictWithContext is the same as Predict with the addition of // the ability to pass a context and additional request options. // // See Predict for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) PredictWithContext(ctx aws.Context, input PredictInput, opts ...request.Option) (PredictOutput, error) { req, out := c.PredictRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opUpdateBatchPrediction = "UpdateBatchPrediction" // UpdateBatchPredictionRequest generates a "aws/request.Request" representing the // client's request for the UpdateBatchPrediction operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See UpdateBatchPrediction for more information on using the UpdateBatchPrediction // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the UpdateBatchPredictionRequest method. // req, resp := client.UpdateBatchPredictionRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) UpdateBatchPredictionRequest(input UpdateBatchPredictionInput) (req request.Request, output UpdateBatchPredictionOutput) { op := &request.Operation{ Name: opUpdateBatchPrediction, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &UpdateBatchPredictionInput{} } output = &UpdateBatchPredictionOutput{} req = c.newRequest(op, input, output) return } // UpdateBatchPrediction API operation for Amazon Machine Learning. // // Updates the BatchPredictionName of a BatchPrediction. // // You can use the GetBatchPrediction operation to view the contents of the // updated data element. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation UpdateBatchPrediction for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) UpdateBatchPrediction(input UpdateBatchPredictionInput) (UpdateBatchPredictionOutput, error) { req, out := c.UpdateBatchPredictionRequest(input) return out, req.Send() } // UpdateBatchPredictionWithContext is the same as UpdateBatchPrediction with the addition of // the ability to pass a context and additional request options. // // See UpdateBatchPrediction for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) UpdateBatchPredictionWithContext(ctx aws.Context, input UpdateBatchPredictionInput, opts ...request.Option) (UpdateBatchPredictionOutput, error) { req, out := c.UpdateBatchPredictionRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opUpdateDataSource = "UpdateDataSource" // UpdateDataSourceRequest generates a "aws/request.Request" representing the // client's request for the UpdateDataSource operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See UpdateDataSource for more information on using the UpdateDataSource // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the UpdateDataSourceRequest method. // req, resp := client.UpdateDataSourceRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) UpdateDataSourceRequest(input UpdateDataSourceInput) (req request.Request, output UpdateDataSourceOutput) { op := &request.Operation{ Name: opUpdateDataSource, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &UpdateDataSourceInput{} } output = &UpdateDataSourceOutput{} req = c.newRequest(op, input, output) return } // UpdateDataSource API operation for Amazon Machine Learning. // // Updates the DataSourceName of a DataSource. // // You can use the GetDataSource operation to view the contents of the updated // data element. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation UpdateDataSource for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) UpdateDataSource(input UpdateDataSourceInput) (UpdateDataSourceOutput, error) { req, out := c.UpdateDataSourceRequest(input) return out, req.Send() } // UpdateDataSourceWithContext is the same as UpdateDataSource with the addition of // the ability to pass a context and additional request options. // // See UpdateDataSource for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) UpdateDataSourceWithContext(ctx aws.Context, input UpdateDataSourceInput, opts ...request.Option) (UpdateDataSourceOutput, error) { req, out := c.UpdateDataSourceRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opUpdateEvaluation = "UpdateEvaluation" // UpdateEvaluationRequest generates a "aws/request.Request" representing the // client's request for the UpdateEvaluation operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See UpdateEvaluation for more information on using the UpdateEvaluation // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the UpdateEvaluationRequest method. // req, resp := client.UpdateEvaluationRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) UpdateEvaluationRequest(input UpdateEvaluationInput) (req request.Request, output UpdateEvaluationOutput) { op := &request.Operation{ Name: opUpdateEvaluation, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &UpdateEvaluationInput{} } output = &UpdateEvaluationOutput{} req = c.newRequest(op, input, output) return } // UpdateEvaluation API operation for Amazon Machine Learning. // // Updates the EvaluationName of an Evaluation. // // You can use the GetEvaluation operation to view the contents of the updated // data element. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation UpdateEvaluation for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) UpdateEvaluation(input UpdateEvaluationInput) (UpdateEvaluationOutput, error) { req, out := c.UpdateEvaluationRequest(input) return out, req.Send() } // UpdateEvaluationWithContext is the same as UpdateEvaluation with the addition of // the ability to pass a context and additional request options. // // See UpdateEvaluation for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) UpdateEvaluationWithContext(ctx aws.Context, input UpdateEvaluationInput, opts ...request.Option) (UpdateEvaluationOutput, error) { req, out := c.UpdateEvaluationRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } const opUpdateMLModel = "UpdateMLModel" // UpdateMLModelRequest generates a "aws/request.Request" representing the // client's request for the UpdateMLModel operation. The "output" return // value will be populated with the request's response once the request completes // successfully. // // Use "Send" method on the returned Request to send the API call to the service. // the "output" return value is not valid until after Send returns without error. // // See UpdateMLModel for more information on using the UpdateMLModel // API call, and error handling. // // This method is useful when you want to inject custom logic or configuration // into the SDK's request lifecycle. Such as custom headers, or retry logic. // // // Example sending a request using the UpdateMLModelRequest method. // req, resp := client.UpdateMLModelRequest(params) // // err := req.Send() // if err == nil { // resp is now filled // fmt.Println(resp) // } func (c MachineLearning) UpdateMLModelRequest(input UpdateMLModelInput) (req request.Request, output UpdateMLModelOutput) { op := &request.Operation{ Name: opUpdateMLModel, HTTPMethod: "POST", HTTPPath: "/", } if input == nil { input = &UpdateMLModelInput{} } output = &UpdateMLModelOutput{} req = c.newRequest(op, input, output) return } // UpdateMLModel API operation for Amazon Machine Learning. // // Updates the MLModelName and the ScoreThreshold of an MLModel. // // You can use the GetMLModel operation to view the contents of the updated // data element. // // Returns awserr.Error for service API and SDK errors. Use runtime type assertions // with awserr.Error's Code and Message methods to get detailed information about // the error. // // See the AWS API reference guide for Amazon Machine Learning's // API operation UpdateMLModel for usage and error information. // // Returned Error Types: // // - InvalidInputException // An error on the client occurred. Typically, the cause is an invalid input // value. // // - ResourceNotFoundException // A specified resource cannot be located. // // - InternalServerException // An error on the server occurred when trying to process a request. func (c MachineLearning) UpdateMLModel(input UpdateMLModelInput) (UpdateMLModelOutput, error) { req, out := c.UpdateMLModelRequest(input) return out, req.Send() } // UpdateMLModelWithContext is the same as UpdateMLModel with the addition of // the ability to pass a context and additional request options. // // See UpdateMLModel for details on how to use this API operation. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) UpdateMLModelWithContext(ctx aws.Context, input UpdateMLModelInput, opts ...request.Option) (UpdateMLModelOutput, error) { req, out := c.UpdateMLModelRequest(input) req.SetContext(ctx) req.ApplyOptions(opts...) return out, req.Send() } type AddTagsInput struct { _ struct{} `type:"structure"` // The ID of the ML object to tag. For example, exampleModelId. // // ResourceId is a required field ResourceId string `min:"1" type:"string" required:"true"` // The type of the ML object to tag. // // ResourceType is a required field ResourceType string `type:"string" required:"true" enum:"TaggableResourceType"` // The key-value pairs to use to create tags. If you specify a key without specifying // a value, Amazon ML creates a tag with the specified key and a value of null. // // Tags is a required field Tags []Tag `type:"list" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s AddTagsInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s AddTagsInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s AddTagsInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "AddTagsInput"} if s.ResourceId == nil { invalidParams.Add(request.NewErrParamRequired("ResourceId")) } if s.ResourceId != nil && len(s.ResourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("ResourceId", 1)) } if s.ResourceType == nil { invalidParams.Add(request.NewErrParamRequired("ResourceType")) } if s.Tags == nil { invalidParams.Add(request.NewErrParamRequired("Tags")) } if s.Tags != nil { for i, v := range s.Tags { if v == nil { continue } if err := v.Validate(); err != nil { invalidParams.AddNested(fmt.Sprintf("%s[%v]", "Tags", i), err.(request.ErrInvalidParams)) } } } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetResourceId sets the ResourceId field's value. func (s AddTagsInput) SetResourceId(v string) AddTagsInput { s.ResourceId = &v return s } // SetResourceType sets the ResourceType field's value. func (s AddTagsInput) SetResourceType(v string) AddTagsInput { s.ResourceType = &v return s } // SetTags sets the Tags field's value. func (s AddTagsInput) SetTags(v []Tag) AddTagsInput { s.Tags = v return s } // Amazon ML returns the following elements. type AddTagsOutput struct { _ struct{} `type:"structure"` // The ID of the ML object that was tagged. ResourceId string `min:"1" type:"string"` // The type of the ML object that was tagged. ResourceType string `type:"string" enum:"TaggableResourceType"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s AddTagsOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s AddTagsOutput) GoString() string { return s.String() } // SetResourceId sets the ResourceId field's value. func (s AddTagsOutput) SetResourceId(v string) AddTagsOutput { s.ResourceId = &v return s } // SetResourceType sets the ResourceType field's value. func (s AddTagsOutput) SetResourceType(v string) AddTagsOutput { s.ResourceType = &v return s } // Represents the output of a GetBatchPrediction operation. // // The content consists of the detailed metadata, the status, and the data file // information of a Batch Prediction. type BatchPrediction struct { _ struct{} `type:"structure"` // The ID of the DataSource that points to the group of observations to predict. BatchPredictionDataSourceId string `min:"1" type:"string"` // The ID assigned to the BatchPrediction at creation. This value should be // identical to the value of the BatchPredictionID in the request. BatchPredictionId string `min:"1" type:"string"` // Long integer type that is a 64-bit signed number. ComputeTime int64 `type:"long"` // The time that the BatchPrediction was created. The time is expressed in epoch // time. CreatedAt time.Time `type:"timestamp"` // The AWS user account that invoked the BatchPrediction. The account type can // be either an AWS root account or an AWS Identity and Access Management (IAM) // user account. CreatedByIamUser string `type:"string"` // A timestamp represented in epoch time. FinishedAt time.Time `type:"timestamp"` // The location of the data file or directory in Amazon Simple Storage Service // (Amazon S3). InputDataLocationS3 string `type:"string"` // Long integer type that is a 64-bit signed number. InvalidRecordCount int64 `type:"long"` // The time of the most recent edit to the BatchPrediction. The time is expressed // in epoch time. LastUpdatedAt time.Time `type:"timestamp"` // The ID of the MLModel that generated predictions for the BatchPrediction // request. MLModelId string `min:"1" type:"string"` // A description of the most recent details about processing the batch prediction // request. Message string `type:"string"` // A user-supplied name or description of the BatchPrediction. Name string `type:"string"` // The location of an Amazon S3 bucket or directory to receive the operation // results. The following substrings are not allowed in the s3 key portion of // the outputURI field: ':', '//', '/./', '/../'. OutputUri string `type:"string"` // A timestamp represented in epoch time. StartedAt time.Time `type:"timestamp"` // The status of the BatchPrediction. This element can have one of the following // values: // // * PENDING - Amazon Machine Learning (Amazon ML) submitted a request to // generate predictions for a batch of observations. // // * INPROGRESS - The process is underway. // // * FAILED - The request to perform a batch prediction did not run to completion. // It is not usable. // // * COMPLETED - The batch prediction process completed successfully. // // * DELETED - The BatchPrediction is marked as deleted. It is not usable. Status string `type:"string" enum:"EntityStatus"` // Long integer type that is a 64-bit signed number. TotalRecordCount int64 `type:"long"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s BatchPrediction) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s BatchPrediction) GoString() string { return s.String() } // SetBatchPredictionDataSourceId sets the BatchPredictionDataSourceId field's value. func (s BatchPrediction) SetBatchPredictionDataSourceId(v string) BatchPrediction { s.BatchPredictionDataSourceId = &v return s } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s BatchPrediction) SetBatchPredictionId(v string) BatchPrediction { s.BatchPredictionId = &v return s } // SetComputeTime sets the ComputeTime field's value. func (s BatchPrediction) SetComputeTime(v int64) BatchPrediction { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s BatchPrediction) SetCreatedAt(v time.Time) BatchPrediction { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s BatchPrediction) SetCreatedByIamUser(v string) BatchPrediction { s.CreatedByIamUser = &v return s } // SetFinishedAt sets the FinishedAt field's value. func (s BatchPrediction) SetFinishedAt(v time.Time) BatchPrediction { s.FinishedAt = &v return s } // SetInputDataLocationS3 sets the InputDataLocationS3 field's value. func (s BatchPrediction) SetInputDataLocationS3(v string) BatchPrediction { s.InputDataLocationS3 = &v return s } // SetInvalidRecordCount sets the InvalidRecordCount field's value. func (s BatchPrediction) SetInvalidRecordCount(v int64) BatchPrediction { s.InvalidRecordCount = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s BatchPrediction) SetLastUpdatedAt(v time.Time) BatchPrediction { s.LastUpdatedAt = &v return s } // SetMLModelId sets the MLModelId field's value. func (s BatchPrediction) SetMLModelId(v string) BatchPrediction { s.MLModelId = &v return s } // SetMessage sets the Message field's value. func (s BatchPrediction) SetMessage(v string) BatchPrediction { s.Message = &v return s } // SetName sets the Name field's value. func (s BatchPrediction) SetName(v string) BatchPrediction { s.Name = &v return s } // SetOutputUri sets the OutputUri field's value. func (s BatchPrediction) SetOutputUri(v string) BatchPrediction { s.OutputUri = &v return s } // SetStartedAt sets the StartedAt field's value. func (s BatchPrediction) SetStartedAt(v time.Time) BatchPrediction { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s BatchPrediction) SetStatus(v string) BatchPrediction { s.Status = &v return s } // SetTotalRecordCount sets the TotalRecordCount field's value. func (s BatchPrediction) SetTotalRecordCount(v int64) BatchPrediction { s.TotalRecordCount = &v return s } type CreateBatchPredictionInput struct { _ struct{} `type:"structure"` // The ID of the DataSource that points to the group of observations to predict. // // BatchPredictionDataSourceId is a required field BatchPredictionDataSourceId string `min:"1" type:"string" required:"true"` // A user-supplied ID that uniquely identifies the BatchPrediction. // // BatchPredictionId is a required field BatchPredictionId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the BatchPrediction. BatchPredictionName // can only use the UTF-8 character set. BatchPredictionName string `type:"string"` // The ID of the MLModel that will generate predictions for the group of observations. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` // The location of an Amazon Simple Storage Service (Amazon S3) bucket or directory // to store the batch prediction results. The following substrings are not allowed // in the s3 key portion of the outputURI field: ':', '//', '/./', '/../'. // // Amazon ML needs permissions to store and retrieve the logs on your behalf. // For information about how to set permissions, see the Amazon Machine Learning // Developer Guide (https://docs.aws.amazon.com/machine-learning/latest/dg). // // OutputUri is a required field OutputUri string `type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateBatchPredictionInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateBatchPredictionInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateBatchPredictionInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateBatchPredictionInput"} if s.BatchPredictionDataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("BatchPredictionDataSourceId")) } if s.BatchPredictionDataSourceId != nil && len(s.BatchPredictionDataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("BatchPredictionDataSourceId", 1)) } if s.BatchPredictionId == nil { invalidParams.Add(request.NewErrParamRequired("BatchPredictionId")) } if s.BatchPredictionId != nil && len(s.BatchPredictionId) < 1 { invalidParams.Add(request.NewErrParamMinLen("BatchPredictionId", 1)) } if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if s.OutputUri == nil { invalidParams.Add(request.NewErrParamRequired("OutputUri")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetBatchPredictionDataSourceId sets the BatchPredictionDataSourceId field's value. func (s CreateBatchPredictionInput) SetBatchPredictionDataSourceId(v string) CreateBatchPredictionInput { s.BatchPredictionDataSourceId = &v return s } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s CreateBatchPredictionInput) SetBatchPredictionId(v string) CreateBatchPredictionInput { s.BatchPredictionId = &v return s } // SetBatchPredictionName sets the BatchPredictionName field's value. func (s CreateBatchPredictionInput) SetBatchPredictionName(v string) CreateBatchPredictionInput { s.BatchPredictionName = &v return s } // SetMLModelId sets the MLModelId field's value. func (s CreateBatchPredictionInput) SetMLModelId(v string) CreateBatchPredictionInput { s.MLModelId = &v return s } // SetOutputUri sets the OutputUri field's value. func (s CreateBatchPredictionInput) SetOutputUri(v string) CreateBatchPredictionInput { s.OutputUri = &v return s } // Represents the output of a CreateBatchPrediction operation, and is an acknowledgement // that Amazon ML received the request. // // The CreateBatchPrediction operation is asynchronous. You can poll for status // updates by using the >GetBatchPrediction operation and checking the Status // parameter of the result. type CreateBatchPredictionOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the BatchPrediction. This value // is identical to the value of the BatchPredictionId in the request. BatchPredictionId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateBatchPredictionOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateBatchPredictionOutput) GoString() string { return s.String() } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s CreateBatchPredictionOutput) SetBatchPredictionId(v string) CreateBatchPredictionOutput { s.BatchPredictionId = &v return s } type CreateDataSourceFromRDSInput struct { _ struct{} `type:"structure"` // The compute statistics for a DataSource. The statistics are generated from // the observation data referenced by a DataSource. Amazon ML uses the statistics // internally during MLModel training. This parameter must be set to true if // the DataSource needs to be used for MLModel training. ComputeStatistics bool `type:"boolean"` // A user-supplied ID that uniquely identifies the DataSource. Typically, an // Amazon Resource Number (ARN) becomes the ID for a DataSource. // // DataSourceId is a required field DataSourceId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the DataSource. DataSourceName string `type:"string"` // The data specification of an Amazon RDS DataSource: // // DatabaseInformation - DatabaseName - The name of the Amazon RDS database. // InstanceIdentifier - A unique identifier for the Amazon RDS database instance. // // * DatabaseCredentials - AWS Identity and Access Management (IAM) credentials // that are used to connect to the Amazon RDS database. // // * ResourceRole - A role (DataPipelineDefaultResourceRole) assumed by an // EC2 instance to carry out the copy task from Amazon RDS to Amazon Simple // Storage Service (Amazon S3). For more information, see Role templates // (https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html) // for data pipelines. // // * ServiceRole - A role (DataPipelineDefaultRole) assumed by the AWS Data // Pipeline service to monitor the progress of the copy task from Amazon // RDS to Amazon S3. For more information, see Role templates (https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html) // for data pipelines. // // * SecurityInfo - The security information to use to access an RDS DB instance. // You need to set up appropriate ingress rules for the security entity IDs // provided to allow access to the Amazon RDS instance. Specify a [SubnetId, // SecurityGroupIds] pair for a VPC-based RDS DB instance. // // * SelectSqlQuery - A query that is used to retrieve the observation data // for the Datasource. // // * S3StagingLocation - The Amazon S3 location for staging Amazon RDS data. // The data retrieved from Amazon RDS using SelectSqlQuery is stored in this // location. // // * DataSchemaUri - The Amazon S3 location of the DataSchema. // // * DataSchema - A JSON string representing the schema. This is not required // if DataSchemaUri is specified. // // * DataRearrangement - A JSON string that represents the splitting and // rearrangement requirements for the Datasource. Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}" // // RDSData is a required field RDSData RDSDataSpec `type:"structure" required:"true"` // The role that Amazon ML assumes on behalf of the user to create and activate // a data pipeline in the user's account and copy data using the SelectSqlQuery // query from Amazon RDS to Amazon S3. // // RoleARN is a required field RoleARN string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRDSInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRDSInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateDataSourceFromRDSInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateDataSourceFromRDSInput"} if s.DataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceId")) } if s.DataSourceId != nil && len(s.DataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("DataSourceId", 1)) } if s.RDSData == nil { invalidParams.Add(request.NewErrParamRequired("RDSData")) } if s.RoleARN == nil { invalidParams.Add(request.NewErrParamRequired("RoleARN")) } if s.RoleARN != nil && len(s.RoleARN) < 1 { invalidParams.Add(request.NewErrParamMinLen("RoleARN", 1)) } if s.RDSData != nil { if err := s.RDSData.Validate(); err != nil { invalidParams.AddNested("RDSData", err.(request.ErrInvalidParams)) } } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetComputeStatistics sets the ComputeStatistics field's value. func (s CreateDataSourceFromRDSInput) SetComputeStatistics(v bool) CreateDataSourceFromRDSInput { s.ComputeStatistics = &v return s } // SetDataSourceId sets the DataSourceId field's value. func (s CreateDataSourceFromRDSInput) SetDataSourceId(v string) CreateDataSourceFromRDSInput { s.DataSourceId = &v return s } // SetDataSourceName sets the DataSourceName field's value. func (s CreateDataSourceFromRDSInput) SetDataSourceName(v string) CreateDataSourceFromRDSInput { s.DataSourceName = &v return s } // SetRDSData sets the RDSData field's value. func (s CreateDataSourceFromRDSInput) SetRDSData(v RDSDataSpec) CreateDataSourceFromRDSInput { s.RDSData = v return s } // SetRoleARN sets the RoleARN field's value. func (s CreateDataSourceFromRDSInput) SetRoleARN(v string) CreateDataSourceFromRDSInput { s.RoleARN = &v return s } // Represents the output of a CreateDataSourceFromRDS operation, and is an acknowledgement // that Amazon ML received the request. // // The CreateDataSourceFromRDS> operation is asynchronous. You can poll for // updates by using the GetBatchPrediction operation and checking the Status // parameter. You can inspect the Message when Status shows up as FAILED. You // can also check the progress of the copy operation by going to the DataPipeline // console and looking up the pipeline using the pipelineId from the describe // call. type CreateDataSourceFromRDSOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the datasource. This value should // be identical to the value of the DataSourceID in the request. DataSourceId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRDSOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRDSOutput) GoString() string { return s.String() } // SetDataSourceId sets the DataSourceId field's value. func (s CreateDataSourceFromRDSOutput) SetDataSourceId(v string) CreateDataSourceFromRDSOutput { s.DataSourceId = &v return s } type CreateDataSourceFromRedshiftInput struct { _ struct{} `type:"structure"` // The compute statistics for a DataSource. The statistics are generated from // the observation data referenced by a DataSource. Amazon ML uses the statistics // internally during MLModel training. This parameter must be set to true if // the DataSource needs to be used for MLModel training. ComputeStatistics bool `type:"boolean"` // A user-supplied ID that uniquely identifies the DataSource. // // DataSourceId is a required field DataSourceId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the DataSource. DataSourceName string `type:"string"` // The data specification of an Amazon Redshift DataSource: // // * DatabaseInformation - DatabaseName - The name of the Amazon Redshift // database. ClusterIdentifier - The unique ID for the Amazon Redshift cluster. // // * DatabaseCredentials - The AWS Identity and Access Management (IAM) credentials // that are used to connect to the Amazon Redshift database. // // * SelectSqlQuery - The query that is used to retrieve the observation // data for the Datasource. // // * S3StagingLocation - The Amazon Simple Storage Service (Amazon S3) location // for staging Amazon Redshift data. The data retrieved from Amazon Redshift // using the SelectSqlQuery query is stored in this location. // // * DataSchemaUri - The Amazon S3 location of the DataSchema. // // * DataSchema - A JSON string representing the schema. This is not required // if DataSchemaUri is specified. // // * DataRearrangement - A JSON string that represents the splitting and // rearrangement requirements for the DataSource. Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}" // // DataSpec is a required field DataSpec RedshiftDataSpec `type:"structure" required:"true"` // A fully specified role Amazon Resource Name (ARN). Amazon ML assumes the // role on behalf of the user to create the following: // // A security group to allow Amazon ML to execute the SelectSqlQuery query // on an Amazon Redshift cluster // // * An Amazon S3 bucket policy to grant Amazon ML read/write permissions // on the S3StagingLocation // // RoleARN is a required field RoleARN string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRedshiftInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRedshiftInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateDataSourceFromRedshiftInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateDataSourceFromRedshiftInput"} if s.DataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceId")) } if s.DataSourceId != nil && len(s.DataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("DataSourceId", 1)) } if s.DataSpec == nil { invalidParams.Add(request.NewErrParamRequired("DataSpec")) } if s.RoleARN == nil { invalidParams.Add(request.NewErrParamRequired("RoleARN")) } if s.RoleARN != nil && len(s.RoleARN) < 1 { invalidParams.Add(request.NewErrParamMinLen("RoleARN", 1)) } if s.DataSpec != nil { if err := s.DataSpec.Validate(); err != nil { invalidParams.AddNested("DataSpec", err.(request.ErrInvalidParams)) } } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetComputeStatistics sets the ComputeStatistics field's value. func (s CreateDataSourceFromRedshiftInput) SetComputeStatistics(v bool) CreateDataSourceFromRedshiftInput { s.ComputeStatistics = &v return s } // SetDataSourceId sets the DataSourceId field's value. func (s CreateDataSourceFromRedshiftInput) SetDataSourceId(v string) CreateDataSourceFromRedshiftInput { s.DataSourceId = &v return s } // SetDataSourceName sets the DataSourceName field's value. func (s CreateDataSourceFromRedshiftInput) SetDataSourceName(v string) CreateDataSourceFromRedshiftInput { s.DataSourceName = &v return s } // SetDataSpec sets the DataSpec field's value. func (s CreateDataSourceFromRedshiftInput) SetDataSpec(v RedshiftDataSpec) CreateDataSourceFromRedshiftInput { s.DataSpec = v return s } // SetRoleARN sets the RoleARN field's value. func (s CreateDataSourceFromRedshiftInput) SetRoleARN(v string) CreateDataSourceFromRedshiftInput { s.RoleARN = &v return s } // Represents the output of a CreateDataSourceFromRedshift operation, and is // an acknowledgement that Amazon ML received the request. // // The CreateDataSourceFromRedshift operation is asynchronous. You can poll // for updates by using the GetBatchPrediction operation and checking the Status // parameter. type CreateDataSourceFromRedshiftOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the datasource. This value should // be identical to the value of the DataSourceID in the request. DataSourceId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRedshiftOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromRedshiftOutput) GoString() string { return s.String() } // SetDataSourceId sets the DataSourceId field's value. func (s CreateDataSourceFromRedshiftOutput) SetDataSourceId(v string) CreateDataSourceFromRedshiftOutput { s.DataSourceId = &v return s } type CreateDataSourceFromS3Input struct { _ struct{} `type:"structure"` // The compute statistics for a DataSource. The statistics are generated from // the observation data referenced by a DataSource. Amazon ML uses the statistics // internally during MLModel training. This parameter must be set to true if // the DataSource needs to be used for MLModel training. ComputeStatistics bool `type:"boolean"` // A user-supplied identifier that uniquely identifies the DataSource. // // DataSourceId is a required field DataSourceId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the DataSource. DataSourceName string `type:"string"` // The data specification of a DataSource: // // DataLocationS3 - The Amazon S3 location of the observation data. // // * DataSchemaLocationS3 - The Amazon S3 location of the DataSchema. // // * DataSchema - A JSON string representing the schema. This is not required // if DataSchemaUri is specified. // // * DataRearrangement - A JSON string that represents the splitting and // rearrangement requirements for the Datasource. Sample - "{\"splitting\":{\"percentBegin\":10,\"percentEnd\":60}}" // // DataSpec is a required field DataSpec S3DataSpec `type:"structure" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromS3Input) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromS3Input) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateDataSourceFromS3Input) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateDataSourceFromS3Input"} if s.DataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceId")) } if s.DataSourceId != nil && len(s.DataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("DataSourceId", 1)) } if s.DataSpec == nil { invalidParams.Add(request.NewErrParamRequired("DataSpec")) } if s.DataSpec != nil { if err := s.DataSpec.Validate(); err != nil { invalidParams.AddNested("DataSpec", err.(request.ErrInvalidParams)) } } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetComputeStatistics sets the ComputeStatistics field's value. func (s CreateDataSourceFromS3Input) SetComputeStatistics(v bool) CreateDataSourceFromS3Input { s.ComputeStatistics = &v return s } // SetDataSourceId sets the DataSourceId field's value. func (s CreateDataSourceFromS3Input) SetDataSourceId(v string) CreateDataSourceFromS3Input { s.DataSourceId = &v return s } // SetDataSourceName sets the DataSourceName field's value. func (s CreateDataSourceFromS3Input) SetDataSourceName(v string) CreateDataSourceFromS3Input { s.DataSourceName = &v return s } // SetDataSpec sets the DataSpec field's value. func (s CreateDataSourceFromS3Input) SetDataSpec(v S3DataSpec) CreateDataSourceFromS3Input { s.DataSpec = v return s } // Represents the output of a CreateDataSourceFromS3 operation, and is an acknowledgement // that Amazon ML received the request. // // The CreateDataSourceFromS3 operation is asynchronous. You can poll for updates // by using the GetBatchPrediction operation and checking the Status parameter. type CreateDataSourceFromS3Output struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the DataSource. This value should // be identical to the value of the DataSourceID in the request. DataSourceId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromS3Output) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateDataSourceFromS3Output) GoString() string { return s.String() } // SetDataSourceId sets the DataSourceId field's value. func (s CreateDataSourceFromS3Output) SetDataSourceId(v string) CreateDataSourceFromS3Output { s.DataSourceId = &v return s } type CreateEvaluationInput struct { _ struct{} `type:"structure"` // The ID of the DataSource for the evaluation. The schema of the DataSource // must match the schema used to create the MLModel. // // EvaluationDataSourceId is a required field EvaluationDataSourceId string `min:"1" type:"string" required:"true"` // A user-supplied ID that uniquely identifies the Evaluation. // // EvaluationId is a required field EvaluationId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the Evaluation. EvaluationName string `type:"string"` // The ID of the MLModel to evaluate. // // The schema used in creating the MLModel must match the schema of the DataSource // used in the Evaluation. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateEvaluationInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateEvaluationInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateEvaluationInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateEvaluationInput"} if s.EvaluationDataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("EvaluationDataSourceId")) } if s.EvaluationDataSourceId != nil && len(s.EvaluationDataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("EvaluationDataSourceId", 1)) } if s.EvaluationId == nil { invalidParams.Add(request.NewErrParamRequired("EvaluationId")) } if s.EvaluationId != nil && len(s.EvaluationId) < 1 { invalidParams.Add(request.NewErrParamMinLen("EvaluationId", 1)) } if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEvaluationDataSourceId sets the EvaluationDataSourceId field's value. func (s CreateEvaluationInput) SetEvaluationDataSourceId(v string) CreateEvaluationInput { s.EvaluationDataSourceId = &v return s } // SetEvaluationId sets the EvaluationId field's value. func (s CreateEvaluationInput) SetEvaluationId(v string) CreateEvaluationInput { s.EvaluationId = &v return s } // SetEvaluationName sets the EvaluationName field's value. func (s CreateEvaluationInput) SetEvaluationName(v string) CreateEvaluationInput { s.EvaluationName = &v return s } // SetMLModelId sets the MLModelId field's value. func (s CreateEvaluationInput) SetMLModelId(v string) CreateEvaluationInput { s.MLModelId = &v return s } // Represents the output of a CreateEvaluation operation, and is an acknowledgement // that Amazon ML received the request. // // CreateEvaluation operation is asynchronous. You can poll for status updates // by using the GetEvcaluation operation and checking the Status parameter. type CreateEvaluationOutput struct { _ struct{} `type:"structure"` // The user-supplied ID that uniquely identifies the Evaluation. This value // should be identical to the value of the EvaluationId in the request. EvaluationId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateEvaluationOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateEvaluationOutput) GoString() string { return s.String() } // SetEvaluationId sets the EvaluationId field's value. func (s CreateEvaluationOutput) SetEvaluationId(v string) CreateEvaluationOutput { s.EvaluationId = &v return s } type CreateMLModelInput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the MLModel. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the MLModel. MLModelName string `type:"string"` // The category of supervised learning that this MLModel will address. Choose // from the following types: // // * Choose REGRESSION if the MLModel will be used to predict a numeric value. // // * Choose BINARY if the MLModel result has two possible values. // // * Choose MULTICLASS if the MLModel result has a limited number of values. // // For more information, see the Amazon Machine Learning Developer Guide (https://docs.aws.amazon.com/machine-learning/latest/dg). // // MLModelType is a required field MLModelType string `type:"string" required:"true" enum:"MLModelType"` // A list of the training parameters in the MLModel. The list is implemented // as a map of key-value pairs. // // The following is the current set of training parameters: // // sgd.maxMLModelSizeInBytes - The maximum allowed size of the model. Depending // on the input data, the size of the model might affect its performance. // The value is an integer that ranges from 100000 to 2147483648. The default // value is 33554432. // // * sgd.maxPasses - The number of times that the training process traverses // the observations to build the MLModel. The value is an integer that ranges // from 1 to 10000. The default value is 10. // // * sgd.shuffleType - Whether Amazon ML shuffles the training data. Shuffling // the data improves a model's ability to find the optimal solution for a // variety of data types. The valid values are auto and none. The default // value is none. We strongly recommend that you shuffle your data. // // * sgd.l1RegularizationAmount - The coefficient regularization L1 norm. // It controls overfitting the data by penalizing large coefficients. This // tends to drive coefficients to zero, resulting in a sparse feature set. // If you use this parameter, start by specifying a small value, such as // 1.0E-08. The value is a double that ranges from 0 to MAX_DOUBLE. The default // is to not use L1 normalization. This parameter can't be used when L2 is // specified. Use this parameter sparingly. // // * sgd.l2RegularizationAmount - The coefficient regularization L2 norm. // It controls overfitting the data by penalizing large coefficients. This // tends to drive coefficients to small, nonzero values. If you use this // parameter, start by specifying a small value, such as 1.0E-08. The value // is a double that ranges from 0 to MAX_DOUBLE. The default is to not use // L2 normalization. This parameter can't be used when L1 is specified. Use // this parameter sparingly. Parameters map[string]string `type:"map"` // The data recipe for creating the MLModel. You must specify either the recipe // or its URI. If you don't specify a recipe or its URI, Amazon ML creates a // default. Recipe string `type:"string"` // The Amazon Simple Storage Service (Amazon S3) location and file name that // contains the MLModel recipe. You must specify either the recipe or its URI. // If you don't specify a recipe or its URI, Amazon ML creates a default. RecipeUri string `type:"string"` // The DataSource that points to the training data. // // TrainingDataSourceId is a required field TrainingDataSourceId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateMLModelInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateMLModelInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateMLModelInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateMLModelInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if s.MLModelType == nil { invalidParams.Add(request.NewErrParamRequired("MLModelType")) } if s.TrainingDataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("TrainingDataSourceId")) } if s.TrainingDataSourceId != nil && len(s.TrainingDataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("TrainingDataSourceId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s CreateMLModelInput) SetMLModelId(v string) CreateMLModelInput { s.MLModelId = &v return s } // SetMLModelName sets the MLModelName field's value. func (s CreateMLModelInput) SetMLModelName(v string) CreateMLModelInput { s.MLModelName = &v return s } // SetMLModelType sets the MLModelType field's value. func (s CreateMLModelInput) SetMLModelType(v string) CreateMLModelInput { s.MLModelType = &v return s } // SetParameters sets the Parameters field's value. func (s CreateMLModelInput) SetParameters(v map[string]string) CreateMLModelInput { s.Parameters = v return s } // SetRecipe sets the Recipe field's value. func (s CreateMLModelInput) SetRecipe(v string) CreateMLModelInput { s.Recipe = &v return s } // SetRecipeUri sets the RecipeUri field's value. func (s CreateMLModelInput) SetRecipeUri(v string) CreateMLModelInput { s.RecipeUri = &v return s } // SetTrainingDataSourceId sets the TrainingDataSourceId field's value. func (s CreateMLModelInput) SetTrainingDataSourceId(v string) CreateMLModelInput { s.TrainingDataSourceId = &v return s } // Represents the output of a CreateMLModel operation, and is an acknowledgement // that Amazon ML received the request. // // The CreateMLModel operation is asynchronous. You can poll for status updates // by using the GetMLModel operation and checking the Status parameter. type CreateMLModelOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the MLModel. This value should // be identical to the value of the MLModelId in the request. MLModelId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateMLModelOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateMLModelOutput) GoString() string { return s.String() } // SetMLModelId sets the MLModelId field's value. func (s CreateMLModelOutput) SetMLModelId(v string) CreateMLModelOutput { s.MLModelId = &v return s } type CreateRealtimeEndpointInput struct { _ struct{} `type:"structure"` // The ID assigned to the MLModel during creation. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateRealtimeEndpointInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateRealtimeEndpointInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s CreateRealtimeEndpointInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "CreateRealtimeEndpointInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s CreateRealtimeEndpointInput) SetMLModelId(v string) CreateRealtimeEndpointInput { s.MLModelId = &v return s } // Represents the output of an CreateRealtimeEndpoint operation. // // The result contains the MLModelId and the endpoint information for the MLModel. // // Note: The endpoint information includes the URI of the MLModel; that is, // the location to send online prediction requests for the specified MLModel. type CreateRealtimeEndpointOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the MLModel. This value should // be identical to the value of the MLModelId in the request. MLModelId string `min:"1" type:"string"` // The endpoint information of the MLModel RealtimeEndpointInfo RealtimeEndpointInfo `type:"structure"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateRealtimeEndpointOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s CreateRealtimeEndpointOutput) GoString() string { return s.String() } // SetMLModelId sets the MLModelId field's value. func (s CreateRealtimeEndpointOutput) SetMLModelId(v string) CreateRealtimeEndpointOutput { s.MLModelId = &v return s } // SetRealtimeEndpointInfo sets the RealtimeEndpointInfo field's value. func (s CreateRealtimeEndpointOutput) SetRealtimeEndpointInfo(v RealtimeEndpointInfo) CreateRealtimeEndpointOutput { s.RealtimeEndpointInfo = v return s } // Represents the output of the GetDataSource operation. // // The content consists of the detailed metadata and data file information and // the current status of the DataSource. type DataSource struct { _ struct{} `type:"structure"` // The parameter is true if statistics need to be generated from the observation // data. ComputeStatistics bool `type:"boolean"` // Long integer type that is a 64-bit signed number. ComputeTime int64 `type:"long"` // The time that the DataSource was created. The time is expressed in epoch // time. CreatedAt time.Time `type:"timestamp"` // The AWS user account from which the DataSource was created. The account type // can be either an AWS root account or an AWS Identity and Access Management // (IAM) user account. CreatedByIamUser string `type:"string"` // The location and name of the data in Amazon Simple Storage Service (Amazon // S3) that is used by a DataSource. DataLocationS3 string `type:"string"` // A JSON string that represents the splitting and rearrangement requirement // used when this DataSource was created. DataRearrangement string `type:"string"` // The total number of observations contained in the data files that the DataSource // references. DataSizeInBytes int64 `type:"long"` // The ID that is assigned to the DataSource during creation. DataSourceId string `min:"1" type:"string"` // A timestamp represented in epoch time. FinishedAt time.Time `type:"timestamp"` // The time of the most recent edit to the BatchPrediction. The time is expressed // in epoch time. LastUpdatedAt time.Time `type:"timestamp"` // A description of the most recent details about creating the DataSource. Message string `type:"string"` // A user-supplied name or description of the DataSource. Name string `type:"string"` // The number of data files referenced by the DataSource. NumberOfFiles int64 `type:"long"` // The datasource details that are specific to Amazon RDS. RDSMetadata RDSMetadata `type:"structure"` // Describes the DataSource details specific to Amazon Redshift. RedshiftMetadata RedshiftMetadata `type:"structure"` // The Amazon Resource Name (ARN) of an AWS IAM Role (https://docs.aws.amazon.com/IAM/latest/UserGuide/roles-toplevel.html#roles-about-termsandconcepts), // such as the following: arn:aws:iam::account:role/rolename. RoleARN string `min:"1" type:"string"` // A timestamp represented in epoch time. StartedAt time.Time `type:"timestamp"` // The current status of the DataSource. This element can have one of the following // values: // // * PENDING - Amazon Machine Learning (Amazon ML) submitted a request to // create a DataSource. // // * INPROGRESS - The creation process is underway. // // * FAILED - The request to create a DataSource did not run to completion. // It is not usable. // // * COMPLETED - The creation process completed successfully. // // * DELETED - The DataSource is marked as deleted. It is not usable. Status string `type:"string" enum:"EntityStatus"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DataSource) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DataSource) GoString() string { return s.String() } // SetComputeStatistics sets the ComputeStatistics field's value. func (s DataSource) SetComputeStatistics(v bool) DataSource { s.ComputeStatistics = &v return s } // SetComputeTime sets the ComputeTime field's value. func (s DataSource) SetComputeTime(v int64) DataSource { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s DataSource) SetCreatedAt(v time.Time) DataSource { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s DataSource) SetCreatedByIamUser(v string) DataSource { s.CreatedByIamUser = &v return s } // SetDataLocationS3 sets the DataLocationS3 field's value. func (s DataSource) SetDataLocationS3(v string) DataSource { s.DataLocationS3 = &v return s } // SetDataRearrangement sets the DataRearrangement field's value. func (s DataSource) SetDataRearrangement(v string) DataSource { s.DataRearrangement = &v return s } // SetDataSizeInBytes sets the DataSizeInBytes field's value. func (s DataSource) SetDataSizeInBytes(v int64) DataSource { s.DataSizeInBytes = &v return s } // SetDataSourceId sets the DataSourceId field's value. func (s DataSource) SetDataSourceId(v string) DataSource { s.DataSourceId = &v return s } // SetFinishedAt sets the FinishedAt field's value. func (s DataSource) SetFinishedAt(v time.Time) DataSource { s.FinishedAt = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s DataSource) SetLastUpdatedAt(v time.Time) DataSource { s.LastUpdatedAt = &v return s } // SetMessage sets the Message field's value. func (s DataSource) SetMessage(v string) DataSource { s.Message = &v return s } // SetName sets the Name field's value. func (s DataSource) SetName(v string) DataSource { s.Name = &v return s } // SetNumberOfFiles sets the NumberOfFiles field's value. func (s DataSource) SetNumberOfFiles(v int64) DataSource { s.NumberOfFiles = &v return s } // SetRDSMetadata sets the RDSMetadata field's value. func (s DataSource) SetRDSMetadata(v RDSMetadata) DataSource { s.RDSMetadata = v return s } // SetRedshiftMetadata sets the RedshiftMetadata field's value. func (s DataSource) SetRedshiftMetadata(v RedshiftMetadata) DataSource { s.RedshiftMetadata = v return s } // SetRoleARN sets the RoleARN field's value. func (s DataSource) SetRoleARN(v string) DataSource { s.RoleARN = &v return s } // SetStartedAt sets the StartedAt field's value. func (s DataSource) SetStartedAt(v time.Time) DataSource { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s DataSource) SetStatus(v string) DataSource { s.Status = &v return s } type DeleteBatchPredictionInput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the BatchPrediction. // // BatchPredictionId is a required field BatchPredictionId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteBatchPredictionInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteBatchPredictionInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DeleteBatchPredictionInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DeleteBatchPredictionInput"} if s.BatchPredictionId == nil { invalidParams.Add(request.NewErrParamRequired("BatchPredictionId")) } if s.BatchPredictionId != nil && len(s.BatchPredictionId) < 1 { invalidParams.Add(request.NewErrParamMinLen("BatchPredictionId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s DeleteBatchPredictionInput) SetBatchPredictionId(v string) DeleteBatchPredictionInput { s.BatchPredictionId = &v return s } // Represents the output of a DeleteBatchPrediction operation. // // You can use the GetBatchPrediction operation and check the value of the Status // parameter to see whether a BatchPrediction is marked as DELETED. type DeleteBatchPredictionOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the BatchPrediction. This value // should be identical to the value of the BatchPredictionID in the request. BatchPredictionId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteBatchPredictionOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteBatchPredictionOutput) GoString() string { return s.String() } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s DeleteBatchPredictionOutput) SetBatchPredictionId(v string) DeleteBatchPredictionOutput { s.BatchPredictionId = &v return s } type DeleteDataSourceInput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the DataSource. // // DataSourceId is a required field DataSourceId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteDataSourceInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteDataSourceInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DeleteDataSourceInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DeleteDataSourceInput"} if s.DataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceId")) } if s.DataSourceId != nil && len(s.DataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("DataSourceId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDataSourceId sets the DataSourceId field's value. func (s DeleteDataSourceInput) SetDataSourceId(v string) DeleteDataSourceInput { s.DataSourceId = &v return s } // Represents the output of a DeleteDataSource operation. type DeleteDataSourceOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the DataSource. This value should // be identical to the value of the DataSourceID in the request. DataSourceId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteDataSourceOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteDataSourceOutput) GoString() string { return s.String() } // SetDataSourceId sets the DataSourceId field's value. func (s DeleteDataSourceOutput) SetDataSourceId(v string) DeleteDataSourceOutput { s.DataSourceId = &v return s } type DeleteEvaluationInput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the Evaluation to delete. // // EvaluationId is a required field EvaluationId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteEvaluationInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteEvaluationInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DeleteEvaluationInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DeleteEvaluationInput"} if s.EvaluationId == nil { invalidParams.Add(request.NewErrParamRequired("EvaluationId")) } if s.EvaluationId != nil && len(s.EvaluationId) < 1 { invalidParams.Add(request.NewErrParamMinLen("EvaluationId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEvaluationId sets the EvaluationId field's value. func (s DeleteEvaluationInput) SetEvaluationId(v string) DeleteEvaluationInput { s.EvaluationId = &v return s } // Represents the output of a DeleteEvaluation operation. The output indicates // that Amazon Machine Learning (Amazon ML) received the request. // // You can use the GetEvaluation operation and check the value of the Status // parameter to see whether an Evaluation is marked as DELETED. type DeleteEvaluationOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the Evaluation. This value should // be identical to the value of the EvaluationId in the request. EvaluationId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteEvaluationOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteEvaluationOutput) GoString() string { return s.String() } // SetEvaluationId sets the EvaluationId field's value. func (s DeleteEvaluationOutput) SetEvaluationId(v string) DeleteEvaluationOutput { s.EvaluationId = &v return s } type DeleteMLModelInput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the MLModel. