Switch to using the dep tool and update all the dependencies

vendor/github.com/aws/aws-sdk-go/service/machinelearning/customizations.go

@@ -0,0 +1,33 @@
+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
+}

vendor/github.com/aws/aws-sdk-go/service/machinelearning/customizations_test.go

@@ -0,0 +1,37 @@
+package machinelearning_test
+
+import (
+	"bytes"
+	"io/ioutil"
+	"net/http"
+	"testing"
+
+	"github.com/stretchr/testify/assert"
+
+	"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()
+
+	assert.Nil(t, err)
+	assert.Equal(t, "https://localhost/endpoint", req.HTTPRequest.URL.String())
+}

vendor/github.com/aws/aws-sdk-go/service/machinelearning/doc.go

@@ -0,0 +1,78