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteMLModelInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteMLModelInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DeleteMLModelInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DeleteMLModelInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s DeleteMLModelInput) SetMLModelId(v string) DeleteMLModelInput { s.MLModelId = &v return s } // Represents the output of a DeleteMLModel operation. // // You can use the GetMLModel operation and check the value of the Status parameter // to see whether an MLModel is marked as DELETED. type DeleteMLModelOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the MLModel. This value should // be identical to the value of the MLModelID in the request. MLModelId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteMLModelOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteMLModelOutput) GoString() string { return s.String() } // SetMLModelId sets the MLModelId field's value. func (s DeleteMLModelOutput) SetMLModelId(v string) DeleteMLModelOutput { s.MLModelId = &v return s } type DeleteRealtimeEndpointInput struct { _ struct{} `type:"structure"` // The ID assigned to the MLModel during creation. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteRealtimeEndpointInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteRealtimeEndpointInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DeleteRealtimeEndpointInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DeleteRealtimeEndpointInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s DeleteRealtimeEndpointInput) SetMLModelId(v string) DeleteRealtimeEndpointInput { s.MLModelId = &v return s } // Represents the output of an DeleteRealtimeEndpoint operation. // // The result contains the MLModelId and the endpoint information for the MLModel. type DeleteRealtimeEndpointOutput struct { _ struct{} `type:"structure"` // A user-supplied ID that uniquely identifies the MLModel. This value should // be identical to the value of the MLModelId in the request. MLModelId string `min:"1" type:"string"` // The endpoint information of the MLModel RealtimeEndpointInfo RealtimeEndpointInfo `type:"structure"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteRealtimeEndpointOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteRealtimeEndpointOutput) GoString() string { return s.String() } // SetMLModelId sets the MLModelId field's value. func (s DeleteRealtimeEndpointOutput) SetMLModelId(v string) DeleteRealtimeEndpointOutput { s.MLModelId = &v return s } // SetRealtimeEndpointInfo sets the RealtimeEndpointInfo field's value. func (s DeleteRealtimeEndpointOutput) SetRealtimeEndpointInfo(v RealtimeEndpointInfo) DeleteRealtimeEndpointOutput { s.RealtimeEndpointInfo = v return s } type DeleteTagsInput struct { _ struct{} `type:"structure"` // The ID of the tagged ML object. For example, exampleModelId. // // ResourceId is a required field ResourceId string `min:"1" type:"string" required:"true"` // The type of the tagged ML object. // // ResourceType is a required field ResourceType string `type:"string" required:"true" enum:"TaggableResourceType"` // One or more tags to delete. // // TagKeys is a required field TagKeys []string `type:"list" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteTagsInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteTagsInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DeleteTagsInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DeleteTagsInput"} if s.ResourceId == nil { invalidParams.Add(request.NewErrParamRequired("ResourceId")) } if s.ResourceId != nil && len(s.ResourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("ResourceId", 1)) } if s.ResourceType == nil { invalidParams.Add(request.NewErrParamRequired("ResourceType")) } if s.TagKeys == nil { invalidParams.Add(request.NewErrParamRequired("TagKeys")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetResourceId sets the ResourceId field's value. func (s DeleteTagsInput) SetResourceId(v string) DeleteTagsInput { s.ResourceId = &v return s } // SetResourceType sets the ResourceType field's value. func (s DeleteTagsInput) SetResourceType(v string) DeleteTagsInput { s.ResourceType = &v return s } // SetTagKeys sets the TagKeys field's value. func (s DeleteTagsInput) SetTagKeys(v []string) DeleteTagsInput { s.TagKeys = v return s } // Amazon ML returns the following elements. type DeleteTagsOutput struct { _ struct{} `type:"structure"` // The ID of the ML object from which tags were deleted. ResourceId string `min:"1" type:"string"` // The type of the ML object from which tags were deleted. ResourceType string `type:"string" enum:"TaggableResourceType"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteTagsOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DeleteTagsOutput) GoString() string { return s.String() } // SetResourceId sets the ResourceId field's value. func (s DeleteTagsOutput) SetResourceId(v string) DeleteTagsOutput { s.ResourceId = &v return s } // SetResourceType sets the ResourceType field's value. func (s DeleteTagsOutput) SetResourceType(v string) DeleteTagsOutput { s.ResourceType = &v return s } type DescribeBatchPredictionsInput struct { _ struct{} `type:"structure"` // The equal to operator. The BatchPrediction results will have FilterVariable // values that exactly match the value specified with EQ. EQ string `type:"string"` // Use one of the following variables to filter a list of BatchPrediction: // // * CreatedAt - Sets the search criteria to the BatchPrediction creation // date. // // * Status - Sets the search criteria to the BatchPrediction status. // // * Name - Sets the search criteria to the contents of the BatchPrediction // Name. // // * IAMUser - Sets the search criteria to the user account that invoked // the BatchPrediction creation. // // * MLModelId - Sets the search criteria to the MLModel used in the BatchPrediction. // // * DataSourceId - Sets the search criteria to the DataSource used in the // BatchPrediction. // // * DataURI - Sets the search criteria to the data file(s) used in the BatchPrediction. // The URL can identify either a file or an Amazon Simple Storage Solution // (Amazon S3) bucket or directory. FilterVariable string `type:"string" enum:"BatchPredictionFilterVariable"` // The greater than or equal to operator. The BatchPrediction results will have // FilterVariable values that are greater than or equal to the value specified // with GE. GE string `type:"string"` // The greater than operator. The BatchPrediction results will have FilterVariable // values that are greater than the value specified with GT. GT string `type:"string"` // The less than or equal to operator. The BatchPrediction results will have // FilterVariable values that are less than or equal to the value specified // with LE. LE string `type:"string"` // The less than operator. The BatchPrediction results will have FilterVariable // values that are less than the value specified with LT. LT string `type:"string"` // The number of pages of information to include in the result. The range of // acceptable values is 1 through 100. The default value is 100. Limit int64 `min:"1" type:"integer"` // The not equal to operator. The BatchPrediction results will have FilterVariable // values not equal to the value specified with NE. NE string `type:"string"` // An ID of the page in the paginated results. NextToken string `type:"string"` // A string that is found at the beginning of a variable, such as Name or Id. // // For example, a Batch Prediction operation could have the Name 2014-09-09-HolidayGiftMailer. // To search for this BatchPrediction, select Name for the FilterVariable and // any of the following strings for the Prefix: // // * 2014-09 // // * 2014-09-09 // // * 2014-09-09-Holiday Prefix string `type:"string"` // A two-value parameter that determines the sequence of the resulting list // of MLModels. // // asc - Arranges the list in ascending order (A-Z, 0-9). // // * dsc - Arranges the list in descending order (Z-A, 9-0). // // Results are sorted by FilterVariable. SortOrder string `type:"string" enum:"SortOrder"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeBatchPredictionsInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeBatchPredictionsInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DescribeBatchPredictionsInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DescribeBatchPredictionsInput"} if s.Limit != nil && s.Limit < 1 { invalidParams.Add(request.NewErrParamMinValue("Limit", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEQ sets the EQ field's value. func (s DescribeBatchPredictionsInput) SetEQ(v string) DescribeBatchPredictionsInput { s.EQ = &v return s } // SetFilterVariable sets the FilterVariable field's value. func (s DescribeBatchPredictionsInput) SetFilterVariable(v string) DescribeBatchPredictionsInput { s.FilterVariable = &v return s } // SetGE sets the GE field's value. func (s DescribeBatchPredictionsInput) SetGE(v string) DescribeBatchPredictionsInput { s.GE = &v return s } // SetGT sets the GT field's value. func (s DescribeBatchPredictionsInput) SetGT(v string) DescribeBatchPredictionsInput { s.GT = &v return s } // SetLE sets the LE field's value. func (s DescribeBatchPredictionsInput) SetLE(v string) DescribeBatchPredictionsInput { s.LE = &v return s } // SetLT sets the LT field's value. func (s DescribeBatchPredictionsInput) SetLT(v string) DescribeBatchPredictionsInput { s.LT = &v return s } // SetLimit sets the Limit field's value. func (s DescribeBatchPredictionsInput) SetLimit(v int64) DescribeBatchPredictionsInput { s.Limit = &v return s } // SetNE sets the NE field's value. func (s DescribeBatchPredictionsInput) SetNE(v string) DescribeBatchPredictionsInput { s.NE = &v return s } // SetNextToken sets the NextToken field's value. func (s DescribeBatchPredictionsInput) SetNextToken(v string) DescribeBatchPredictionsInput { s.NextToken = &v return s } // SetPrefix sets the Prefix field's value. func (s DescribeBatchPredictionsInput) SetPrefix(v string) DescribeBatchPredictionsInput { s.Prefix = &v return s } // SetSortOrder sets the SortOrder field's value. func (s DescribeBatchPredictionsInput) SetSortOrder(v string) DescribeBatchPredictionsInput { s.SortOrder = &v return s } // Represents the output of a DescribeBatchPredictions operation. The content // is essentially a list of BatchPredictions. type DescribeBatchPredictionsOutput struct { _ struct{} `type:"structure"` // The ID of the next page in the paginated results that indicates at least // one more page follows. NextToken string `type:"string"` // A list of BatchPrediction objects that meet the search criteria. Results []BatchPrediction `type:"list"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeBatchPredictionsOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeBatchPredictionsOutput) GoString() string { return s.String() } // SetNextToken sets the NextToken field's value. func (s DescribeBatchPredictionsOutput) SetNextToken(v string) DescribeBatchPredictionsOutput { s.NextToken = &v return s } // SetResults sets the Results field's value. func (s DescribeBatchPredictionsOutput) SetResults(v []BatchPrediction) DescribeBatchPredictionsOutput { s.Results = v return s } type DescribeDataSourcesInput struct { _ struct{} `type:"structure"` // The equal to operator. The DataSource results will have FilterVariable values // that exactly match the value specified with EQ. EQ string `type:"string"` // Use one of the following variables to filter a list of DataSource: // // CreatedAt - Sets the search criteria to DataSource creation dates. // // * Status - Sets the search criteria to DataSource statuses. // // * Name - Sets the search criteria to the contents of DataSource Name. // // * DataUri - Sets the search criteria to the URI of data files used to // create the DataSource. The URI can identify either a file or an Amazon // Simple Storage Service (Amazon S3) bucket or directory. // // * IAMUser - Sets the search criteria to the user account that invoked // the DataSource creation. FilterVariable string `type:"string" enum:"DataSourceFilterVariable"` // The greater than or equal to operator. The DataSource results will have FilterVariable // values that are greater than or equal to the value specified with GE. GE string `type:"string"` // The greater than operator. The DataSource results will have FilterVariable // values that are greater than the value specified with GT. GT string `type:"string"` // The less than or equal to operator. The DataSource results will have FilterVariable // values that are less than or equal to the value specified with LE. LE string `type:"string"` // The less than operator. The DataSource results will have FilterVariable values // that are less than the value specified with LT. LT string `type:"string"` // The maximum number of DataSource to include in the result. Limit int64 `min:"1" type:"integer"` // The not equal to operator. The DataSource results will have FilterVariable // values not equal to the value specified with NE. NE string `type:"string"` // The ID of the page in the paginated results. NextToken string `type:"string"` // A string that is found at the beginning of a variable, such as Name or Id. // // For example, a DataSource could have the Name 2014-09-09-HolidayGiftMailer. // To search for this DataSource, select Name for the FilterVariable and any // of the following strings for the Prefix: // // * 2014-09 // // * 2014-09-09 // // * 2014-09-09-Holiday Prefix string `type:"string"` // A two-value parameter that determines the sequence of the resulting list // of DataSource. // // asc - Arranges the list in ascending order (A-Z, 0-9). // // * dsc - Arranges the list in descending order (Z-A, 9-0). // // Results are sorted by FilterVariable. SortOrder string `type:"string" enum:"SortOrder"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeDataSourcesInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeDataSourcesInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DescribeDataSourcesInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DescribeDataSourcesInput"} if s.Limit != nil && s.Limit < 1 { invalidParams.Add(request.NewErrParamMinValue("Limit", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEQ sets the EQ field's value. func (s DescribeDataSourcesInput) SetEQ(v string) DescribeDataSourcesInput { s.EQ = &v return s } // SetFilterVariable sets the FilterVariable field's value. func (s DescribeDataSourcesInput) SetFilterVariable(v string) DescribeDataSourcesInput { s.FilterVariable = &v return s } // SetGE sets the GE field's value. func (s DescribeDataSourcesInput) SetGE(v string) DescribeDataSourcesInput { s.GE = &v return s } // SetGT sets the GT field's value. func (s DescribeDataSourcesInput) SetGT(v string) DescribeDataSourcesInput { s.GT = &v return s } // SetLE sets the LE field's value. func (s DescribeDataSourcesInput) SetLE(v string) DescribeDataSourcesInput { s.LE = &v return s } // SetLT sets the LT field's value. func (s DescribeDataSourcesInput) SetLT(v string) DescribeDataSourcesInput { s.LT = &v return s } // SetLimit sets the Limit field's value. func (s DescribeDataSourcesInput) SetLimit(v int64) DescribeDataSourcesInput { s.Limit = &v return s } // SetNE sets the NE field's value. func (s DescribeDataSourcesInput) SetNE(v string) DescribeDataSourcesInput { s.NE = &v return s } // SetNextToken sets the NextToken field's value. func (s DescribeDataSourcesInput) SetNextToken(v string) DescribeDataSourcesInput { s.NextToken = &v return s } // SetPrefix sets the Prefix field's value. func (s DescribeDataSourcesInput) SetPrefix(v string) DescribeDataSourcesInput { s.Prefix = &v return s } // SetSortOrder sets the SortOrder field's value. func (s DescribeDataSourcesInput) SetSortOrder(v string) DescribeDataSourcesInput { s.SortOrder = &v return s } // Represents the query results from a DescribeDataSources operation. The content // is essentially a list of DataSource. type DescribeDataSourcesOutput struct { _ struct{} `type:"structure"` // An ID of the next page in the paginated results that indicates at least one // more page follows. NextToken string `type:"string"` // A list of DataSource that meet the search criteria. Results []DataSource `type:"list"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeDataSourcesOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeDataSourcesOutput) GoString() string { return s.String() } // SetNextToken sets the NextToken field's value. func (s DescribeDataSourcesOutput) SetNextToken(v string) DescribeDataSourcesOutput { s.NextToken = &v return s } // SetResults sets the Results field's value. func (s DescribeDataSourcesOutput) SetResults(v []DataSource) DescribeDataSourcesOutput { s.Results = v return s } type DescribeEvaluationsInput struct { _ struct{} `type:"structure"` // The equal to operator. The Evaluation results will have FilterVariable values // that exactly match the value specified with EQ. EQ string `type:"string"` // Use one of the following variable to filter a list of Evaluation objects: // // CreatedAt - Sets the search criteria to the Evaluation creation date. // // * Status - Sets the search criteria to the Evaluation status. // // * Name - Sets the search criteria to the contents of Evaluation Name. // // * IAMUser - Sets the search criteria to the user account that invoked // an Evaluation. // // * MLModelId - Sets the search criteria to the MLModel that was evaluated. // // * DataSourceId - Sets the search criteria to the DataSource used in Evaluation. // // * DataUri - Sets the search criteria to the data file(s) used in Evaluation. // The URL can identify either a file or an Amazon Simple Storage Solution // (Amazon S3) bucket or directory. FilterVariable string `type:"string" enum:"EvaluationFilterVariable"` // The greater than or equal to operator. The Evaluation results will have FilterVariable // values that are greater than or equal to the value specified with GE. GE string `type:"string"` // The greater than operator. The Evaluation results will have FilterVariable // values that are greater than the value specified with GT. GT string `type:"string"` // The less than or equal to operator. The Evaluation results will have FilterVariable // values that are less than or equal to the value specified with LE. LE string `type:"string"` // The less than operator. The Evaluation results will have FilterVariable values // that are less than the value specified with LT. LT string `type:"string"` // The maximum number of Evaluation to include in the result. Limit int64 `min:"1" type:"integer"` // The not equal to operator. The Evaluation results will have FilterVariable // values not equal to the value specified with NE. NE string `type:"string"` // The ID of the page in the paginated results. NextToken string `type:"string"` // A string that is found at the beginning of a variable, such as Name or Id. // // For example, an Evaluation could have the Name 2014-09-09-HolidayGiftMailer. // To search for this Evaluation, select Name for the FilterVariable and any // of the following strings for the Prefix: // // * 2014-09 // // * 2014-09-09 // // * 2014-09-09-Holiday Prefix string `type:"string"` // A two-value parameter that determines the sequence of the resulting list // of Evaluation. // // asc - Arranges the list in ascending order (A-Z, 0-9). // // * dsc - Arranges the list in descending order (Z-A, 9-0). // // Results are sorted by FilterVariable. SortOrder string `type:"string" enum:"SortOrder"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeEvaluationsInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeEvaluationsInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DescribeEvaluationsInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DescribeEvaluationsInput"} if s.Limit != nil && s.Limit < 1 { invalidParams.Add(request.NewErrParamMinValue("Limit", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEQ sets the EQ field's value. func (s DescribeEvaluationsInput) SetEQ(v string) DescribeEvaluationsInput { s.EQ = &v return s } // SetFilterVariable sets the FilterVariable field's value. func (s DescribeEvaluationsInput) SetFilterVariable(v string) DescribeEvaluationsInput { s.FilterVariable = &v return s } // SetGE sets the GE field's value. func (s DescribeEvaluationsInput) SetGE(v string) DescribeEvaluationsInput { s.GE = &v return s } // SetGT sets the GT field's value. func (s DescribeEvaluationsInput) SetGT(v string) DescribeEvaluationsInput { s.GT = &v return s } // SetLE sets the LE field's value. func (s DescribeEvaluationsInput) SetLE(v string) DescribeEvaluationsInput { s.LE = &v return s } // SetLT sets the LT field's value. func (s DescribeEvaluationsInput) SetLT(v string) DescribeEvaluationsInput { s.LT = &v return s } // SetLimit sets the Limit field's value. func (s DescribeEvaluationsInput) SetLimit(v int64) DescribeEvaluationsInput { s.Limit = &v return s } // SetNE sets the NE field's value. func (s DescribeEvaluationsInput) SetNE(v string) DescribeEvaluationsInput { s.NE = &v return s } // SetNextToken sets the NextToken field's value. func (s DescribeEvaluationsInput) SetNextToken(v string) DescribeEvaluationsInput { s.NextToken = &v return s } // SetPrefix sets the Prefix field's value. func (s DescribeEvaluationsInput) SetPrefix(v string) DescribeEvaluationsInput { s.Prefix = &v return s } // SetSortOrder sets the SortOrder field's value. func (s DescribeEvaluationsInput) SetSortOrder(v string) DescribeEvaluationsInput { s.SortOrder = &v return s } // Represents the query results from a DescribeEvaluations operation. The content // is essentially a list of Evaluation. type DescribeEvaluationsOutput struct { _ struct{} `type:"structure"` // The ID of the next page in the paginated results that indicates at least // one more page follows. NextToken string `type:"string"` // A list of Evaluation that meet the search criteria. Results []Evaluation `type:"list"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeEvaluationsOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeEvaluationsOutput) GoString() string { return s.String() } // SetNextToken sets the NextToken field's value. func (s DescribeEvaluationsOutput) SetNextToken(v string) DescribeEvaluationsOutput { s.NextToken = &v return s } // SetResults sets the Results field's value. func (s DescribeEvaluationsOutput) SetResults(v []Evaluation) DescribeEvaluationsOutput { s.Results = v return s } type DescribeMLModelsInput struct { _ struct{} `type:"structure"` // The equal to operator. The MLModel results will have FilterVariable values // that exactly match the value specified with EQ. EQ string `type:"string"` // Use one of the following variables to filter a list of MLModel: // // CreatedAt - Sets the search criteria to MLModel creation date. // // * Status - Sets the search criteria to MLModel status. // // * Name - Sets the search criteria to the contents of MLModel Name. // // * IAMUser - Sets the search criteria to the user account that invoked // the MLModel creation. // // * TrainingDataSourceId - Sets the search criteria to the DataSource used // to train one or more MLModel. // // * RealtimeEndpointStatus - Sets the search criteria to the MLModel real-time // endpoint status. // // * MLModelType - Sets the search criteria to MLModel type: binary, regression, // or multi-class. // // * Algorithm - Sets the search criteria to the algorithm that the MLModel // uses. // // * TrainingDataURI - Sets the search criteria to the data file(s) used // in training a MLModel. The URL can identify either a file or an Amazon // Simple Storage Service (Amazon S3) bucket or directory. FilterVariable string `type:"string" enum:"MLModelFilterVariable"` // The greater than or equal to operator. The MLModel results will have FilterVariable // values that are greater than or equal to the value specified with GE. GE string `type:"string"` // The greater than operator. The MLModel results will have FilterVariable values // that are greater than the value specified with GT. GT string `type:"string"` // The less than or equal to operator. The MLModel results will have FilterVariable // values that are less than or equal to the value specified with LE. LE string `type:"string"` // The less than operator. The MLModel results will have FilterVariable values // that are less than the value specified with LT. LT string `type:"string"` // The number of pages of information to include in the result. The range of // acceptable values is 1 through 100. The default value is 100. Limit int64 `min:"1" type:"integer"` // The not equal to operator. The MLModel results will have FilterVariable values // not equal to the value specified with NE. NE string `type:"string"` // The ID of the page in the paginated results. NextToken string `type:"string"` // A string that is found at the beginning of a variable, such as Name or Id. // // For example, an MLModel could have the Name 2014-09-09-HolidayGiftMailer. // To search for this MLModel, select Name for the FilterVariable and any of // the following strings for the Prefix: // // * 2014-09 // // * 2014-09-09 // // * 2014-09-09-Holiday Prefix string `type:"string"` // A two-value parameter that determines the sequence of the resulting list // of MLModel. // // asc - Arranges the list in ascending order (A-Z, 0-9). // // * dsc - Arranges the list in descending order (Z-A, 9-0). // // Results are sorted by FilterVariable. SortOrder string `type:"string" enum:"SortOrder"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeMLModelsInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeMLModelsInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DescribeMLModelsInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DescribeMLModelsInput"} if s.Limit != nil && s.Limit < 1 { invalidParams.Add(request.NewErrParamMinValue("Limit", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEQ sets the EQ field's value. func (s DescribeMLModelsInput) SetEQ(v string) DescribeMLModelsInput { s.EQ = &v return s } // SetFilterVariable sets the FilterVariable field's value. func (s DescribeMLModelsInput) SetFilterVariable(v string) DescribeMLModelsInput { s.FilterVariable = &v return s } // SetGE sets the GE field's value. func (s DescribeMLModelsInput) SetGE(v string) DescribeMLModelsInput { s.GE = &v return s } // SetGT sets the GT field's value. func (s DescribeMLModelsInput) SetGT(v string) DescribeMLModelsInput { s.GT = &v return s } // SetLE sets the LE field's value. func (s DescribeMLModelsInput) SetLE(v string) DescribeMLModelsInput { s.LE = &v return s } // SetLT sets the LT field's value. func (s DescribeMLModelsInput) SetLT(v string) DescribeMLModelsInput { s.LT = &v return s } // SetLimit sets the Limit field's value. func (s DescribeMLModelsInput) SetLimit(v int64) DescribeMLModelsInput { s.Limit = &v return s } // SetNE sets the NE field's value. func (s DescribeMLModelsInput) SetNE(v string) DescribeMLModelsInput { s.NE = &v return s } // SetNextToken sets the NextToken field's value. func (s DescribeMLModelsInput) SetNextToken(v string) DescribeMLModelsInput { s.NextToken = &v return s } // SetPrefix sets the Prefix field's value. func (s DescribeMLModelsInput) SetPrefix(v string) DescribeMLModelsInput { s.Prefix = &v return s } // SetSortOrder sets the SortOrder field's value. func (s DescribeMLModelsInput) SetSortOrder(v string) DescribeMLModelsInput { s.SortOrder = &v return s } // Represents the output of a DescribeMLModels operation. The content is essentially // a list of MLModel. type DescribeMLModelsOutput struct { _ struct{} `type:"structure"` // The ID of the next page in the paginated results that indicates at least // one more page follows. NextToken string `type:"string"` // A list of MLModel that meet the search criteria. Results []MLModel `type:"list"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeMLModelsOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeMLModelsOutput) GoString() string { return s.String() } // SetNextToken sets the NextToken field's value. func (s DescribeMLModelsOutput) SetNextToken(v string) DescribeMLModelsOutput { s.NextToken = &v return s } // SetResults sets the Results field's value. func (s DescribeMLModelsOutput) SetResults(v []MLModel) DescribeMLModelsOutput { s.Results = v return s } type DescribeTagsInput struct { _ struct{} `type:"structure"` // The ID of the ML object. For example, exampleModelId. // // ResourceId is a required field ResourceId string `min:"1" type:"string" required:"true"` // The type of the ML object. // // ResourceType is a required field ResourceType string `type:"string" required:"true" enum:"TaggableResourceType"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeTagsInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeTagsInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s DescribeTagsInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "DescribeTagsInput"} if s.ResourceId == nil { invalidParams.Add(request.NewErrParamRequired("ResourceId")) } if s.ResourceId != nil && len(s.ResourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("ResourceId", 1)) } if s.ResourceType == nil { invalidParams.Add(request.NewErrParamRequired("ResourceType")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetResourceId sets the ResourceId field's value. func (s DescribeTagsInput) SetResourceId(v string) DescribeTagsInput { s.ResourceId = &v return s } // SetResourceType sets the ResourceType field's value. func (s DescribeTagsInput) SetResourceType(v string) DescribeTagsInput { s.ResourceType = &v return s } // Amazon ML returns the following elements. type DescribeTagsOutput struct { _ struct{} `type:"structure"` // The ID of the tagged ML object. ResourceId string `min:"1" type:"string"` // The type of the tagged ML object. ResourceType string `type:"string" enum:"TaggableResourceType"` // A list of tags associated with the ML object. Tags []Tag `type:"list"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeTagsOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s DescribeTagsOutput) GoString() string { return s.String() } // SetResourceId sets the ResourceId field's value. func (s DescribeTagsOutput) SetResourceId(v string) DescribeTagsOutput { s.ResourceId = &v return s } // SetResourceType sets the ResourceType field's value. func (s DescribeTagsOutput) SetResourceType(v string) DescribeTagsOutput { s.ResourceType = &v return s } // SetTags sets the Tags field's value. func (s DescribeTagsOutput) SetTags(v []Tag) DescribeTagsOutput { s.Tags = v return s } // Represents the output of GetEvaluation operation. // // The content consists of the detailed metadata and data file information and // the current status of the Evaluation. type Evaluation struct { _ struct{} `type:"structure"` // Long integer type that is a 64-bit signed number. ComputeTime int64 `type:"long"` // The time that the Evaluation was created. The time is expressed in epoch // time. CreatedAt time.Time `type:"timestamp"` // The AWS user account that invoked the evaluation. The account type can be // either an AWS root account or an AWS Identity and Access Management (IAM) // user account. CreatedByIamUser string `type:"string"` // The ID of the DataSource that is used to evaluate the MLModel. EvaluationDataSourceId string `min:"1" type:"string"` // The ID that is assigned to the Evaluation at creation. EvaluationId string `min:"1" type:"string"` // A timestamp represented in epoch time. FinishedAt time.Time `type:"timestamp"` // The location and name of the data in Amazon Simple Storage Server (Amazon // S3) that is used in the evaluation. InputDataLocationS3 string `type:"string"` // The time of the most recent edit to the Evaluation. The time is expressed // in epoch time. LastUpdatedAt time.Time `type:"timestamp"` // The ID of the MLModel that is the focus of the evaluation. MLModelId string `min:"1" type:"string"` // A description of the most recent details about evaluating the MLModel. Message string `type:"string"` // A user-supplied name or description of the Evaluation. Name string `type:"string"` // Measurements of how well the MLModel performed, using observations referenced // by the DataSource. One of the following metrics is returned, based on the // type of the MLModel: // // BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique // to measure performance. // // * RegressionRMSE: A regression MLModel uses the Root Mean Square Error // (RMSE) technique to measure performance. RMSE measures the difference // between predicted and actual values for a single variable. // // * MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique // to measure performance. // // For more information about performance metrics, please see the Amazon Machine // Learning Developer Guide (https://docs.aws.amazon.com/machine-learning/latest/dg). PerformanceMetrics PerformanceMetrics `type:"structure"` // A timestamp represented in epoch time. StartedAt time.Time `type:"timestamp"` // The status of the evaluation. This element can have one of the following // values: // // * PENDING - Amazon Machine Learning (Amazon ML) submitted a request to // evaluate an MLModel. // // * INPROGRESS - The evaluation is underway. // // * FAILED - The request to evaluate an MLModel did not run to completion. // It is not usable. // // * COMPLETED - The evaluation process completed successfully. // // * DELETED - The Evaluation is marked as deleted. It is not usable. Status string `type:"string" enum:"EntityStatus"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s Evaluation) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s Evaluation) GoString() string { return s.String() } // SetComputeTime sets the ComputeTime field's value. func (s Evaluation) SetComputeTime(v int64) Evaluation { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s Evaluation) SetCreatedAt(v time.Time) Evaluation { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s Evaluation) SetCreatedByIamUser(v string) Evaluation { s.CreatedByIamUser = &v return s } // SetEvaluationDataSourceId sets the EvaluationDataSourceId field's value. func (s Evaluation) SetEvaluationDataSourceId(v string) Evaluation { s.EvaluationDataSourceId = &v return s } // SetEvaluationId sets the EvaluationId field's value. func (s Evaluation) SetEvaluationId(v string) Evaluation { s.EvaluationId = &v return s } // SetFinishedAt sets the FinishedAt field's value. func (s Evaluation) SetFinishedAt(v time.Time) Evaluation { s.FinishedAt = &v return s } // SetInputDataLocationS3 sets the InputDataLocationS3 field's value. func (s Evaluation) SetInputDataLocationS3(v string) Evaluation { s.InputDataLocationS3 = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s Evaluation) SetLastUpdatedAt(v time.Time) Evaluation { s.LastUpdatedAt = &v return s } // SetMLModelId sets the MLModelId field's value. func (s Evaluation) SetMLModelId(v string) Evaluation { s.MLModelId = &v return s } // SetMessage sets the Message field's value. func (s Evaluation) SetMessage(v string) Evaluation { s.Message = &v return s } // SetName sets the Name field's value. func (s Evaluation) SetName(v string) Evaluation { s.Name = &v return s } // SetPerformanceMetrics sets the PerformanceMetrics field's value. func (s Evaluation) SetPerformanceMetrics(v PerformanceMetrics) Evaluation { s.PerformanceMetrics = v return s } // SetStartedAt sets the StartedAt field's value. func (s Evaluation) SetStartedAt(v time.Time) Evaluation { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s Evaluation) SetStatus(v string) Evaluation { s.Status = &v return s } type GetBatchPredictionInput struct { _ struct{} `type:"structure"` // An ID assigned to the BatchPrediction at creation. // // BatchPredictionId is a required field BatchPredictionId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetBatchPredictionInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetBatchPredictionInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s GetBatchPredictionInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "GetBatchPredictionInput"} if s.BatchPredictionId == nil { invalidParams.Add(request.NewErrParamRequired("BatchPredictionId")) } if s.BatchPredictionId != nil && len(s.BatchPredictionId) < 1 { invalidParams.Add(request.NewErrParamMinLen("BatchPredictionId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s GetBatchPredictionInput) SetBatchPredictionId(v string) GetBatchPredictionInput { s.BatchPredictionId = &v return s } // Represents the output of a GetBatchPrediction operation and describes a BatchPrediction. type GetBatchPredictionOutput struct { _ struct{} `type:"structure"` // The ID of the DataSource that was used to create the BatchPrediction. BatchPredictionDataSourceId string `min:"1" type:"string"` // An ID assigned to the BatchPrediction at creation. This value should be identical // to the value of the BatchPredictionID in the request. BatchPredictionId string `min:"1" type:"string"` // The approximate CPU time in milliseconds that Amazon Machine Learning spent // processing the BatchPrediction, normalized and scaled on computation resources. // ComputeTime is only available if the BatchPrediction is in the COMPLETED // state. ComputeTime int64 `type:"long"` // The time when the BatchPrediction was created. The time is expressed in epoch // time. CreatedAt time.Time `type:"timestamp"` // The AWS user account that invoked the BatchPrediction. The account type can // be either an AWS root account or an AWS Identity and Access Management (IAM) // user account. CreatedByIamUser string `type:"string"` // The epoch time when Amazon Machine Learning marked the BatchPrediction as // COMPLETED or FAILED. FinishedAt is only available when the BatchPrediction // is in the COMPLETED or FAILED state. FinishedAt time.Time `type:"timestamp"` // The location of the data file or directory in Amazon Simple Storage Service // (Amazon S3). InputDataLocationS3 string `type:"string"` // The number of invalid records that Amazon Machine Learning saw while processing // the BatchPrediction. InvalidRecordCount int64 `type:"long"` // The time of the most recent edit to BatchPrediction. The time is expressed // in epoch time. LastUpdatedAt time.Time `type:"timestamp"` // A link to the file that contains logs of the CreateBatchPrediction operation. LogUri string `type:"string"` // The ID of the MLModel that generated predictions for the BatchPrediction // request. MLModelId string `min:"1" type:"string"` // A description of the most recent details about processing the batch prediction // request. Message string `type:"string"` // A user-supplied name or description of the BatchPrediction. Name string `type:"string"` // The location of an Amazon S3 bucket or directory to receive the operation // results. OutputUri string `type:"string"` // The epoch time when Amazon Machine Learning marked the BatchPrediction as // INPROGRESS. StartedAt isn't available if the BatchPrediction is in the PENDING // state. StartedAt time.Time `type:"timestamp"` // The status of the BatchPrediction, which can be one of the following values: // // * PENDING - Amazon Machine Learning (Amazon ML) submitted a request to // generate batch predictions. // // * INPROGRESS - The batch predictions are in progress. // // * FAILED - The request to perform a batch prediction did not run to completion. // It is not usable. // // * COMPLETED - The batch prediction process completed successfully. // // * DELETED - The BatchPrediction is marked as deleted. It is not usable. Status string `type:"string" enum:"EntityStatus"` // The number of total records that Amazon Machine Learning saw while processing // the BatchPrediction. TotalRecordCount int64 `type:"long"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetBatchPredictionOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetBatchPredictionOutput) GoString() string { return s.String() } // SetBatchPredictionDataSourceId sets the BatchPredictionDataSourceId field's value. func (s GetBatchPredictionOutput) SetBatchPredictionDataSourceId(v string) GetBatchPredictionOutput { s.BatchPredictionDataSourceId = &v return s } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s GetBatchPredictionOutput) SetBatchPredictionId(v string) GetBatchPredictionOutput { s.BatchPredictionId = &v return s } // SetComputeTime sets the ComputeTime field's value. func (s GetBatchPredictionOutput) SetComputeTime(v int64) GetBatchPredictionOutput { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s GetBatchPredictionOutput) SetCreatedAt(v time.Time) GetBatchPredictionOutput { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s GetBatchPredictionOutput) SetCreatedByIamUser(v string) GetBatchPredictionOutput { s.CreatedByIamUser = &v return s } // SetFinishedAt sets the FinishedAt field's value. func (s GetBatchPredictionOutput) SetFinishedAt(v time.Time) GetBatchPredictionOutput { s.FinishedAt = &v return s } // SetInputDataLocationS3 sets the InputDataLocationS3 field's value. func (s GetBatchPredictionOutput) SetInputDataLocationS3(v string) GetBatchPredictionOutput { s.InputDataLocationS3 = &v return s } // SetInvalidRecordCount sets the InvalidRecordCount field's value. func (s GetBatchPredictionOutput) SetInvalidRecordCount(v int64) GetBatchPredictionOutput { s.InvalidRecordCount = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s GetBatchPredictionOutput) SetLastUpdatedAt(v time.Time) GetBatchPredictionOutput { s.LastUpdatedAt = &v return s } // SetLogUri sets the LogUri field's value. func (s GetBatchPredictionOutput) SetLogUri(v string) GetBatchPredictionOutput { s.LogUri = &v return s } // SetMLModelId sets the MLModelId field's value. func (s GetBatchPredictionOutput) SetMLModelId(v string) GetBatchPredictionOutput { s.MLModelId = &v return s } // SetMessage sets the Message field's value. func (s GetBatchPredictionOutput) SetMessage(v string) GetBatchPredictionOutput { s.Message = &v return s } // SetName sets the Name field's value. func (s GetBatchPredictionOutput) SetName(v string) GetBatchPredictionOutput { s.Name = &v return s } // SetOutputUri sets the OutputUri field's value. func (s GetBatchPredictionOutput) SetOutputUri(v string) GetBatchPredictionOutput { s.OutputUri = &v return s } // SetStartedAt sets the StartedAt field's value. func (s GetBatchPredictionOutput) SetStartedAt(v time.Time) GetBatchPredictionOutput { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s GetBatchPredictionOutput) SetStatus(v string) GetBatchPredictionOutput { s.Status = &v return s } // SetTotalRecordCount sets the TotalRecordCount field's value. func (s GetBatchPredictionOutput) SetTotalRecordCount(v int64) GetBatchPredictionOutput { s.TotalRecordCount = &v return s } type GetDataSourceInput struct { _ struct{} `type:"structure"` // The ID assigned to the DataSource at creation. // // DataSourceId is a required field DataSourceId string `min:"1" type:"string" required:"true"` // Specifies whether the GetDataSource operation should return DataSourceSchema. // // If true, DataSourceSchema is returned. // // If false, DataSourceSchema is not returned. Verbose bool `type:"boolean"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetDataSourceInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetDataSourceInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s GetDataSourceInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "GetDataSourceInput"} if s.DataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceId")) } if s.DataSourceId != nil && len(s.DataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("DataSourceId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDataSourceId sets the DataSourceId field's value. func (s GetDataSourceInput) SetDataSourceId(v string) GetDataSourceInput { s.DataSourceId = &v return s } // SetVerbose sets the Verbose field's value. func (s GetDataSourceInput) SetVerbose(v bool) GetDataSourceInput { s.Verbose = &v return s } // Represents the output of a GetDataSource operation and describes a DataSource. type GetDataSourceOutput struct { _ struct{} `type:"structure"` // The parameter is true if statistics need to be generated from the observation // data. ComputeStatistics bool `type:"boolean"` // The approximate CPU time in milliseconds that Amazon Machine Learning spent // processing the DataSource, normalized and scaled on computation resources. // ComputeTime is only available if the DataSource is in the COMPLETED state // and the ComputeStatistics is set to true. ComputeTime int64 `type:"long"` // The time that the DataSource was created. The time is expressed in epoch // time. CreatedAt time.Time `type:"timestamp"` // The AWS user account from which the DataSource was created. The account type // can be either an AWS root account or an AWS Identity and Access Management // (IAM) user account. CreatedByIamUser string `type:"string"` // The location of the data file or directory in Amazon Simple Storage Service // (Amazon S3). DataLocationS3 string `type:"string"` // A JSON string that represents the splitting and rearrangement requirement // used when this DataSource was created. DataRearrangement string `type:"string"` // The total size of observations in the data files. DataSizeInBytes int64 `type:"long"` // The ID assigned to the DataSource at creation. This value should be identical // to the value of the DataSourceId in the request. DataSourceId string `min:"1" type:"string"` // The schema used by all of the data files of this DataSource. // // Note: This parameter is provided as part of the verbose format. DataSourceSchema string `type:"string"` // The epoch time when Amazon Machine Learning marked the DataSource as COMPLETED // or FAILED. FinishedAt is only available when the DataSource is in the COMPLETED // or FAILED state. FinishedAt time.Time `type:"timestamp"` // The time of the most recent edit to the DataSource. The time is expressed // in epoch time. LastUpdatedAt time.Time `type:"timestamp"` // A link to the file containing logs of CreateDataSourceFrom operations. LogUri string `type:"string"` // The user-supplied description of the most recent details about creating the // DataSource. Message string `type:"string"` // A user-supplied name or description of the DataSource. Name string `type:"string"` // The number of data files referenced by the DataSource. NumberOfFiles int64 `type:"long"` // The datasource details that are specific to Amazon RDS. RDSMetadata RDSMetadata `type:"structure"` // Describes the DataSource details specific to Amazon Redshift. RedshiftMetadata RedshiftMetadata `type:"structure"` // The Amazon Resource Name (ARN) of an AWS IAM Role (https://docs.aws.amazon.com/IAM/latest/UserGuide/roles-toplevel.html#roles-about-termsandconcepts), // such as the following: arn:aws:iam::account:role/rolename. RoleARN string `min:"1" type:"string"` // The epoch time when Amazon Machine Learning marked the DataSource as INPROGRESS. // StartedAt isn't available if the DataSource is in the PENDING state. StartedAt time.Time `type:"timestamp"` // The current status of the DataSource. This element can have one of the following // values: // // * PENDING - Amazon ML submitted a request to create a DataSource. // // * INPROGRESS - The creation process is underway. // // * FAILED - The request to create a DataSource did not run to completion. // It is not usable. // // * COMPLETED - The creation process completed successfully. // // * DELETED - The DataSource is marked as deleted. It is not usable. Status string `type:"string" enum:"EntityStatus"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetDataSourceOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetDataSourceOutput) GoString() string { return s.String() } // SetComputeStatistics sets the ComputeStatistics field's value. func (s GetDataSourceOutput) SetComputeStatistics(v bool) GetDataSourceOutput { s.ComputeStatistics = &v return s } // SetComputeTime sets the ComputeTime field's value. func (s GetDataSourceOutput) SetComputeTime(v int64) GetDataSourceOutput { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s GetDataSourceOutput) SetCreatedAt(v time.Time) GetDataSourceOutput { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s GetDataSourceOutput) SetCreatedByIamUser(v string) GetDataSourceOutput { s.CreatedByIamUser = &v return s } // SetDataLocationS3 sets the DataLocationS3 field's value. func (s GetDataSourceOutput) SetDataLocationS3(v string) GetDataSourceOutput { s.DataLocationS3 = &v return s } // SetDataRearrangement sets the DataRearrangement field's value. func (s GetDataSourceOutput) SetDataRearrangement(v string) GetDataSourceOutput { s.DataRearrangement = &v return s } // SetDataSizeInBytes sets the DataSizeInBytes field's value. func (s GetDataSourceOutput) SetDataSizeInBytes(v int64) GetDataSourceOutput { s.DataSizeInBytes = &v return s } // SetDataSourceId sets the DataSourceId field's value. func (s GetDataSourceOutput) SetDataSourceId(v string) GetDataSourceOutput { s.DataSourceId = &v return s } // SetDataSourceSchema sets the DataSourceSchema field's value. func (s GetDataSourceOutput) SetDataSourceSchema(v string) GetDataSourceOutput { s.DataSourceSchema = &v return s } // SetFinishedAt sets the FinishedAt field's value. func (s GetDataSourceOutput) SetFinishedAt(v time.Time) GetDataSourceOutput { s.FinishedAt = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s GetDataSourceOutput) SetLastUpdatedAt(v time.Time) GetDataSourceOutput { s.LastUpdatedAt = &v return s } // SetLogUri sets the LogUri field's value. func (s GetDataSourceOutput) SetLogUri(v string) GetDataSourceOutput { s.LogUri = &v return s } // SetMessage sets the Message field's value. func (s GetDataSourceOutput) SetMessage(v string) GetDataSourceOutput { s.Message = &v return s } // SetName sets the Name field's value. func (s GetDataSourceOutput) SetName(v string) GetDataSourceOutput { s.Name = &v return s } // SetNumberOfFiles sets the NumberOfFiles field's value. func (s GetDataSourceOutput) SetNumberOfFiles(v int64) GetDataSourceOutput { s.NumberOfFiles = &v return s } // SetRDSMetadata sets the RDSMetadata field's value. func (s GetDataSourceOutput) SetRDSMetadata(v RDSMetadata) GetDataSourceOutput { s.RDSMetadata = v return s } // SetRedshiftMetadata sets the RedshiftMetadata field's value. func (s GetDataSourceOutput) SetRedshiftMetadata(v RedshiftMetadata) GetDataSourceOutput { s.RedshiftMetadata = v return s } // SetRoleARN sets the RoleARN field's value. func (s GetDataSourceOutput) SetRoleARN(v string) GetDataSourceOutput { s.RoleARN = &v return s } // SetStartedAt sets the StartedAt field's value. func (s GetDataSourceOutput) SetStartedAt(v time.Time) GetDataSourceOutput { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s GetDataSourceOutput) SetStatus(v string) GetDataSourceOutput { s.Status = &v return s } type GetEvaluationInput struct { _ struct{} `type:"structure"` // The ID of the Evaluation to retrieve. The evaluation of each MLModel is recorded // and cataloged. The ID provides the means to access the information. // // EvaluationId is a required field EvaluationId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetEvaluationInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetEvaluationInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s GetEvaluationInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "GetEvaluationInput"} if s.EvaluationId == nil { invalidParams.Add(request.NewErrParamRequired("EvaluationId")) } if s.EvaluationId != nil && len(s.EvaluationId) < 1 { invalidParams.Add(request.NewErrParamMinLen("EvaluationId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEvaluationId sets the EvaluationId field's value. func (s GetEvaluationInput) SetEvaluationId(v string) GetEvaluationInput { s.EvaluationId = &v return s } // Represents the output of a GetEvaluation operation and describes an Evaluation. type GetEvaluationOutput struct { _ struct{} `type:"structure"` // The approximate CPU time in milliseconds that Amazon Machine Learning spent // processing the Evaluation, normalized and scaled on computation resources. // ComputeTime is only available if the Evaluation is in the COMPLETED state. ComputeTime int64 `type:"long"` // The time that the Evaluation was created. The time is expressed in epoch // time. CreatedAt time.Time `type:"timestamp"` // The AWS user account that invoked the evaluation. The account type can be // either an AWS root account or an AWS Identity and Access Management (IAM) // user account. CreatedByIamUser string `type:"string"` // The DataSource used for this evaluation. EvaluationDataSourceId string `min:"1" type:"string"` // The evaluation ID which is same as the EvaluationId in the request. EvaluationId string `min:"1" type:"string"` // The epoch time when Amazon Machine Learning marked the Evaluation as COMPLETED // or FAILED. FinishedAt is only available when the Evaluation is in the COMPLETED // or FAILED state. FinishedAt time.Time `type:"timestamp"` // The location of the data file or directory in Amazon Simple Storage Service // (Amazon S3). InputDataLocationS3 string `type:"string"` // The time of the most recent edit to the Evaluation. The time is expressed // in epoch time. LastUpdatedAt time.Time `type:"timestamp"` // A link to the file that contains logs of the CreateEvaluation operation. LogUri string `type:"string"` // The ID of the MLModel that was the focus of the evaluation. MLModelId string `min:"1" type:"string"` // A description of the most recent details about evaluating the MLModel. Message string `type:"string"` // A user-supplied name or description of the Evaluation. Name string `type:"string"` // Measurements of how well the MLModel performed using observations referenced // by the DataSource. One of the following metric is returned based on the type // of the MLModel: // // * BinaryAUC: A binary MLModel uses the Area Under the Curve (AUC) technique // to measure performance. // // * RegressionRMSE: A regression MLModel uses the Root Mean Square Error // (RMSE) technique to measure performance. RMSE measures the difference // between predicted and actual values for a single variable. // // * MulticlassAvgFScore: A multiclass MLModel uses the F1 score technique // to measure performance. // // For more information about performance metrics, please see the Amazon Machine // Learning Developer Guide (https://docs.aws.amazon.com/machine-learning/latest/dg). PerformanceMetrics PerformanceMetrics `type:"structure"` // The epoch time when Amazon Machine Learning marked the Evaluation as INPROGRESS. // StartedAt isn't available if the Evaluation is in the PENDING state. StartedAt time.Time `type:"timestamp"` // The status of the evaluation. This element can have one of the following // values: // // * PENDING - Amazon Machine Language (Amazon ML) submitted a request to // evaluate an MLModel. // // * INPROGRESS - The evaluation is underway. // // * FAILED - The request to evaluate an MLModel did not run to completion. // It is not usable. // // * COMPLETED - The evaluation process completed successfully. // // * DELETED - The Evaluation is marked as deleted. It is not usable. Status string `type:"string" enum:"EntityStatus"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetEvaluationOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetEvaluationOutput) GoString() string { return s.String() } // SetComputeTime sets the ComputeTime field's value. func (s GetEvaluationOutput) SetComputeTime(v int64) GetEvaluationOutput { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s GetEvaluationOutput) SetCreatedAt(v time.Time) GetEvaluationOutput { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s GetEvaluationOutput) SetCreatedByIamUser(v string) GetEvaluationOutput { s.CreatedByIamUser = &v return s } // SetEvaluationDataSourceId sets the EvaluationDataSourceId field's value. func (s GetEvaluationOutput) SetEvaluationDataSourceId(v string) GetEvaluationOutput { s.EvaluationDataSourceId = &v return s } // SetEvaluationId sets the EvaluationId field's value. func (s GetEvaluationOutput) SetEvaluationId(v string) GetEvaluationOutput { s.EvaluationId = &v return s } // SetFinishedAt sets the FinishedAt field's value. func (s GetEvaluationOutput) SetFinishedAt(v time.Time) GetEvaluationOutput { s.FinishedAt = &v return s } // SetInputDataLocationS3 sets the InputDataLocationS3 field's value. func (s GetEvaluationOutput) SetInputDataLocationS3(v string) GetEvaluationOutput { s.InputDataLocationS3 = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s GetEvaluationOutput) SetLastUpdatedAt(v time.Time) GetEvaluationOutput { s.LastUpdatedAt = &v return s } // SetLogUri sets the LogUri field's value. func (s GetEvaluationOutput) SetLogUri(v string) GetEvaluationOutput { s.LogUri = &v return s } // SetMLModelId sets the MLModelId field's value. func (s GetEvaluationOutput) SetMLModelId(v string) GetEvaluationOutput { s.MLModelId = &v return s } // SetMessage sets the Message field's value. func (s GetEvaluationOutput) SetMessage(v string) GetEvaluationOutput { s.Message = &v return s } // SetName sets the Name field's value. func (s GetEvaluationOutput) SetName(v string) GetEvaluationOutput { s.Name = &v return s } // SetPerformanceMetrics sets the PerformanceMetrics field's value. func (s GetEvaluationOutput) SetPerformanceMetrics(v PerformanceMetrics) GetEvaluationOutput { s.PerformanceMetrics = v return s } // SetStartedAt sets the StartedAt field's value. func (s GetEvaluationOutput) SetStartedAt(v time.Time) GetEvaluationOutput { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s GetEvaluationOutput) SetStatus(v string) GetEvaluationOutput { s.Status = &v return s } type GetMLModelInput struct { _ struct{} `type:"structure"` // The ID assigned to the MLModel at creation. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` // Specifies whether the GetMLModel operation should return Recipe. // // If true, Recipe is returned. // // If false, Recipe is not returned. Verbose bool `type:"boolean"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetMLModelInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetMLModelInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s GetMLModelInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "GetMLModelInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s GetMLModelInput) SetMLModelId(v string) GetMLModelInput { s.MLModelId = &v return s } // SetVerbose sets the Verbose field's value. func (s GetMLModelInput) SetVerbose(v bool) GetMLModelInput { s.Verbose = &v return s } // Represents the output of a GetMLModel operation, and provides detailed information // about a MLModel. type GetMLModelOutput struct { _ struct{} `type:"structure"` // The approximate CPU time in milliseconds that Amazon Machine Learning spent // processing the MLModel, normalized and scaled on computation resources. ComputeTime // is only available if the MLModel is in the COMPLETED state. ComputeTime int64 `type:"long"` // The time that the MLModel was created. The time is expressed in epoch time. CreatedAt time.Time `type:"timestamp"` // The AWS user account from which the MLModel was created. The account type // can be either an AWS root account or an AWS Identity and Access Management // (IAM) user account. CreatedByIamUser string `type:"string"` // The current endpoint of the MLModel EndpointInfo RealtimeEndpointInfo `type:"structure"` // The epoch time when Amazon Machine Learning marked the MLModel as COMPLETED // or FAILED. FinishedAt is only available when the MLModel is in the COMPLETED // or FAILED state. FinishedAt time.Time `type:"timestamp"` // The location of the data file or directory in Amazon Simple Storage Service // (Amazon S3). InputDataLocationS3 string `type:"string"` // The time of the most recent edit to the MLModel. The time is expressed in // epoch time. LastUpdatedAt time.Time `type:"timestamp"` // A link to the file that contains logs of the CreateMLModel operation. LogUri string `type:"string"` // The MLModel ID, which is same as the MLModelId in the request. MLModelId string `min:"1" type:"string"` // Identifies the MLModel category. The following are the available types: // // REGRESSION -- Produces a numeric result. For example, "What price should // a house be listed at?" // // * BINARY -- Produces one of two possible results. For example, "Is this // an e-commerce website?" // // * MULTICLASS -- Produces one of several possible results. For example, // "Is this a HIGH, LOW or MEDIUM risk trade?" MLModelType string `type:"string" enum:"MLModelType"` // A description of the most recent details about accessing the MLModel. Message string `type:"string"` // A user-supplied name or description of the MLModel. Name string `type:"string"` // The recipe to use when training the MLModel. The Recipe provides detailed // information about the observation data to use during training, and manipulations // to perform on the observation data during training. // // Note: This parameter is provided as part of the verbose format. Recipe string `type:"string"` // The schema used by all of the data files referenced by the DataSource. // // Note: This parameter is provided as part of the verbose format. Schema string `type:"string"` // The scoring threshold is used in binary classification MLModel models. It // marks the boundary between a positive prediction and a negative prediction. // // Output values greater than or equal to the threshold receive a positive result // from the MLModel, such as true. Output values less than the threshold receive // a negative response from the MLModel, such as false. ScoreThreshold float64 `type:"float"` // The time of the most recent edit to the ScoreThreshold. The time is expressed // in epoch time. ScoreThresholdLastUpdatedAt time.Time `type:"timestamp"` // Long integer type that is a 64-bit signed number. SizeInBytes int64 `type:"long"` // The epoch time when Amazon Machine Learning marked the MLModel as INPROGRESS. // StartedAt isn't available if the MLModel is in the PENDING state. StartedAt time.Time `type:"timestamp"` // The current status of the MLModel. This element can have one of the following // values: // // PENDING - Amazon Machine Learning (Amazon ML) submitted a request to // describe a MLModel. // // * INPROGRESS - The request is processing. // // * FAILED - The request did not run to completion. The ML model isn't usable. // // * COMPLETED - The request completed successfully. // // * DELETED - The MLModel is marked as deleted. It isn't usable. Status string `type:"string" enum:"EntityStatus"` // The ID of the training DataSource. TrainingDataSourceId string `min:"1" type:"string"` // A list of the training parameters in the MLModel. The list is implemented // as a map of key-value pairs. // // The following is the current set of training parameters: // // * sgd.maxMLModelSizeInBytes - The maximum allowed size of the model. Depending // on the input data, the size of the model might affect its performance. // The value is an integer that ranges from 100000 to 2147483648. The default // value is 33554432. // // * sgd.maxPasses - The number of times that the training process traverses // the observations to build the MLModel. The value is an integer that ranges // from 1 to 10000. The default value is 10. // // * sgd.shuffleType - Whether Amazon ML shuffles the training data. Shuffling // data improves a model's ability to find the optimal solution for a variety // of data types. The valid values are auto and none. The default value is // none. We strongly recommend that you shuffle your data. // // * sgd.l1RegularizationAmount - The coefficient regularization L1 norm. // It controls overfitting the data by penalizing large coefficients. This // tends to drive coefficients to zero, resulting in a sparse feature set. // If you use this parameter, start by specifying a small value, such as // 1.0E-08. The value is a double that ranges from 0 to MAX_DOUBLE. The default // is to not use L1 normalization. This parameter can't be used when L2 is // specified. Use this parameter sparingly. // // * sgd.l2RegularizationAmount - The coefficient regularization L2 norm. // It controls overfitting the data by penalizing large coefficients. This // tends to drive coefficients to small, nonzero values. If you use this // parameter, start by specifying a small value, such as 1.0E-08. The value // is a double that ranges from 0 to MAX_DOUBLE. The default is to not use // L2 normalization. This parameter can't be used when L1 is specified. Use // this parameter sparingly. TrainingParameters map[string]string `type:"map"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetMLModelOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s GetMLModelOutput) GoString() string { return s.String() } // SetComputeTime sets the ComputeTime field's value. func (s GetMLModelOutput) SetComputeTime(v int64) GetMLModelOutput { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s GetMLModelOutput) SetCreatedAt(v time.Time) GetMLModelOutput { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s GetMLModelOutput) SetCreatedByIamUser(v string) GetMLModelOutput { s.CreatedByIamUser = &v return s } // SetEndpointInfo sets the EndpointInfo field's value. func (s GetMLModelOutput) SetEndpointInfo(v RealtimeEndpointInfo) GetMLModelOutput { s.EndpointInfo = v return s } // SetFinishedAt sets the FinishedAt field's value. func (s GetMLModelOutput) SetFinishedAt(v time.Time) GetMLModelOutput { s.FinishedAt = &v return s } // SetInputDataLocationS3 sets the InputDataLocationS3 field's value. func (s GetMLModelOutput) SetInputDataLocationS3(v string) GetMLModelOutput { s.InputDataLocationS3 = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s GetMLModelOutput) SetLastUpdatedAt(v time.Time) GetMLModelOutput { s.LastUpdatedAt = &v return s } // SetLogUri sets the LogUri field's value. func (s GetMLModelOutput) SetLogUri(v string) GetMLModelOutput { s.LogUri = &v return s } // SetMLModelId sets the MLModelId field's value. func (s GetMLModelOutput) SetMLModelId(v string) GetMLModelOutput { s.MLModelId = &v return s } // SetMLModelType sets the MLModelType field's value. func (s GetMLModelOutput) SetMLModelType(v string) GetMLModelOutput { s.MLModelType = &v return s } // SetMessage sets the Message field's value. func (s GetMLModelOutput) SetMessage(v string) GetMLModelOutput { s.Message = &v return s } // SetName sets the Name field's value. func (s GetMLModelOutput) SetName(v string) GetMLModelOutput { s.Name = &v return s } // SetRecipe sets the Recipe field's value. func (s GetMLModelOutput) SetRecipe(v string) GetMLModelOutput { s.Recipe = &v return s } // SetSchema sets the Schema field's value. func (s GetMLModelOutput) SetSchema(v string) GetMLModelOutput { s.Schema = &v return s } // SetScoreThreshold sets the ScoreThreshold field's value. func (s GetMLModelOutput) SetScoreThreshold(v float64) GetMLModelOutput { s.ScoreThreshold = &v return s } // SetScoreThresholdLastUpdatedAt sets the ScoreThresholdLastUpdatedAt field's value. func (s GetMLModelOutput) SetScoreThresholdLastUpdatedAt(v time.Time) GetMLModelOutput { s.ScoreThresholdLastUpdatedAt = &v return s } // SetSizeInBytes sets the SizeInBytes field's value. func (s GetMLModelOutput) SetSizeInBytes(v int64) GetMLModelOutput { s.SizeInBytes = &v return s } // SetStartedAt sets the StartedAt field's value. func (s GetMLModelOutput) SetStartedAt(v time.Time) GetMLModelOutput { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s GetMLModelOutput) SetStatus(v string) GetMLModelOutput { s.Status = &v return s } // SetTrainingDataSourceId sets the TrainingDataSourceId field's value. func (s GetMLModelOutput) SetTrainingDataSourceId(v string) GetMLModelOutput { s.TrainingDataSourceId = &v return s } // SetTrainingParameters sets the TrainingParameters field's value. func (s GetMLModelOutput) SetTrainingParameters(v map[string]string) GetMLModelOutput { s.TrainingParameters = v return s } // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. type IdempotentParameterMismatchException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Code_ int64 `locationName:"code" type:"integer"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s IdempotentParameterMismatchException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s IdempotentParameterMismatchException) GoString() string { return s.String() } func newErrorIdempotentParameterMismatchException(v protocol.ResponseMetadata) error { return &IdempotentParameterMismatchException{ RespMetadata: v, } } // Code returns the exception type name. func (s IdempotentParameterMismatchException) Code() string { return "IdempotentParameterMismatchException" } // Message returns the exception's message. func (s IdempotentParameterMismatchException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s IdempotentParameterMismatchException) OrigErr() error { return nil } func (s IdempotentParameterMismatchException) Error() string { return fmt.Sprintf("%s: %s\n%s", s.Code(), s.Message(), s.String()) } // Status code returns the HTTP status code for the request's response error. func (s IdempotentParameterMismatchException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s IdempotentParameterMismatchException) RequestID() string { return s.RespMetadata.RequestID } // An error on the server occurred when trying to process a request. type InternalServerException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Code_ int64 `locationName:"code" type:"integer"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s InternalServerException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s InternalServerException) GoString() string { return s.String() } func newErrorInternalServerException(v protocol.ResponseMetadata) error { return &InternalServerException{ RespMetadata: v, } } // Code returns the exception type name. func (s InternalServerException) Code() string { return "InternalServerException" } // Message returns the exception's message. func (s InternalServerException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s InternalServerException) OrigErr() error { return nil } func (s InternalServerException) Error() string { return fmt.Sprintf("%s: %s\n%s", s.Code(), s.Message(), s.String()) } // Status code returns the HTTP status code for the request's response error. func (s InternalServerException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s InternalServerException) RequestID() string { return s.RespMetadata.RequestID } // An error on the client occurred. Typically, the cause is an invalid input // value. type InvalidInputException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Code_ int64 `locationName:"code" type:"integer"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s InvalidInputException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s InvalidInputException) GoString() string { return s.String() } func newErrorInvalidInputException(v protocol.ResponseMetadata) error { return &InvalidInputException{ RespMetadata: v, } } // Code returns the exception type name. func (s InvalidInputException) Code() string { return "InvalidInputException" } // Message returns the exception's message. func (s InvalidInputException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s InvalidInputException) OrigErr() error { return nil } func (s InvalidInputException) Error() string { return fmt.Sprintf("%s: %s\n%s", s.Code(), s.Message(), s.String()) } // Status code returns the HTTP status code for the request's response error. func (s InvalidInputException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s InvalidInputException) RequestID() string { return s.RespMetadata.RequestID } type InvalidTagException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s InvalidTagException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s InvalidTagException) GoString() string { return s.String() } func newErrorInvalidTagException(v protocol.ResponseMetadata) error { return &InvalidTagException{ RespMetadata: v, } } // Code returns the exception type name. func (s InvalidTagException) Code() string { return "InvalidTagException" } // Message returns the exception's message. func (s InvalidTagException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s InvalidTagException) OrigErr() error { return nil } func (s InvalidTagException) Error() string { return fmt.Sprintf("%s: %s", s.Code(), s.Message()) } // Status code returns the HTTP status code for the request's response error. func (s InvalidTagException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s InvalidTagException) RequestID() string { return s.RespMetadata.RequestID } // The subscriber exceeded the maximum number of operations. This exception // can occur when listing objects such as DataSource. type LimitExceededException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Code_ int64 `locationName:"code" type:"integer"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s LimitExceededException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s LimitExceededException) GoString() string { return s.String() } func newErrorLimitExceededException(v protocol.ResponseMetadata) error { return &LimitExceededException{ RespMetadata: v, } } // Code returns the exception type name. func (s LimitExceededException) Code() string { return "LimitExceededException" } // Message returns the exception's message. func (s LimitExceededException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s LimitExceededException) OrigErr() error { return nil } func (s LimitExceededException) Error() string { return fmt.Sprintf("%s: %s\n%s", s.Code(), s.Message(), s.String()) } // Status code returns the HTTP status code for the request's response error. func (s LimitExceededException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s LimitExceededException) RequestID() string { return s.RespMetadata.RequestID } // Represents the output of a GetMLModel operation. // // The content consists of the detailed metadata and the current status of the // MLModel. type MLModel struct { _ struct{} `type:"structure"` // The algorithm used to train the MLModel. The following algorithm is supported: // // SGD -- Stochastic gradient descent. The goal of SGD is to minimize the // gradient of the loss function. Algorithm string `type:"string" enum:"Algorithm"` // Long integer type that is a 64-bit signed number. ComputeTime int64 `type:"long"` // The time that the MLModel was created. The time is expressed in epoch time. CreatedAt time.Time `type:"timestamp"` // The AWS user account from which the MLModel was created. The account type // can be either an AWS root account or an AWS Identity and Access Management // (IAM) user account. CreatedByIamUser string `type:"string"` // The current endpoint of the MLModel. EndpointInfo RealtimeEndpointInfo `type:"structure"` // A timestamp represented in epoch time. FinishedAt time.Time `type:"timestamp"` // The location of the data file or directory in Amazon Simple Storage Service // (Amazon S3). InputDataLocationS3 string `type:"string"` // The time of the most recent edit to the MLModel. The time is expressed in // epoch time. LastUpdatedAt time.Time `type:"timestamp"` // The ID assigned to the MLModel at creation. MLModelId string `min:"1" type:"string"` // Identifies the MLModel category. The following are the available types: // // REGRESSION - Produces a numeric result. For example, "What price should // a house be listed at?" // // * BINARY - Produces one of two possible results. For example, "Is this // a child-friendly web site?". // // * MULTICLASS - Produces one of several possible results. For example, // "Is this a HIGH-, LOW-, or MEDIUM-risk trade?". MLModelType string `type:"string" enum:"MLModelType"` // A description of the most recent details about accessing the MLModel. Message string `type:"string"` // A user-supplied name or description of the MLModel. Name string `type:"string"` ScoreThreshold float64 `type:"float"` // The time of the most recent edit to the ScoreThreshold. The time is expressed // in epoch time. ScoreThresholdLastUpdatedAt time.Time `type:"timestamp"` // Long integer type that is a 64-bit signed number. SizeInBytes int64 `type:"long"` // A timestamp represented in epoch time. StartedAt time.Time `type:"timestamp"` // The current status of an MLModel. This element can have one of the following // values: // // PENDING - Amazon Machine Learning (Amazon ML) submitted a request to // create an MLModel. // // * INPROGRESS - The creation process is underway. // // * FAILED - The request to create an MLModel didn't run to completion. // The model isn't usable. // // * COMPLETED - The creation process completed successfully. // // * DELETED - The MLModel is marked as deleted. It isn't usable. Status string `type:"string" enum:"EntityStatus"` // The ID of the training DataSource. The CreateMLModel operation uses the TrainingDataSourceId. TrainingDataSourceId string `min:"1" type:"string"` // A list of the training parameters in the MLModel. The list is implemented // as a map of key-value pairs. // // The following is the current set of training parameters: // // * sgd.maxMLModelSizeInBytes - The maximum allowed size of the model. Depending // on the input data, the size of the model might affect its performance. // The value is an integer that ranges from 100000 to 2147483648. The default // value is 33554432. // // * sgd.maxPasses - The number of times that the training process traverses // the observations to build the MLModel. The value is an integer that ranges // from 1 to 10000. The default value is 10. // // * sgd.shuffleType - Whether Amazon ML shuffles the training data. Shuffling // the data improves a model's ability to find the optimal solution for a // variety of data types. The valid values are auto and none. The default // value is none. // // * sgd.l1RegularizationAmount - The coefficient regularization L1 norm, // which controls overfitting the data by penalizing large coefficients. // This parameter tends to drive coefficients to zero, resulting in sparse // feature set. If you use this parameter, start by specifying a small value, // such as 1.0E-08. The value is a double that ranges from 0 to MAX_DOUBLE. // The default is to not use L1 normalization. This parameter can't be used // when L2 is specified. Use this parameter sparingly. // // * sgd.l2RegularizationAmount - The coefficient regularization L2 norm, // which controls overfitting the data by penalizing large coefficients. // This tends to drive coefficients to small, nonzero values. If you use // this parameter, start by specifying a small value, such as 1.0E-08. The // value is a double that ranges from 0 to MAX_DOUBLE. The default is to // not use L2 normalization. This parameter can't be used when L1 is specified. // Use this parameter sparingly. TrainingParameters map[string]string `type:"map"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s MLModel) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s MLModel) GoString() string { return s.String() } // SetAlgorithm sets the Algorithm field's value. func (s MLModel) SetAlgorithm(v string) MLModel { s.Algorithm = &v return s } // SetComputeTime sets the ComputeTime field's value. func (s MLModel) SetComputeTime(v int64) MLModel { s.ComputeTime = &v return s } // SetCreatedAt sets the CreatedAt field's value. func (s MLModel) SetCreatedAt(v time.Time) MLModel { s.CreatedAt = &v return s } // SetCreatedByIamUser sets the CreatedByIamUser field's value. func (s MLModel) SetCreatedByIamUser(v string) MLModel { s.CreatedByIamUser = &v return s } // SetEndpointInfo sets the EndpointInfo field's value. func (s MLModel) SetEndpointInfo(v RealtimeEndpointInfo) MLModel { s.EndpointInfo = v return s } // SetFinishedAt sets the FinishedAt field's value. func (s MLModel) SetFinishedAt(v time.Time) MLModel { s.FinishedAt = &v return s } // SetInputDataLocationS3 sets the InputDataLocationS3 field's value. func (s MLModel) SetInputDataLocationS3(v string) MLModel { s.InputDataLocationS3 = &v return s } // SetLastUpdatedAt sets the LastUpdatedAt field's value. func (s MLModel) SetLastUpdatedAt(v time.Time) MLModel { s.LastUpdatedAt = &v return s } // SetMLModelId sets the MLModelId field's value. func (s MLModel) SetMLModelId(v string) MLModel { s.MLModelId = &v return s } // SetMLModelType sets the MLModelType field's value. func (s MLModel) SetMLModelType(v string) MLModel { s.MLModelType = &v return s } // SetMessage sets the Message field's value. func (s MLModel) SetMessage(v string) MLModel { s.Message = &v return s } // SetName sets the Name field's value. func (s MLModel) SetName(v string) MLModel { s.Name = &v return s } // SetScoreThreshold sets the ScoreThreshold field's value. func (s MLModel) SetScoreThreshold(v float64) MLModel { s.ScoreThreshold = &v return s } // SetScoreThresholdLastUpdatedAt sets the ScoreThresholdLastUpdatedAt field's value. func (s MLModel) SetScoreThresholdLastUpdatedAt(v time.Time) MLModel { s.ScoreThresholdLastUpdatedAt = &v return s } // SetSizeInBytes sets the SizeInBytes field's value. func (s MLModel) SetSizeInBytes(v int64) MLModel { s.SizeInBytes = &v return s } // SetStartedAt sets the StartedAt field's value. func (s MLModel) SetStartedAt(v time.Time) MLModel { s.StartedAt = &v return s } // SetStatus sets the Status field's value. func (s MLModel) SetStatus(v string) MLModel { s.Status = &v return s } // SetTrainingDataSourceId sets the TrainingDataSourceId field's value. func (s MLModel) SetTrainingDataSourceId(v string) MLModel { s.TrainingDataSourceId = &v return s } // SetTrainingParameters sets the TrainingParameters field's value. func (s MLModel) SetTrainingParameters(v map[string]string) MLModel { s.TrainingParameters = v return s } // Measurements of how well the MLModel performed on known observations. One // of the following metrics is returned, based on the type of the MLModel: // // - BinaryAUC: The binary MLModel uses the Area Under the Curve (AUC) technique // to measure performance. // // - RegressionRMSE: The regression MLModel uses the Root Mean Square Error // (RMSE) technique to measure performance. RMSE measures the difference // between predicted and actual values for a single variable. // // - MulticlassAvgFScore: The multiclass MLModel uses the F1 score technique // to measure performance. // // For more information about performance metrics, please see the Amazon Machine // Learning Developer Guide (https://docs.aws.amazon.com/machine-learning/latest/dg). type PerformanceMetrics struct { _ struct{} `type:"structure"` Properties map[string]string `type:"map"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PerformanceMetrics) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PerformanceMetrics) GoString() string { return s.String() } // SetProperties sets the Properties field's value. func (s PerformanceMetrics) SetProperties(v map[string]string) PerformanceMetrics { s.Properties = v return s } type PredictInput struct { _ struct{} `type:"structure"` // A unique identifier of the MLModel. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` // PredictEndpoint is a required field PredictEndpoint string `type:"string" required:"true"` // A map of variable name-value pairs that represent an observation. // // Record is a required field Record map[string]string `type:"map" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PredictInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PredictInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s PredictInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "PredictInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if s.PredictEndpoint == nil { invalidParams.Add(request.NewErrParamRequired("PredictEndpoint")) } if s.Record == nil { invalidParams.Add(request.NewErrParamRequired("Record")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s PredictInput) SetMLModelId(v string) PredictInput { s.MLModelId = &v return s } // SetPredictEndpoint sets the PredictEndpoint field's value. func (s PredictInput) SetPredictEndpoint(v string) PredictInput { s.PredictEndpoint = &v return s } // SetRecord sets the Record field's value. func (s PredictInput) SetRecord(v map[string]string) PredictInput { s.Record = v return s } type PredictOutput struct { _ struct{} `type:"structure"` // The output from a Predict operation: // // Details - Contains the following attributes: DetailsAttributes.PREDICTIVE_MODEL_TYPE // - REGRESSION \| BINARY \| MULTICLASS DetailsAttributes.ALGORITHM - SGD // // * PredictedLabel - Present for either a BINARY or MULTICLASS MLModel request. // // * PredictedScores - Contains the raw classification score corresponding // to each label. // // * PredictedValue - Present for a REGRESSION MLModel request. Prediction Prediction `type:"structure"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PredictOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PredictOutput) GoString() string { return s.String() } // SetPrediction sets the Prediction field's value. func (s PredictOutput) SetPrediction(v Prediction) PredictOutput { s.Prediction = v return s } // The output from a Predict operation: // // - Details - Contains the following attributes: DetailsAttributes.PREDICTIVE_MODEL_TYPE // // - REGRESSION \| BINARY \| MULTICLASS DetailsAttributes.ALGORITHM - SGD // // - PredictedLabel - Present for either a BINARY or MULTICLASS MLModel request. // // - PredictedScores - Contains the raw classification score corresponding // to each label. // // - PredictedValue - Present for a REGRESSION MLModel request. type Prediction struct { _ struct{} `type:"structure"` // Provides any additional details regarding the prediction. Details map[string]string `locationName:"details" type:"map"` // The prediction label for either a BINARY or MULTICLASS MLModel. PredictedLabel string `locationName:"predictedLabel" min:"1" type:"string"` // Provides the raw classification score corresponding to each label. PredictedScores map[string]float64 `locationName:"predictedScores" type:"map"` // The prediction value for REGRESSION MLModel. PredictedValue float64 `locationName:"predictedValue" type:"float"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s Prediction) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s Prediction) GoString() string { return s.String() } // SetDetails sets the Details field's value. func (s Prediction) SetDetails(v map[string]string) Prediction { s.Details = v return s } // SetPredictedLabel sets the PredictedLabel field's value. func (s Prediction) SetPredictedLabel(v string) Prediction { s.PredictedLabel = &v return s } // SetPredictedScores sets the PredictedScores field's value. func (s Prediction) SetPredictedScores(v map[string]float64) Prediction { s.PredictedScores = v return s } // SetPredictedValue sets the PredictedValue field's value. func (s Prediction) SetPredictedValue(v float64) Prediction { s.PredictedValue = &v return s } // The exception is thrown when a predict request is made to an unmounted MLModel. type PredictorNotMountedException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PredictorNotMountedException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s PredictorNotMountedException) GoString() string { return s.String() } func newErrorPredictorNotMountedException(v protocol.ResponseMetadata) error { return &PredictorNotMountedException{ RespMetadata: v, } } // Code returns the exception type name. func (s PredictorNotMountedException) Code() string { return "PredictorNotMountedException" } // Message returns the exception's message. func (s PredictorNotMountedException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s PredictorNotMountedException) OrigErr() error { return nil } func (s PredictorNotMountedException) Error() string { return fmt.Sprintf("%s: %s", s.Code(), s.Message()) } // Status code returns the HTTP status code for the request's response error. func (s PredictorNotMountedException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s PredictorNotMountedException) RequestID() string { return s.RespMetadata.RequestID } // The data specification of an Amazon Relational Database Service (Amazon RDS) // DataSource. type RDSDataSpec struct { _ struct{} `type:"structure"` // A JSON string that represents the splitting and rearrangement processing // to be applied to a DataSource. If the DataRearrangement parameter is not // provided, all of the input data is used to create the Datasource. // // There are multiple parameters that control what data is used to create a // datasource: // // * percentBegin Use percentBegin to indicate the beginning of the range // of the data used to create the Datasource. If you do not include percentBegin // and percentEnd, Amazon ML includes all of the data when creating the datasource. // // * percentEnd Use percentEnd to indicate the end of the range of the data // used to create the Datasource. If you do not include percentBegin and // percentEnd, Amazon ML includes all of the data when creating the datasource. // // * complement The complement parameter instructs Amazon ML to use the data // that is not included in the range of percentBegin to percentEnd to create // a datasource. The complement parameter is useful if you need to create // complementary datasources for training and evaluation. To create a complementary // datasource, use the same values for percentBegin and percentEnd, along // with the complement parameter. For example, the following two datasources // do not share any data, and can be used to train and evaluate a model. // The first datasource has 25 percent of the data, and the second one has // 75 percent of the data. Datasource for evaluation: {"splitting":{"percentBegin":0, // "percentEnd":25}} Datasource for training: {"splitting":{"percentBegin":0, // "percentEnd":25, "complement":"true"}} // // * strategy To change how Amazon ML splits the data for a datasource, use // the strategy parameter. The default value for the strategy parameter is // sequential, meaning that Amazon ML takes all of the data records between // the percentBegin and percentEnd parameters for the datasource, in the // order that the records appear in the input data. The following two DataRearrangement // lines are examples of sequentially ordered training and evaluation datasources: // Datasource for evaluation: {"splitting":{"percentBegin":70, "percentEnd":100, // "strategy":"sequential"}} Datasource for training: {"splitting":{"percentBegin":70, // "percentEnd":100, "strategy":"sequential", "complement":"true"}} To randomly // split the input data into the proportions indicated by the percentBegin // and percentEnd parameters, set the strategy parameter to random and provide // a string that is used as the seed value for the random data splitting // (for example, you can use the S3 path to your data as the random seed // string). If you choose the random split strategy, Amazon ML assigns each // row of data a pseudo-random number between 0 and 100, and then selects // the rows that have an assigned number between percentBegin and percentEnd. // Pseudo-random numbers are assigned using both the input seed string value // and the byte offset as a seed, so changing the data results in a different // split. Any existing ordering is preserved. The random splitting strategy // ensures that variables in the training and evaluation data are distributed // similarly. It is useful in the cases where the input data may have an // implicit sort order, which would otherwise result in training and evaluation // datasources containing non-similar data records. The following two DataRearrangement // lines are examples of non-sequentially ordered training and evaluation // datasources: Datasource for evaluation: {"splitting":{"percentBegin":70, // "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}} // Datasource for training: {"splitting":{"percentBegin":70, "percentEnd":100, // "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}} DataRearrangement string `type:"string"` // A JSON string that represents the schema for an Amazon RDS DataSource. The // DataSchema defines the structure of the observation data in the data file(s) // referenced in the DataSource. // // A DataSchema is not required if you specify a DataSchemaUri // // Define your DataSchema as a series of key-value pairs. attributes and excludedVariableNames // have an array of key-value pairs for their value. Use the following format // to define your DataSchema. // // { "version": "1.0", // // "recordAnnotationFieldName": "F1", // // "recordWeightFieldName": "F2", // // "targetFieldName": "F3", // // "dataFormat": "CSV", // // "dataFileContainsHeader": true, // // "attributes": [ // // { "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": // "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": // "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" // }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": // "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" // } ], // // "excludedVariableNames": [ "F6" ] } DataSchema string `type:"string"` // The Amazon S3 location of the DataSchema. DataSchemaUri string `type:"string"` // The AWS Identity and Access Management (IAM) credentials that are used connect // to the Amazon RDS database. // // DatabaseCredentials is a required field DatabaseCredentials RDSDatabaseCredentials `type:"structure" required:"true"` // Describes the DatabaseName and InstanceIdentifier of an Amazon RDS database. // // DatabaseInformation is a required field DatabaseInformation RDSDatabase `type:"structure" required:"true"` // The role (DataPipelineDefaultResourceRole) assumed by an Amazon Elastic Compute // Cloud (Amazon EC2) instance to carry out the copy operation from Amazon RDS // to an Amazon S3 task. For more information, see Role templates (https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html) // for data pipelines. // // ResourceRole is a required field ResourceRole string `min:"1" type:"string" required:"true"` // The Amazon S3 location for staging Amazon RDS data. The data retrieved from // Amazon RDS using SelectSqlQuery is stored in this location. // // S3StagingLocation is a required field S3StagingLocation string `type:"string" required:"true"` // The security group IDs to be used to access a VPC-based RDS DB instance. // Ensure that there are appropriate ingress rules set up to allow access to // the RDS DB instance. This attribute is used by Data Pipeline to carry out // the copy operation from Amazon RDS to an Amazon S3 task. // // SecurityGroupIds is a required field SecurityGroupIds []string `type:"list" required:"true"` // The query that is used to retrieve the observation data for the DataSource. // // SelectSqlQuery is a required field SelectSqlQuery string `min:"1" type:"string" required:"true"` // The role (DataPipelineDefaultRole) assumed by AWS Data Pipeline service to // monitor the progress of the copy task from Amazon RDS to Amazon S3. For more // information, see Role templates (https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html) // for data pipelines. // // ServiceRole is a required field ServiceRole string `min:"1" type:"string" required:"true"` // The subnet ID to be used to access a VPC-based RDS DB instance. This attribute // is used by Data Pipeline to carry out the copy task from Amazon RDS to Amazon // S3. // // SubnetId is a required field SubnetId string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSDataSpec) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSDataSpec) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s RDSDataSpec) Validate() error { invalidParams := request.ErrInvalidParams{Context: "RDSDataSpec"} if s.DatabaseCredentials == nil { invalidParams.Add(request.NewErrParamRequired("DatabaseCredentials")) } if s.DatabaseInformation == nil { invalidParams.Add(request.NewErrParamRequired("DatabaseInformation")) } if s.ResourceRole == nil { invalidParams.Add(request.NewErrParamRequired("ResourceRole")) } if s.ResourceRole != nil && len(s.ResourceRole) < 1 { invalidParams.Add(request.NewErrParamMinLen("ResourceRole", 1)) } if s.S3StagingLocation == nil { invalidParams.Add(request.NewErrParamRequired("S3StagingLocation")) } if s.SecurityGroupIds == nil { invalidParams.Add(request.NewErrParamRequired("SecurityGroupIds")) } if s.SelectSqlQuery == nil { invalidParams.Add(request.NewErrParamRequired("SelectSqlQuery")) } if s.SelectSqlQuery != nil && len(s.SelectSqlQuery) < 1 { invalidParams.Add(request.NewErrParamMinLen("SelectSqlQuery", 1)) } if s.ServiceRole == nil { invalidParams.Add(request.NewErrParamRequired("ServiceRole")) } if s.ServiceRole != nil && len(s.ServiceRole) < 1 { invalidParams.Add(request.NewErrParamMinLen("ServiceRole", 1)) } if s.SubnetId == nil { invalidParams.Add(request.NewErrParamRequired("SubnetId")) } if s.SubnetId != nil && len(s.SubnetId) < 1 { invalidParams.Add(request.NewErrParamMinLen("SubnetId", 1)) } if s.DatabaseCredentials != nil { if err := s.DatabaseCredentials.Validate(); err != nil { invalidParams.AddNested("DatabaseCredentials", err.(request.ErrInvalidParams)) } } if s.DatabaseInformation != nil { if err := s.DatabaseInformation.Validate(); err != nil { invalidParams.AddNested("DatabaseInformation", err.(request.ErrInvalidParams)) } } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDataRearrangement sets the DataRearrangement field's value. func (s RDSDataSpec) SetDataRearrangement(v string) RDSDataSpec { s.DataRearrangement = &v return s } // SetDataSchema sets the DataSchema field's value. func (s RDSDataSpec) SetDataSchema(v string) RDSDataSpec { s.DataSchema = &v return s } // SetDataSchemaUri sets the DataSchemaUri field's value. func (s RDSDataSpec) SetDataSchemaUri(v string) RDSDataSpec { s.DataSchemaUri = &v return s } // SetDatabaseCredentials sets the DatabaseCredentials field's value. func (s RDSDataSpec) SetDatabaseCredentials(v RDSDatabaseCredentials) RDSDataSpec { s.DatabaseCredentials = v return s } // SetDatabaseInformation sets the DatabaseInformation field's value. func (s RDSDataSpec) SetDatabaseInformation(v RDSDatabase) RDSDataSpec { s.DatabaseInformation = v return s } // SetResourceRole sets the ResourceRole field's value. func (s RDSDataSpec) SetResourceRole(v string) RDSDataSpec { s.ResourceRole = &v return s } // SetS3StagingLocation sets the S3StagingLocation field's value. func (s RDSDataSpec) SetS3StagingLocation(v string) RDSDataSpec { s.S3StagingLocation = &v return s } // SetSecurityGroupIds sets the SecurityGroupIds field's value. func (s RDSDataSpec) SetSecurityGroupIds(v []string) RDSDataSpec { s.SecurityGroupIds = v return s } // SetSelectSqlQuery sets the SelectSqlQuery field's value. func (s RDSDataSpec) SetSelectSqlQuery(v string) RDSDataSpec { s.SelectSqlQuery = &v return s } // SetServiceRole sets the ServiceRole field's value. func (s RDSDataSpec) SetServiceRole(v string) RDSDataSpec { s.ServiceRole = &v return s } // SetSubnetId sets the SubnetId field's value. func (s RDSDataSpec) SetSubnetId(v string) RDSDataSpec { s.SubnetId = &v return s } // The database details of an Amazon RDS database. type RDSDatabase struct { _ struct{} `type:"structure"` // The name of a database hosted on an RDS DB instance. // // DatabaseName is a required field DatabaseName string `min:"1" type:"string" required:"true"` // The ID of an RDS DB instance. // // InstanceIdentifier is a required field InstanceIdentifier string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSDatabase) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSDatabase) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s RDSDatabase) Validate() error { invalidParams := request.ErrInvalidParams{Context: "RDSDatabase"} if s.DatabaseName == nil { invalidParams.Add(request.NewErrParamRequired("DatabaseName")) } if s.DatabaseName != nil && len(s.DatabaseName) < 1 { invalidParams.Add(request.NewErrParamMinLen("DatabaseName", 1)) } if s.InstanceIdentifier == nil { invalidParams.Add(request.NewErrParamRequired("InstanceIdentifier")) } if s.InstanceIdentifier != nil && len(s.InstanceIdentifier) < 1 { invalidParams.Add(request.NewErrParamMinLen("InstanceIdentifier", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDatabaseName sets the DatabaseName field's value. func (s RDSDatabase) SetDatabaseName(v string) RDSDatabase { s.DatabaseName = &v return s } // SetInstanceIdentifier sets the InstanceIdentifier field's value. func (s RDSDatabase) SetInstanceIdentifier(v string) RDSDatabase { s.InstanceIdentifier = &v return s } // The database credentials to connect to a database on an RDS DB instance. type RDSDatabaseCredentials struct { _ struct{} `type:"structure"` // The password to be used by Amazon ML to connect to a database on an RDS DB // instance. The password should have sufficient permissions to execute the // RDSSelectQuery query. // // Password is a sensitive parameter and its value will be // replaced with "sensitive" in string returned by RDSDatabaseCredentials's // String and GoString methods. // // Password is a required field Password string `min:"8" type:"string" required:"true" sensitive:"true"` // The username to be used by Amazon ML to connect to database on an Amazon // RDS instance. The username should have sufficient permissions to execute // an RDSSelectSqlQuery query. // // Username is a required field Username string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSDatabaseCredentials) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSDatabaseCredentials) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s RDSDatabaseCredentials) Validate() error { invalidParams := request.ErrInvalidParams{Context: "RDSDatabaseCredentials"} if s.Password == nil { invalidParams.Add(request.NewErrParamRequired("Password")) } if s.Password != nil && len(s.Password) < 8 { invalidParams.Add(request.NewErrParamMinLen("Password", 8)) } if s.Username == nil { invalidParams.Add(request.NewErrParamRequired("Username")) } if s.Username != nil && len(s.Username) < 1 { invalidParams.Add(request.NewErrParamMinLen("Username", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetPassword sets the Password field's value. func (s RDSDatabaseCredentials) SetPassword(v string) RDSDatabaseCredentials { s.Password = &v return s } // SetUsername sets the Username field's value. func (s RDSDatabaseCredentials) SetUsername(v string) RDSDatabaseCredentials { s.Username = &v return s } // The datasource details that are specific to Amazon RDS. type RDSMetadata struct { _ struct{} `type:"structure"` // The ID of the Data Pipeline instance that is used to carry to copy data from // Amazon RDS to Amazon S3. You can use the ID to find details about the instance // in the Data Pipeline console. DataPipelineId string `min:"1" type:"string"` // The database details required to connect to an Amazon RDS. Database RDSDatabase `type:"structure"` // The username to be used by Amazon ML to connect to database on an Amazon // RDS instance. The username should have sufficient permissions to execute // an RDSSelectSqlQuery query. DatabaseUserName string `min:"1" type:"string"` // The role (DataPipelineDefaultResourceRole) assumed by an Amazon EC2 instance // to carry out the copy task from Amazon RDS to Amazon S3. For more information, // see Role templates (https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html) // for data pipelines. ResourceRole string `min:"1" type:"string"` // The SQL query that is supplied during CreateDataSourceFromRDS. Returns only // if Verbose is true in GetDataSourceInput. SelectSqlQuery string `min:"1" type:"string"` // The role (DataPipelineDefaultRole) assumed by the Data Pipeline service to // monitor the progress of the copy task from Amazon RDS to Amazon S3. For more // information, see Role templates (https://docs.aws.amazon.com/datapipeline/latest/DeveloperGuide/dp-iam-roles.html) // for data pipelines. ServiceRole string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSMetadata) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RDSMetadata) GoString() string { return s.String() } // SetDataPipelineId sets the DataPipelineId field's value. func (s RDSMetadata) SetDataPipelineId(v string) RDSMetadata { s.DataPipelineId = &v return s } // SetDatabase sets the Database field's value. func (s RDSMetadata) SetDatabase(v RDSDatabase) RDSMetadata { s.Database = v return s } // SetDatabaseUserName sets the DatabaseUserName field's value. func (s RDSMetadata) SetDatabaseUserName(v string) RDSMetadata { s.DatabaseUserName = &v return s } // SetResourceRole sets the ResourceRole field's value. func (s RDSMetadata) SetResourceRole(v string) RDSMetadata { s.ResourceRole = &v return s } // SetSelectSqlQuery sets the SelectSqlQuery field's value. func (s RDSMetadata) SetSelectSqlQuery(v string) RDSMetadata { s.SelectSqlQuery = &v return s } // SetServiceRole sets the ServiceRole field's value. func (s RDSMetadata) SetServiceRole(v string) RDSMetadata { s.ServiceRole = &v return s } // Describes the real-time endpoint information for an MLModel. type RealtimeEndpointInfo struct { _ struct{} `type:"structure"` // The time that the request to create the real-time endpoint for the MLModel // was received. The time is expressed in epoch time. CreatedAt time.Time `type:"timestamp"` // The current status of the real-time endpoint for the MLModel. This element // can have one of the following values: // // NONE - Endpoint does not exist or was previously deleted. // // * READY - Endpoint is ready to be used for real-time predictions. // // * UPDATING - Updating/creating the endpoint. EndpointStatus string `type:"string" enum:"RealtimeEndpointStatus"` // The URI that specifies where to send real-time prediction requests for the // MLModel. // // Note: The application must wait until the real-time endpoint is ready before // using this URI. EndpointUrl string `type:"string"` // The maximum processing rate for the real-time endpoint for MLModel, measured // in incoming requests per second. PeakRequestsPerSecond int64 `type:"integer"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RealtimeEndpointInfo) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RealtimeEndpointInfo) GoString() string { return s.String() } // SetCreatedAt sets the CreatedAt field's value. func (s RealtimeEndpointInfo) SetCreatedAt(v time.Time) RealtimeEndpointInfo { s.CreatedAt = &v return s } // SetEndpointStatus sets the EndpointStatus field's value. func (s RealtimeEndpointInfo) SetEndpointStatus(v string) RealtimeEndpointInfo { s.EndpointStatus = &v return s } // SetEndpointUrl sets the EndpointUrl field's value. func (s RealtimeEndpointInfo) SetEndpointUrl(v string) RealtimeEndpointInfo { s.EndpointUrl = &v return s } // SetPeakRequestsPerSecond sets the PeakRequestsPerSecond field's value. func (s RealtimeEndpointInfo) SetPeakRequestsPerSecond(v int64) RealtimeEndpointInfo { s.PeakRequestsPerSecond = &v return s } // Describes the data specification of an Amazon Redshift DataSource. type RedshiftDataSpec struct { _ struct{} `type:"structure"` // A JSON string that represents the splitting and rearrangement processing // to be applied to a DataSource. If the DataRearrangement parameter is not // provided, all of the input data is used to create the Datasource. // // There are multiple parameters that control what data is used to create a // datasource: // // percentBegin Use percentBegin to indicate the beginning of the range // of the data used to create the Datasource. If you do not include percentBegin // and percentEnd, Amazon ML includes all of the data when creating the datasource. // // * percentEnd Use percentEnd to indicate the end of the range of the data // used to create the Datasource. If you do not include percentBegin and // percentEnd, Amazon ML includes all of the data when creating the datasource. // // * complement The complement parameter instructs Amazon ML to use the data // that is not included in the range of percentBegin to percentEnd to create // a datasource. The complement parameter is useful if you need to create // complementary datasources for training and evaluation. To create a complementary // datasource, use the same values for percentBegin and percentEnd, along // with the complement parameter. For example, the following two datasources // do not share any data, and can be used to train and evaluate a model. // The first datasource has 25 percent of the data, and the second one has // 75 percent of the data. Datasource for evaluation: {"splitting":{"percentBegin":0, // "percentEnd":25}} Datasource for training: {"splitting":{"percentBegin":0, // "percentEnd":25, "complement":"true"}} // // * strategy To change how Amazon ML splits the data for a datasource, use // the strategy parameter. The default value for the strategy parameter is // sequential, meaning that Amazon ML takes all of the data records between // the percentBegin and percentEnd parameters for the datasource, in the // order that the records appear in the input data. The following two DataRearrangement // lines are examples of sequentially ordered training and evaluation datasources: // Datasource for evaluation: {"splitting":{"percentBegin":70, "percentEnd":100, // "strategy":"sequential"}} Datasource for training: {"splitting":{"percentBegin":70, // "percentEnd":100, "strategy":"sequential", "complement":"true"}} To randomly // split the input data into the proportions indicated by the percentBegin // and percentEnd parameters, set the strategy parameter to random and provide // a string that is used as the seed value for the random data splitting // (for example, you can use the S3 path to your data as the random seed // string). If you choose the random split strategy, Amazon ML assigns each // row of data a pseudo-random number between 0 and 100, and then selects // the rows that have an assigned number between percentBegin and percentEnd. // Pseudo-random numbers are assigned using both the input seed string value // and the byte offset as a seed, so changing the data results in a different // split. Any existing ordering is preserved. The random splitting strategy // ensures that variables in the training and evaluation data are distributed // similarly. It is useful in the cases where the input data may have an // implicit sort order, which would otherwise result in training and evaluation // datasources containing non-similar data records. The following two DataRearrangement // lines are examples of non-sequentially ordered training and evaluation // datasources: Datasource for evaluation: {"splitting":{"percentBegin":70, // "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}} // Datasource for training: {"splitting":{"percentBegin":70, "percentEnd":100, // "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}} DataRearrangement string `type:"string"` // A JSON string that represents the schema for an Amazon Redshift DataSource. // The DataSchema defines the structure of the observation data in the data // file(s) referenced in the DataSource. // // A DataSchema is not required if you specify a DataSchemaUri. // // Define your DataSchema as a series of key-value pairs. attributes and excludedVariableNames // have an array of key-value pairs for their value. Use the following format // to define your DataSchema. // // { "version": "1.0", // // "recordAnnotationFieldName": "F1", // // "recordWeightFieldName": "F2", // // "targetFieldName": "F3", // // "dataFormat": "CSV", // // "dataFileContainsHeader": true, // // "attributes": [ // // { "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": // "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": // "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" // }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": // "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" // } ], // // "excludedVariableNames": [ "F6" ] } DataSchema string `type:"string"` // Describes the schema location for an Amazon Redshift DataSource. DataSchemaUri string `type:"string"` // Describes AWS Identity and Access Management (IAM) credentials that are used // connect to the Amazon Redshift database. // // DatabaseCredentials is a required field DatabaseCredentials RedshiftDatabaseCredentials `type:"structure" required:"true"` // Describes the DatabaseName and ClusterIdentifier for an Amazon Redshift DataSource. // // DatabaseInformation is a required field DatabaseInformation RedshiftDatabase `type:"structure" required:"true"` // Describes an Amazon S3 location to store the result set of the SelectSqlQuery // query. // // S3StagingLocation is a required field S3StagingLocation string `type:"string" required:"true"` // Describes the SQL Query to execute on an Amazon Redshift database for an // Amazon Redshift DataSource. // // SelectSqlQuery is a required field SelectSqlQuery string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftDataSpec) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftDataSpec) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s RedshiftDataSpec) Validate() error { invalidParams := request.ErrInvalidParams{Context: "RedshiftDataSpec"} if s.DatabaseCredentials == nil { invalidParams.Add(request.NewErrParamRequired("DatabaseCredentials")) } if s.DatabaseInformation == nil { invalidParams.Add(request.NewErrParamRequired("DatabaseInformation")) } if s.S3StagingLocation == nil { invalidParams.Add(request.NewErrParamRequired("S3StagingLocation")) } if s.SelectSqlQuery == nil { invalidParams.Add(request.NewErrParamRequired("SelectSqlQuery")) } if s.SelectSqlQuery != nil && len(s.SelectSqlQuery) < 1 { invalidParams.Add(request.NewErrParamMinLen("SelectSqlQuery", 1)) } if s.DatabaseCredentials != nil { if err := s.DatabaseCredentials.Validate(); err != nil { invalidParams.AddNested("DatabaseCredentials", err.(request.ErrInvalidParams)) } } if s.DatabaseInformation != nil { if err := s.DatabaseInformation.Validate(); err != nil { invalidParams.AddNested("DatabaseInformation", err.(request.ErrInvalidParams)) } } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDataRearrangement sets the DataRearrangement field's value. func (s RedshiftDataSpec) SetDataRearrangement(v string) RedshiftDataSpec { s.DataRearrangement = &v return s } // SetDataSchema sets the DataSchema field's value. func (s RedshiftDataSpec) SetDataSchema(v string) RedshiftDataSpec { s.DataSchema = &v return s } // SetDataSchemaUri sets the DataSchemaUri field's value. func (s RedshiftDataSpec) SetDataSchemaUri(v string) RedshiftDataSpec { s.DataSchemaUri = &v return s } // SetDatabaseCredentials sets the DatabaseCredentials field's value. func (s RedshiftDataSpec) SetDatabaseCredentials(v RedshiftDatabaseCredentials) RedshiftDataSpec { s.DatabaseCredentials = v return s } // SetDatabaseInformation sets the DatabaseInformation field's value. func (s RedshiftDataSpec) SetDatabaseInformation(v RedshiftDatabase) RedshiftDataSpec { s.DatabaseInformation = v return s } // SetS3StagingLocation sets the S3StagingLocation field's value. func (s RedshiftDataSpec) SetS3StagingLocation(v string) RedshiftDataSpec { s.S3StagingLocation = &v return s } // SetSelectSqlQuery sets the SelectSqlQuery field's value. func (s RedshiftDataSpec) SetSelectSqlQuery(v string) RedshiftDataSpec { s.SelectSqlQuery = &v return s } // Describes the database details required to connect to an Amazon Redshift // database. type RedshiftDatabase struct { _ struct{} `type:"structure"` // The ID of an Amazon Redshift cluster. // // ClusterIdentifier is a required field ClusterIdentifier string `min:"1" type:"string" required:"true"` // The name of a database hosted on an Amazon Redshift cluster. // // DatabaseName is a required field DatabaseName string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftDatabase) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftDatabase) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s RedshiftDatabase) Validate() error { invalidParams := request.ErrInvalidParams{Context: "RedshiftDatabase"} if s.ClusterIdentifier == nil { invalidParams.Add(request.NewErrParamRequired("ClusterIdentifier")) } if s.ClusterIdentifier != nil && len(s.ClusterIdentifier) < 1 { invalidParams.Add(request.NewErrParamMinLen("ClusterIdentifier", 1)) } if s.DatabaseName == nil { invalidParams.Add(request.NewErrParamRequired("DatabaseName")) } if s.DatabaseName != nil && len(s.DatabaseName) < 1 { invalidParams.Add(request.NewErrParamMinLen("DatabaseName", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetClusterIdentifier sets the ClusterIdentifier field's value. func (s RedshiftDatabase) SetClusterIdentifier(v string) RedshiftDatabase { s.ClusterIdentifier = &v return s } // SetDatabaseName sets the DatabaseName field's value. func (s RedshiftDatabase) SetDatabaseName(v string) RedshiftDatabase { s.DatabaseName = &v return s } // Describes the database credentials for connecting to a database on an Amazon // Redshift cluster. type RedshiftDatabaseCredentials struct { _ struct{} `type:"structure"` // A password to be used by Amazon ML to connect to a database on an Amazon // Redshift cluster. The password should have sufficient permissions to execute // a RedshiftSelectSqlQuery query. The password should be valid for an Amazon // Redshift USER (https://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_USER.html). // // Password is a sensitive parameter and its value will be // replaced with "sensitive" in string returned by RedshiftDatabaseCredentials's // String and GoString methods. // // Password is a required field Password string `min:"8" type:"string" required:"true" sensitive:"true"` // A username to be used by Amazon Machine Learning (Amazon ML)to connect to // a database on an Amazon Redshift cluster. The username should have sufficient // permissions to execute the RedshiftSelectSqlQuery query. The username should // be valid for an Amazon Redshift USER (https://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_USER.html). // // Username is a required field Username string `min:"1" type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftDatabaseCredentials) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftDatabaseCredentials) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s RedshiftDatabaseCredentials) Validate() error { invalidParams := request.ErrInvalidParams{Context: "RedshiftDatabaseCredentials"} if s.Password == nil { invalidParams.Add(request.NewErrParamRequired("Password")) } if s.Password != nil && len(s.Password) < 8 { invalidParams.Add(request.NewErrParamMinLen("Password", 8)) } if s.Username == nil { invalidParams.Add(request.NewErrParamRequired("Username")) } if s.Username != nil && len(s.Username) < 1 { invalidParams.Add(request.NewErrParamMinLen("Username", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetPassword sets the Password field's value. func (s RedshiftDatabaseCredentials) SetPassword(v string) RedshiftDatabaseCredentials { s.Password = &v return s } // SetUsername sets the Username field's value. func (s RedshiftDatabaseCredentials) SetUsername(v string) RedshiftDatabaseCredentials { s.Username = &v return s } // Describes the DataSource details specific to Amazon Redshift. type RedshiftMetadata struct { _ struct{} `type:"structure"` // A username to be used by Amazon Machine Learning (Amazon ML)to connect to // a database on an Amazon Redshift cluster. The username should have sufficient // permissions to execute the RedshiftSelectSqlQuery query. The username should // be valid for an Amazon Redshift USER (https://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_USER.html). DatabaseUserName string `min:"1" type:"string"` // Describes the database details required to connect to an Amazon Redshift // database. RedshiftDatabase RedshiftDatabase `type:"structure"` // The SQL query that is specified during CreateDataSourceFromRedshift. Returns // only if Verbose is true in GetDataSourceInput. SelectSqlQuery string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftMetadata) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s RedshiftMetadata) GoString() string { return s.String() } // SetDatabaseUserName sets the DatabaseUserName field's value. func (s RedshiftMetadata) SetDatabaseUserName(v string) RedshiftMetadata { s.DatabaseUserName = &v return s } // SetRedshiftDatabase sets the RedshiftDatabase field's value. func (s RedshiftMetadata) SetRedshiftDatabase(v RedshiftDatabase) RedshiftMetadata { s.RedshiftDatabase = v return s } // SetSelectSqlQuery sets the SelectSqlQuery field's value. func (s RedshiftMetadata) SetSelectSqlQuery(v string) RedshiftMetadata { s.SelectSqlQuery = &v return s } // A specified resource cannot be located. type ResourceNotFoundException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Code_ int64 `locationName:"code" type:"integer"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s ResourceNotFoundException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s ResourceNotFoundException) GoString() string { return s.String() } func newErrorResourceNotFoundException(v protocol.ResponseMetadata) error { return &ResourceNotFoundException{ RespMetadata: v, } } // Code returns the exception type name. func (s ResourceNotFoundException) Code() string { return "ResourceNotFoundException" } // Message returns the exception's message. func (s ResourceNotFoundException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s ResourceNotFoundException) OrigErr() error { return nil } func (s ResourceNotFoundException) Error() string { return fmt.Sprintf("%s: %s\n%s", s.Code(), s.Message(), s.String()) } // Status code returns the HTTP status code for the request's response error. func (s ResourceNotFoundException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s ResourceNotFoundException) RequestID() string { return s.RespMetadata.RequestID } // Describes the data specification of a DataSource. type S3DataSpec struct { _ struct{} `type:"structure"` // The location of the data file(s) used by a DataSource. The URI specifies // a data file or an Amazon Simple Storage Service (Amazon S3) directory or // bucket containing data files. // // DataLocationS3 is a required field DataLocationS3 string `type:"string" required:"true"` // A JSON string that represents the splitting and rearrangement processing // to be applied to a DataSource. If the DataRearrangement parameter is not // provided, all of the input data is used to create the Datasource. // // There are multiple parameters that control what data is used to create a // datasource: // // percentBegin Use percentBegin to indicate the beginning of the range // of the data used to create the Datasource. If you do not include percentBegin // and percentEnd, Amazon ML includes all of the data when creating the datasource. // // * percentEnd Use percentEnd to indicate the end of the range of the data // used to create the Datasource. If you do not include percentBegin and // percentEnd, Amazon ML includes all of the data when creating the datasource. // // * complement The complement parameter instructs Amazon ML to use the data // that is not included in the range of percentBegin to percentEnd to create // a datasource. The complement parameter is useful if you need to create // complementary datasources for training and evaluation. To create a complementary // datasource, use the same values for percentBegin and percentEnd, along // with the complement parameter. For example, the following two datasources // do not share any data, and can be used to train and evaluate a model. // The first datasource has 25 percent of the data, and the second one has // 75 percent of the data. Datasource for evaluation: {"splitting":{"percentBegin":0, // "percentEnd":25}} Datasource for training: {"splitting":{"percentBegin":0, // "percentEnd":25, "complement":"true"}} // // * strategy To change how Amazon ML splits the data for a datasource, use // the strategy parameter. The default value for the strategy parameter is // sequential, meaning that Amazon ML takes all of the data records between // the percentBegin and percentEnd parameters for the datasource, in the // order that the records appear in the input data. The following two DataRearrangement // lines are examples of sequentially ordered training and evaluation datasources: // Datasource for evaluation: {"splitting":{"percentBegin":70, "percentEnd":100, // "strategy":"sequential"}} Datasource for training: {"splitting":{"percentBegin":70, // "percentEnd":100, "strategy":"sequential", "complement":"true"}} To randomly // split the input data into the proportions indicated by the percentBegin // and percentEnd parameters, set the strategy parameter to random and provide // a string that is used as the seed value for the random data splitting // (for example, you can use the S3 path to your data as the random seed // string). If you choose the random split strategy, Amazon ML assigns each // row of data a pseudo-random number between 0 and 100, and then selects // the rows that have an assigned number between percentBegin and percentEnd. // Pseudo-random numbers are assigned using both the input seed string value // and the byte offset as a seed, so changing the data results in a different // split. Any existing ordering is preserved. The random splitting strategy // ensures that variables in the training and evaluation data are distributed // similarly. It is useful in the cases where the input data may have an // implicit sort order, which would otherwise result in training and evaluation // datasources containing non-similar data records. The following two DataRearrangement // lines are examples of non-sequentially ordered training and evaluation // datasources: Datasource for evaluation: {"splitting":{"percentBegin":70, // "percentEnd":100, "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv"}} // Datasource for training: {"splitting":{"percentBegin":70, "percentEnd":100, // "strategy":"random", "randomSeed"="s3://my_s3_path/bucket/file.csv", "complement":"true"}} DataRearrangement string `type:"string"` // A JSON string that represents the schema for an Amazon S3 DataSource. The // DataSchema defines the structure of the observation data in the data file(s) // referenced in the DataSource. // // You must provide either the DataSchema or the DataSchemaLocationS3. // // Define your DataSchema as a series of key-value pairs. attributes and excludedVariableNames // have an array of key-value pairs for their value. Use the following format // to define your DataSchema. // // { "version": "1.0", // // "recordAnnotationFieldName": "F1", // // "recordWeightFieldName": "F2", // // "targetFieldName": "F3", // // "dataFormat": "CSV", // // "dataFileContainsHeader": true, // // "attributes": [ // // { "fieldName": "F1", "fieldType": "TEXT" }, { "fieldName": "F2", "fieldType": // "NUMERIC" }, { "fieldName": "F3", "fieldType": "CATEGORICAL" }, { "fieldName": // "F4", "fieldType": "NUMERIC" }, { "fieldName": "F5", "fieldType": "CATEGORICAL" // }, { "fieldName": "F6", "fieldType": "TEXT" }, { "fieldName": "F7", "fieldType": // "WEIGHTED_INT_SEQUENCE" }, { "fieldName": "F8", "fieldType": "WEIGHTED_STRING_SEQUENCE" // } ], // // "excludedVariableNames": [ "F6" ] } DataSchema string `type:"string"` // Describes the schema location in Amazon S3. You must provide either the DataSchema // or the DataSchemaLocationS3. DataSchemaLocationS3 string `type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s S3DataSpec) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s S3DataSpec) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s S3DataSpec) Validate() error { invalidParams := request.ErrInvalidParams{Context: "S3DataSpec"} if s.DataLocationS3 == nil { invalidParams.Add(request.NewErrParamRequired("DataLocationS3")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDataLocationS3 sets the DataLocationS3 field's value. func (s S3DataSpec) SetDataLocationS3(v string) S3DataSpec { s.DataLocationS3 = &v return s } // SetDataRearrangement sets the DataRearrangement field's value. func (s S3DataSpec) SetDataRearrangement(v string) S3DataSpec { s.DataRearrangement = &v return s } // SetDataSchema sets the DataSchema field's value. func (s S3DataSpec) SetDataSchema(v string) S3DataSpec { s.DataSchema = &v return s } // SetDataSchemaLocationS3 sets the DataSchemaLocationS3 field's value. func (s S3DataSpec) SetDataSchemaLocationS3(v string) S3DataSpec { s.DataSchemaLocationS3 = &v return s } // A custom key-value pair associated with an ML object, such as an ML model. type Tag struct { _ struct{} `type:"structure"` // A unique identifier for the tag. Valid characters include Unicode letters, // digits, white space, _, ., /, =, +, -, %, and @. Key string `min:"1" type:"string"` // An optional string, typically used to describe or define the tag. Valid characters // include Unicode letters, digits, white space, _, ., /, =, +, -, %, and @. Value string `type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s Tag) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s Tag) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s Tag) Validate() error { invalidParams := request.ErrInvalidParams{Context: "Tag"} if s.Key != nil && len(s.Key) < 1 { invalidParams.Add(request.NewErrParamMinLen("Key", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetKey sets the Key field's value. func (s Tag) SetKey(v string) Tag { s.Key = &v return s } // SetValue sets the Value field's value. func (s Tag) SetValue(v string) Tag { s.Value = &v return s } type TagLimitExceededException struct { _ struct{} `type:"structure"` RespMetadata protocol.ResponseMetadata `json:"-" xml:"-"` Message_ string `locationName:"message" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s TagLimitExceededException) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s TagLimitExceededException) GoString() string { return s.String() } func newErrorTagLimitExceededException(v protocol.ResponseMetadata) error { return &TagLimitExceededException{ RespMetadata: v, } } // Code returns the exception type name. func (s TagLimitExceededException) Code() string { return "TagLimitExceededException" } // Message returns the exception's message. func (s TagLimitExceededException) Message() string { if s.Message_ != nil { return s.Message_ } return "" } // OrigErr always returns nil, satisfies awserr.Error interface. func (s TagLimitExceededException) OrigErr() error { return nil } func (s TagLimitExceededException) Error() string { return fmt.Sprintf("%s: %s", s.Code(), s.Message()) } // Status code returns the HTTP status code for the request's response error. func (s TagLimitExceededException) StatusCode() int { return s.RespMetadata.StatusCode } // RequestID returns the service's response RequestID for request. func (s TagLimitExceededException) RequestID() string { return s.RespMetadata.RequestID } type UpdateBatchPredictionInput struct { _ struct{} `type:"structure"` // The ID assigned to the BatchPrediction during creation. // // BatchPredictionId is a required field BatchPredictionId string `min:"1" type:"string" required:"true"` // A new user-supplied name or description of the BatchPrediction. // // BatchPredictionName is a required field BatchPredictionName string `type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateBatchPredictionInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateBatchPredictionInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s UpdateBatchPredictionInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "UpdateBatchPredictionInput"} if s.BatchPredictionId == nil { invalidParams.Add(request.NewErrParamRequired("BatchPredictionId")) } if s.BatchPredictionId != nil && len(s.BatchPredictionId) < 1 { invalidParams.Add(request.NewErrParamMinLen("BatchPredictionId", 1)) } if s.BatchPredictionName == nil { invalidParams.Add(request.NewErrParamRequired("BatchPredictionName")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s UpdateBatchPredictionInput) SetBatchPredictionId(v string) UpdateBatchPredictionInput { s.BatchPredictionId = &v return s } // SetBatchPredictionName sets the BatchPredictionName field's value. func (s UpdateBatchPredictionInput) SetBatchPredictionName(v string) UpdateBatchPredictionInput { s.BatchPredictionName = &v return s } // Represents the output of an UpdateBatchPrediction operation. // // You can see the updated content by using the GetBatchPrediction operation. type UpdateBatchPredictionOutput struct { _ struct{} `type:"structure"` // The ID assigned to the BatchPrediction during creation. This value should // be identical to the value of the BatchPredictionId in the request. BatchPredictionId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateBatchPredictionOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateBatchPredictionOutput) GoString() string { return s.String() } // SetBatchPredictionId sets the BatchPredictionId field's value. func (s UpdateBatchPredictionOutput) SetBatchPredictionId(v string) UpdateBatchPredictionOutput { s.BatchPredictionId = &v return s } type UpdateDataSourceInput struct { _ struct{} `type:"structure"` // The ID assigned to the DataSource during creation. // // DataSourceId is a required field DataSourceId string `min:"1" type:"string" required:"true"` // A new user-supplied name or description of the DataSource that will replace // the current description. // // DataSourceName is a required field DataSourceName string `type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateDataSourceInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateDataSourceInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s UpdateDataSourceInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "UpdateDataSourceInput"} if s.DataSourceId == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceId")) } if s.DataSourceId != nil && len(s.DataSourceId) < 1 { invalidParams.Add(request.NewErrParamMinLen("DataSourceId", 1)) } if s.DataSourceName == nil { invalidParams.Add(request.NewErrParamRequired("DataSourceName")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetDataSourceId sets the DataSourceId field's value. func (s UpdateDataSourceInput) SetDataSourceId(v string) UpdateDataSourceInput { s.DataSourceId = &v return s } // SetDataSourceName sets the DataSourceName field's value. func (s UpdateDataSourceInput) SetDataSourceName(v string) UpdateDataSourceInput { s.DataSourceName = &v return s } // Represents the output of an UpdateDataSource operation. // // You can see the updated content by using the GetBatchPrediction operation. type UpdateDataSourceOutput struct { _ struct{} `type:"structure"` // The ID assigned to the DataSource during creation. This value should be identical // to the value of the DataSourceID in the request. DataSourceId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateDataSourceOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateDataSourceOutput) GoString() string { return s.String() } // SetDataSourceId sets the DataSourceId field's value. func (s UpdateDataSourceOutput) SetDataSourceId(v string) UpdateDataSourceOutput { s.DataSourceId = &v return s } type UpdateEvaluationInput struct { _ struct{} `type:"structure"` // The ID assigned to the Evaluation during creation. // // EvaluationId is a required field EvaluationId string `min:"1" type:"string" required:"true"` // A new user-supplied name or description of the Evaluation that will replace // the current content. // // EvaluationName is a required field EvaluationName string `type:"string" required:"true"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateEvaluationInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateEvaluationInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s UpdateEvaluationInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "UpdateEvaluationInput"} if s.EvaluationId == nil { invalidParams.Add(request.NewErrParamRequired("EvaluationId")) } if s.EvaluationId != nil && len(s.EvaluationId) < 1 { invalidParams.Add(request.NewErrParamMinLen("EvaluationId", 1)) } if s.EvaluationName == nil { invalidParams.Add(request.NewErrParamRequired("EvaluationName")) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetEvaluationId sets the EvaluationId field's value. func (s UpdateEvaluationInput) SetEvaluationId(v string) UpdateEvaluationInput { s.EvaluationId = &v return s } // SetEvaluationName sets the EvaluationName field's value. func (s UpdateEvaluationInput) SetEvaluationName(v string) UpdateEvaluationInput { s.EvaluationName = &v return s } // Represents the output of an UpdateEvaluation operation. // // You can see the updated content by using the GetEvaluation operation. type UpdateEvaluationOutput struct { _ struct{} `type:"structure"` // The ID assigned to the Evaluation during creation. This value should be identical // to the value of the Evaluation in the request. EvaluationId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateEvaluationOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateEvaluationOutput) GoString() string { return s.String() } // SetEvaluationId sets the EvaluationId field's value. func (s UpdateEvaluationOutput) SetEvaluationId(v string) UpdateEvaluationOutput { s.EvaluationId = &v return s } type UpdateMLModelInput struct { _ struct{} `type:"structure"` // The ID assigned to the MLModel during creation. // // MLModelId is a required field MLModelId string `min:"1" type:"string" required:"true"` // A user-supplied name or description of the MLModel. MLModelName string `type:"string"` // The ScoreThreshold used in binary classification MLModel that marks the boundary // between a positive prediction and a negative prediction. // // Output values greater than or equal to the ScoreThreshold receive a positive // result from the MLModel, such as true. Output values less than the ScoreThreshold // receive a negative response from the MLModel, such as false. ScoreThreshold float64 `type:"float"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateMLModelInput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateMLModelInput) GoString() string { return s.String() } // Validate inspects the fields of the type to determine if they are valid. func (s UpdateMLModelInput) Validate() error { invalidParams := request.ErrInvalidParams{Context: "UpdateMLModelInput"} if s.MLModelId == nil { invalidParams.Add(request.NewErrParamRequired("MLModelId")) } if s.MLModelId != nil && len(s.MLModelId) < 1 { invalidParams.Add(request.NewErrParamMinLen("MLModelId", 1)) } if invalidParams.Len() > 0 { return invalidParams } return nil } // SetMLModelId sets the MLModelId field's value. func (s UpdateMLModelInput) SetMLModelId(v string) UpdateMLModelInput { s.MLModelId = &v return s } // SetMLModelName sets the MLModelName field's value. func (s UpdateMLModelInput) SetMLModelName(v string) UpdateMLModelInput { s.MLModelName = &v return s } // SetScoreThreshold sets the ScoreThreshold field's value. func (s UpdateMLModelInput) SetScoreThreshold(v float64) UpdateMLModelInput { s.ScoreThreshold = &v return s } // Represents the output of an UpdateMLModel operation. // // You can see the updated content by using the GetMLModel operation. type UpdateMLModelOutput struct { _ struct{} `type:"structure"` // The ID assigned to the MLModel during creation. This value should be identical // to the value of the MLModelID in the request. MLModelId string `min:"1" type:"string"` } // String returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateMLModelOutput) String() string { return awsutil.Prettify(s) } // GoString returns the string representation. // // API parameter values that are decorated as "sensitive" in the API will not // be included in the string output. The member name will be present, but the // value will be replaced with "sensitive". func (s UpdateMLModelOutput) GoString() string { return s.String() } // SetMLModelId sets the MLModelId field's value. func (s UpdateMLModelOutput) SetMLModelId(v string) *UpdateMLModelOutput { s.MLModelId = &v return s } // The function used to train an MLModel. Training choices supported by Amazon // ML include the following: // // - SGD - Stochastic Gradient Descent. // // - RandomForest - Random forest of decision trees. const ( // AlgorithmSgd is a Algorithm enum value AlgorithmSgd = "sgd" ) // Algorithm_Values returns all elements of the Algorithm enum func Algorithm_Values() []string { return []string{ AlgorithmSgd, } } // A list of the variables to use in searching or filtering BatchPrediction. // // - CreatedAt - Sets the search criteria to BatchPrediction creation date. // // - Status - Sets the search criteria to BatchPrediction status. // // - Name - Sets the search criteria to the contents of BatchPrediction Name. // // - IAMUser - Sets the search criteria to the user account that invoked // the BatchPrediction creation. // // - MLModelId - Sets the search criteria to the MLModel used in the BatchPrediction. // // - DataSourceId - Sets the search criteria to the DataSource used in the // BatchPrediction. // // - DataURI - Sets the search criteria to the data file(s) used in the BatchPrediction. // The URL can identify either a file or an Amazon Simple Storage Service // (Amazon S3) bucket or directory. const ( // BatchPredictionFilterVariableCreatedAt is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableCreatedAt = "CreatedAt" // BatchPredictionFilterVariableLastUpdatedAt is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableLastUpdatedAt = "LastUpdatedAt" // BatchPredictionFilterVariableStatus is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableStatus = "Status" // BatchPredictionFilterVariableName is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableName = "Name" // BatchPredictionFilterVariableIamuser is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableIamuser = "IAMUser" // BatchPredictionFilterVariableMlmodelId is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableMlmodelId = "MLModelId" // BatchPredictionFilterVariableDataSourceId is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableDataSourceId = "DataSourceId" // BatchPredictionFilterVariableDataUri is a BatchPredictionFilterVariable enum value BatchPredictionFilterVariableDataUri = "DataURI" ) // BatchPredictionFilterVariable_Values returns all elements of the BatchPredictionFilterVariable enum func BatchPredictionFilterVariable_Values() []string { return []string{ BatchPredictionFilterVariableCreatedAt, BatchPredictionFilterVariableLastUpdatedAt, BatchPredictionFilterVariableStatus, BatchPredictionFilterVariableName, BatchPredictionFilterVariableIamuser, BatchPredictionFilterVariableMlmodelId, BatchPredictionFilterVariableDataSourceId, BatchPredictionFilterVariableDataUri, } } // A list of the variables to use in searching or filtering DataSource. // // - CreatedAt - Sets the search criteria to DataSource creation date. // // - Status - Sets the search criteria to DataSource status. // // - Name - Sets the search criteria to the contents of DataSource Name. // // - DataUri - Sets the search criteria to the URI of data files used to // create the DataSource. The URI can identify either a file or an Amazon // Simple Storage Service (Amazon S3) bucket or directory. // // - IAMUser - Sets the search criteria to the user account that invoked // the DataSource creation. // // Note: The variable names should match the variable names in the DataSource. const ( // DataSourceFilterVariableCreatedAt is a DataSourceFilterVariable enum value DataSourceFilterVariableCreatedAt = "CreatedAt" // DataSourceFilterVariableLastUpdatedAt is a DataSourceFilterVariable enum value DataSourceFilterVariableLastUpdatedAt = "LastUpdatedAt" // DataSourceFilterVariableStatus is a DataSourceFilterVariable enum value DataSourceFilterVariableStatus = "Status" // DataSourceFilterVariableName is a DataSourceFilterVariable enum value DataSourceFilterVariableName = "Name" // DataSourceFilterVariableDataLocationS3 is a DataSourceFilterVariable enum value DataSourceFilterVariableDataLocationS3 = "DataLocationS3" // DataSourceFilterVariableIamuser is a DataSourceFilterVariable enum value DataSourceFilterVariableIamuser = "IAMUser" ) // DataSourceFilterVariable_Values returns all elements of the DataSourceFilterVariable enum func DataSourceFilterVariable_Values() []string { return []string{ DataSourceFilterVariableCreatedAt, DataSourceFilterVariableLastUpdatedAt, DataSourceFilterVariableStatus, DataSourceFilterVariableName, DataSourceFilterVariableDataLocationS3, DataSourceFilterVariableIamuser, } } // Contains the key values of DetailsMap: // // - PredictiveModelType - Indicates the type of the MLModel. // // - Algorithm - Indicates the algorithm that was used for the MLModel. const ( // DetailsAttributesPredictiveModelType is a DetailsAttributes enum value DetailsAttributesPredictiveModelType = "PredictiveModelType" // DetailsAttributesAlgorithm is a DetailsAttributes enum value DetailsAttributesAlgorithm = "Algorithm" ) // DetailsAttributes_Values returns all elements of the DetailsAttributes enum func DetailsAttributes_Values() []string { return []string{ DetailsAttributesPredictiveModelType, DetailsAttributesAlgorithm, } } // Object status with the following possible values: // // - PENDING // // - INPROGRESS // // - FAILED // // - COMPLETED // // - DELETED const ( // EntityStatusPending is a EntityStatus enum value EntityStatusPending = "PENDING" // EntityStatusInprogress is a EntityStatus enum value EntityStatusInprogress = "INPROGRESS" // EntityStatusFailed is a EntityStatus enum value EntityStatusFailed = "FAILED" // EntityStatusCompleted is a EntityStatus enum value EntityStatusCompleted = "COMPLETED" // EntityStatusDeleted is a EntityStatus enum value EntityStatusDeleted = "DELETED" ) // EntityStatus_Values returns all elements of the EntityStatus enum func EntityStatus_Values() []string { return []string{ EntityStatusPending, EntityStatusInprogress, EntityStatusFailed, EntityStatusCompleted, EntityStatusDeleted, } } // A list of the variables to use in searching or filtering Evaluation. // // - CreatedAt - Sets the search criteria to Evaluation creation date. // // - Status - Sets the search criteria to Evaluation status. // // - Name - Sets the search criteria to the contents of Evaluation Name. // // - IAMUser - Sets the search criteria to the user account that invoked // an evaluation. // // - MLModelId - Sets the search criteria to the Predictor that was evaluated. // // - DataSourceId - Sets the search criteria to the DataSource used in evaluation. // // - DataUri - Sets the search criteria to the data file(s) used in evaluation. // The URL can identify either a file or an Amazon Simple Storage Service // (Amazon S3) bucket or directory. const ( // EvaluationFilterVariableCreatedAt is a EvaluationFilterVariable enum value EvaluationFilterVariableCreatedAt = "CreatedAt" // EvaluationFilterVariableLastUpdatedAt is a EvaluationFilterVariable enum value EvaluationFilterVariableLastUpdatedAt = "LastUpdatedAt" // EvaluationFilterVariableStatus is a EvaluationFilterVariable enum value EvaluationFilterVariableStatus = "Status" // EvaluationFilterVariableName is a EvaluationFilterVariable enum value EvaluationFilterVariableName = "Name" // EvaluationFilterVariableIamuser is a EvaluationFilterVariable enum value EvaluationFilterVariableIamuser = "IAMUser" // EvaluationFilterVariableMlmodelId is a EvaluationFilterVariable enum value EvaluationFilterVariableMlmodelId = "MLModelId" // EvaluationFilterVariableDataSourceId is a EvaluationFilterVariable enum value EvaluationFilterVariableDataSourceId = "DataSourceId" // EvaluationFilterVariableDataUri is a EvaluationFilterVariable enum value EvaluationFilterVariableDataUri = "DataURI" ) // EvaluationFilterVariable_Values returns all elements of the EvaluationFilterVariable enum func EvaluationFilterVariable_Values() []string { return []string{ EvaluationFilterVariableCreatedAt, EvaluationFilterVariableLastUpdatedAt, EvaluationFilterVariableStatus, EvaluationFilterVariableName, EvaluationFilterVariableIamuser, EvaluationFilterVariableMlmodelId, EvaluationFilterVariableDataSourceId, EvaluationFilterVariableDataUri, } } const ( // MLModelFilterVariableCreatedAt is a MLModelFilterVariable enum value MLModelFilterVariableCreatedAt = "CreatedAt" // MLModelFilterVariableLastUpdatedAt is a MLModelFilterVariable enum value MLModelFilterVariableLastUpdatedAt = "LastUpdatedAt" // MLModelFilterVariableStatus is a MLModelFilterVariable enum value MLModelFilterVariableStatus = "Status" // MLModelFilterVariableName is a MLModelFilterVariable enum value MLModelFilterVariableName = "Name" // MLModelFilterVariableIamuser is a MLModelFilterVariable enum value MLModelFilterVariableIamuser = "IAMUser" // MLModelFilterVariableTrainingDataSourceId is a MLModelFilterVariable enum value MLModelFilterVariableTrainingDataSourceId = "TrainingDataSourceId" // MLModelFilterVariableRealtimeEndpointStatus is a MLModelFilterVariable enum value MLModelFilterVariableRealtimeEndpointStatus = "RealtimeEndpointStatus" // MLModelFilterVariableMlmodelType is a MLModelFilterVariable enum value MLModelFilterVariableMlmodelType = "MLModelType" // MLModelFilterVariableAlgorithm is a MLModelFilterVariable enum value MLModelFilterVariableAlgorithm = "Algorithm" // MLModelFilterVariableTrainingDataUri is a MLModelFilterVariable enum value MLModelFilterVariableTrainingDataUri = "TrainingDataURI" ) // MLModelFilterVariable_Values returns all elements of the MLModelFilterVariable enum func MLModelFilterVariable_Values() []string { return []string{ MLModelFilterVariableCreatedAt, MLModelFilterVariableLastUpdatedAt, MLModelFilterVariableStatus, MLModelFilterVariableName, MLModelFilterVariableIamuser, MLModelFilterVariableTrainingDataSourceId, MLModelFilterVariableRealtimeEndpointStatus, MLModelFilterVariableMlmodelType, MLModelFilterVariableAlgorithm, MLModelFilterVariableTrainingDataUri, } } const ( // MLModelTypeRegression is a MLModelType enum value MLModelTypeRegression = "REGRESSION" // MLModelTypeBinary is a MLModelType enum value MLModelTypeBinary = "BINARY" // MLModelTypeMulticlass is a MLModelType enum value MLModelTypeMulticlass = "MULTICLASS" ) // MLModelType_Values returns all elements of the MLModelType enum func MLModelType_Values() []string { return []string{ MLModelTypeRegression, MLModelTypeBinary, MLModelTypeMulticlass, } } const ( // RealtimeEndpointStatusNone is a RealtimeEndpointStatus enum value RealtimeEndpointStatusNone = "NONE" // RealtimeEndpointStatusReady is a RealtimeEndpointStatus enum value RealtimeEndpointStatusReady = "READY" // RealtimeEndpointStatusUpdating is a RealtimeEndpointStatus enum value RealtimeEndpointStatusUpdating = "UPDATING" // RealtimeEndpointStatusFailed is a RealtimeEndpointStatus enum value RealtimeEndpointStatusFailed = "FAILED" ) // RealtimeEndpointStatus_Values returns all elements of the RealtimeEndpointStatus enum func RealtimeEndpointStatus_Values() []string { return []string{ RealtimeEndpointStatusNone, RealtimeEndpointStatusReady, RealtimeEndpointStatusUpdating, RealtimeEndpointStatusFailed, } } // The sort order specified in a listing condition. Possible values include // the following: // // - asc - Present the information in ascending order (from A-Z). // // - dsc - Present the information in descending order (from Z-A). const ( // SortOrderAsc is a SortOrder enum value SortOrderAsc = "asc" // SortOrderDsc is a SortOrder enum value SortOrderDsc = "dsc" ) // SortOrder_Values returns all elements of the SortOrder enum func SortOrder_Values() []string { return []string{ SortOrderAsc, SortOrderDsc, } } const ( // TaggableResourceTypeBatchPrediction is a TaggableResourceType enum value TaggableResourceTypeBatchPrediction = "BatchPrediction" // TaggableResourceTypeDataSource is a TaggableResourceType enum value TaggableResourceTypeDataSource = "DataSource" // TaggableResourceTypeEvaluation is a TaggableResourceType enum value TaggableResourceTypeEvaluation = "Evaluation" // TaggableResourceTypeMlmodel is a TaggableResourceType enum value TaggableResourceTypeMlmodel = "MLModel" ) // TaggableResourceType_Values returns all elements of the TaggableResourceType enum func TaggableResourceType_Values() []string { return []string{ TaggableResourceTypeBatchPrediction, TaggableResourceTypeDataSource, TaggableResourceTypeEvaluation, TaggableResourceTypeMlmodel, } }	356.39 KB	2025-05-25 12:27
📄 customizations.go package machinelearning import ( "net/url" "github.com/aws/aws-sdk-go/aws/request" ) func init() { initRequest = func(r request.Request) { switch r.Operation.Name { case opPredict: r.Handlers.Build.PushBack(updatePredictEndpoint) } } } // updatePredictEndpoint rewrites the request endpoint to use the // "PredictEndpoint" parameter of the Predict operation. func updatePredictEndpoint(r request.Request) { if !r.ParamsFilled() { return } r.ClientInfo.Endpoint = r.Params.(PredictInput).PredictEndpoint uri, err := url.Parse(r.ClientInfo.Endpoint) if err != nil { r.Error = err return } r.HTTPRequest.URL = uri }	649 B	2025-05-25 12:27
📄 customizations_test.go package machinelearning_test import ( "bytes" "io/ioutil" "net/http" "testing" "github.com/aws/aws-sdk-go/aws" "github.com/aws/aws-sdk-go/aws/request" "github.com/aws/aws-sdk-go/awstesting/unit" "github.com/aws/aws-sdk-go/service/machinelearning" ) func TestPredictEndpoint(t testing.T) { ml := machinelearning.New(unit.Session) ml.Handlers.Send.Clear() ml.Handlers.Send.PushBack(func(r request.Request) { r.HTTPResponse = &http.Response{ StatusCode: 200, Header: http.Header{}, Body: ioutil.NopCloser(bytes.NewReader([]byte("{}"))), } }) req, _ := ml.PredictRequest(&machinelearning.PredictInput{ PredictEndpoint: aws.String("https://localhost/endpoint"), MLModelId: aws.String("id"), Record: map[string]*string{}, }) err := req.Send() if err != nil { t.Errorf("expect no error, got %v", err) } if e, a := "https://localhost/endpoint", req.HTTPRequest.URL.String(); e != a { t.Errorf("expect %v, got %v", e, a) } }	990 B	2025-05-25 12:27
📄 doc.go // Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT. // Package machinelearning provides the client and types for making API // requests to Amazon Machine Learning. // // # Definition of the public APIs exposed by Amazon Machine Learning // // See machinelearning package documentation for more information. // https://docs.aws.amazon.com/sdk-for-go/api/service/machinelearning/ // // # Using the Client // // To contact Amazon Machine Learning with the SDK use the New function to create // a new service client. With that client you can make API requests to the service. // These clients are safe to use concurrently. // // See the SDK's documentation for more information on how to use the SDK. // https://docs.aws.amazon.com/sdk-for-go/api/ // // See aws.Config documentation for more information on configuring SDK clients. // https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config // // See the Amazon Machine Learning client MachineLearning for more // information on creating client for this service. // https://docs.aws.amazon.com/sdk-for-go/api/service/machinelearning/#New package machinelearning	1.1 KB	2025-05-25 12:27
📄 errors.go // Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT. package machinelearning import ( "github.com/aws/aws-sdk-go/private/protocol" ) const ( // ErrCodeIdempotentParameterMismatchException for service response error code // "IdempotentParameterMismatchException". // // A second request to use or change an object was not allowed. This can result // from retrying a request using a parameter that was not present in the original // request. ErrCodeIdempotentParameterMismatchException = "IdempotentParameterMismatchException" // ErrCodeInternalServerException for service response error code // "InternalServerException". // // An error on the server occurred when trying to process a request. ErrCodeInternalServerException = "InternalServerException" // ErrCodeInvalidInputException for service response error code // "InvalidInputException". // // An error on the client occurred. Typically, the cause is an invalid input // value. ErrCodeInvalidInputException = "InvalidInputException" // ErrCodeInvalidTagException for service response error code // "InvalidTagException". ErrCodeInvalidTagException = "InvalidTagException" // ErrCodeLimitExceededException for service response error code // "LimitExceededException". // // The subscriber exceeded the maximum number of operations. This exception // can occur when listing objects such as DataSource. ErrCodeLimitExceededException = "LimitExceededException" // ErrCodePredictorNotMountedException for service response error code // "PredictorNotMountedException". // // The exception is thrown when a predict request is made to an unmounted MLModel. ErrCodePredictorNotMountedException = "PredictorNotMountedException" // ErrCodeResourceNotFoundException for service response error code // "ResourceNotFoundException". // // A specified resource cannot be located. ErrCodeResourceNotFoundException = "ResourceNotFoundException" // ErrCodeTagLimitExceededException for service response error code // "TagLimitExceededException". ErrCodeTagLimitExceededException = "TagLimitExceededException" ) var exceptionFromCode = map[string]func(protocol.ResponseMetadata) error{ "IdempotentParameterMismatchException": newErrorIdempotentParameterMismatchException, "InternalServerException": newErrorInternalServerException, "InvalidInputException": newErrorInvalidInputException, "InvalidTagException": newErrorInvalidTagException, "LimitExceededException": newErrorLimitExceededException, "PredictorNotMountedException": newErrorPredictorNotMountedException, "ResourceNotFoundException": newErrorResourceNotFoundException, "TagLimitExceededException": newErrorTagLimitExceededException, }	2.73 KB	2025-05-25 12:27
📁 machinelearningiface	-	2025-05-25 12:27
📄 service.go // Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT. package machinelearning import ( "github.com/aws/aws-sdk-go/aws" "github.com/aws/aws-sdk-go/aws/client" "github.com/aws/aws-sdk-go/aws/client/metadata" "github.com/aws/aws-sdk-go/aws/request" "github.com/aws/aws-sdk-go/aws/signer/v4" "github.com/aws/aws-sdk-go/private/protocol" "github.com/aws/aws-sdk-go/private/protocol/jsonrpc" ) // MachineLearning provides the API operation methods for making requests to // Amazon Machine Learning. See this package's package overview docs // for details on the service. // // MachineLearning methods are safe to use concurrently. It is not safe to // modify mutate any of the struct's properties though. type MachineLearning struct { client.Client } // Used for custom client initialization logic var initClient func(client.Client) // Used for custom request initialization logic var initRequest func(request.Request) // Service information constants const ( ServiceName = "machinelearning" // Name of service. EndpointsID = ServiceName // ID to lookup a service endpoint with. ServiceID = "Machine Learning" // ServiceID is a unique identifier of a specific service. ) // New creates a new instance of the MachineLearning client with a session. // If additional configuration is needed for the client instance use the optional // aws.Config parameter to add your extra config. // // Example: // // mySession := session.Must(session.NewSession()) // // // Create a MachineLearning client from just a session. // svc := machinelearning.New(mySession) // // // Create a MachineLearning client with additional configuration // svc := machinelearning.New(mySession, aws.NewConfig().WithRegion("us-west-2")) func New(p client.ConfigProvider, cfgs ...aws.Config) MachineLearning { c := p.ClientConfig(EndpointsID, cfgs...) if c.SigningNameDerived \|\| len(c.SigningName) == 0 { c.SigningName = EndpointsID // No Fallback } return newClient(c.Config, c.Handlers, c.PartitionID, c.Endpoint, c.SigningRegion, c.SigningName, c.ResolvedRegion) } // newClient creates, initializes and returns a new service client instance. func newClient(cfg aws.Config, handlers request.Handlers, partitionID, endpoint, signingRegion, signingName, resolvedRegion string) MachineLearning { svc := &MachineLearning{ Client: client.New( cfg, metadata.ClientInfo{ ServiceName: ServiceName, ServiceID: ServiceID, SigningName: signingName, SigningRegion: signingRegion, PartitionID: partitionID, Endpoint: endpoint, APIVersion: "2014-12-12", ResolvedRegion: resolvedRegion, JSONVersion: "1.1", TargetPrefix: "AmazonML_20141212", }, handlers, ), } // Handlers svc.Handlers.Sign.PushBackNamed(v4.SignRequestHandler) svc.Handlers.Build.PushBackNamed(jsonrpc.BuildHandler) svc.Handlers.Unmarshal.PushBackNamed(jsonrpc.UnmarshalHandler) svc.Handlers.UnmarshalMeta.PushBackNamed(jsonrpc.UnmarshalMetaHandler) svc.Handlers.UnmarshalError.PushBackNamed( protocol.NewUnmarshalErrorHandler(jsonrpc.NewUnmarshalTypedError(exceptionFromCode)).NamedHandler(), ) // Run custom client initialization if present if initClient != nil { initClient(svc.Client) } return svc } // newRequest creates a new request for a MachineLearning operation and runs any // custom request initialization. func (c MachineLearning) newRequest(op request.Operation, params, data interface{}) request.Request { req := c.NewRequest(op, params, data) // Run custom request initialization if present if initRequest != nil { initRequest(req) } return req }	3.57 KB	2025-05-25 12:27
📄 waiters.go // Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT. package machinelearning import ( "time" "github.com/aws/aws-sdk-go/aws" "github.com/aws/aws-sdk-go/aws/request" ) // WaitUntilBatchPredictionAvailable uses the Amazon Machine Learning API operation // DescribeBatchPredictions to wait for a condition to be met before returning. // If the condition is not met within the max attempt window, an error will // be returned. func (c MachineLearning) WaitUntilBatchPredictionAvailable(input DescribeBatchPredictionsInput) error { return c.WaitUntilBatchPredictionAvailableWithContext(aws.BackgroundContext(), input) } // WaitUntilBatchPredictionAvailableWithContext is an extended version of WaitUntilBatchPredictionAvailable. // With the support for passing in a context and options to configure the // Waiter and the underlying request options. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) WaitUntilBatchPredictionAvailableWithContext(ctx aws.Context, input DescribeBatchPredictionsInput, opts ...request.WaiterOption) error { w := request.Waiter{ Name: "WaitUntilBatchPredictionAvailable", MaxAttempts: 60, Delay: request.ConstantWaiterDelay(30 * time.Second), Acceptors: []request.WaiterAcceptor{ { State: request.SuccessWaiterState, Matcher: request.PathAllWaiterMatch, Argument: "Results[].Status", Expected: "COMPLETED", }, { State: request.FailureWaiterState, Matcher: request.PathAnyWaiterMatch, Argument: "Results[].Status", Expected: "FAILED", }, }, Logger: c.Config.Logger, NewRequest: func(opts []request.Option) (request.Request, error) { var inCpy DescribeBatchPredictionsInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeBatchPredictionsRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } w.ApplyOptions(opts...) return w.WaitWithContext(ctx) } // WaitUntilDataSourceAvailable uses the Amazon Machine Learning API operation // DescribeDataSources to wait for a condition to be met before returning. // If the condition is not met within the max attempt window, an error will // be returned. func (c MachineLearning) WaitUntilDataSourceAvailable(input DescribeDataSourcesInput) error { return c.WaitUntilDataSourceAvailableWithContext(aws.BackgroundContext(), input) } // WaitUntilDataSourceAvailableWithContext is an extended version of WaitUntilDataSourceAvailable. // With the support for passing in a context and options to configure the // Waiter and the underlying request options. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) WaitUntilDataSourceAvailableWithContext(ctx aws.Context, input DescribeDataSourcesInput, opts ...request.WaiterOption) error { w := request.Waiter{ Name: "WaitUntilDataSourceAvailable", MaxAttempts: 60, Delay: request.ConstantWaiterDelay(30 time.Second), Acceptors: []request.WaiterAcceptor{ { State: request.SuccessWaiterState, Matcher: request.PathAllWaiterMatch, Argument: "Results[].Status", Expected: "COMPLETED", }, { State: request.FailureWaiterState, Matcher: request.PathAnyWaiterMatch, Argument: "Results[].Status", Expected: "FAILED", }, }, Logger: c.Config.Logger, NewRequest: func(opts []request.Option) (request.Request, error) { var inCpy DescribeDataSourcesInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeDataSourcesRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } w.ApplyOptions(opts...) return w.WaitWithContext(ctx) } // WaitUntilEvaluationAvailable uses the Amazon Machine Learning API operation // DescribeEvaluations to wait for a condition to be met before returning. // If the condition is not met within the max attempt window, an error will // be returned. func (c MachineLearning) WaitUntilEvaluationAvailable(input DescribeEvaluationsInput) error { return c.WaitUntilEvaluationAvailableWithContext(aws.BackgroundContext(), input) } // WaitUntilEvaluationAvailableWithContext is an extended version of WaitUntilEvaluationAvailable. // With the support for passing in a context and options to configure the // Waiter and the underlying request options. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) WaitUntilEvaluationAvailableWithContext(ctx aws.Context, input DescribeEvaluationsInput, opts ...request.WaiterOption) error { w := request.Waiter{ Name: "WaitUntilEvaluationAvailable", MaxAttempts: 60, Delay: request.ConstantWaiterDelay(30 time.Second), Acceptors: []request.WaiterAcceptor{ { State: request.SuccessWaiterState, Matcher: request.PathAllWaiterMatch, Argument: "Results[].Status", Expected: "COMPLETED", }, { State: request.FailureWaiterState, Matcher: request.PathAnyWaiterMatch, Argument: "Results[].Status", Expected: "FAILED", }, }, Logger: c.Config.Logger, NewRequest: func(opts []request.Option) (request.Request, error) { var inCpy DescribeEvaluationsInput if input != nil { tmp := input inCpy = &tmp } req, _ := c.DescribeEvaluationsRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } w.ApplyOptions(opts...) return w.WaitWithContext(ctx) } // WaitUntilMLModelAvailable uses the Amazon Machine Learning API operation // DescribeMLModels to wait for a condition to be met before returning. // If the condition is not met within the max attempt window, an error will // be returned. func (c MachineLearning) WaitUntilMLModelAvailable(input DescribeMLModelsInput) error { return c.WaitUntilMLModelAvailableWithContext(aws.BackgroundContext(), input) } // WaitUntilMLModelAvailableWithContext is an extended version of WaitUntilMLModelAvailable. // With the support for passing in a context and options to configure the // Waiter and the underlying request options. // // The context must be non-nil and will be used for request cancellation. If // the context is nil a panic will occur. In the future the SDK may create // sub-contexts for http.Requests. See https://golang.org/pkg/context/ // for more information on using Contexts. func (c MachineLearning) WaitUntilMLModelAvailableWithContext(ctx aws.Context, input DescribeMLModelsInput, opts ...request.WaiterOption) error { w := request.Waiter{ Name: "WaitUntilMLModelAvailable", MaxAttempts: 60, Delay: request.ConstantWaiterDelay(30 time.Second), Acceptors: []request.WaiterAcceptor{ { State: request.SuccessWaiterState, Matcher: request.PathAllWaiterMatch, Argument: "Results[].Status", Expected: "COMPLETED", }, { State: request.FailureWaiterState, Matcher: request.PathAnyWaiterMatch, Argument: "Results[].Status", Expected: "FAILED", }, }, Logger: c.Config.Logger, NewRequest: func(opts []request.Option) (request.Request, error) { var inCpy DescribeMLModelsInput if input != nil { tmp := *input inCpy = &tmp } req, _ := c.DescribeMLModelsRequest(inCpy) req.SetContext(ctx) req.ApplyOptions(opts...) return req, nil }, } w.ApplyOptions(opts...) return w.WaitWithContext(ctx) }	7.81 KB	2025-05-25 12:27

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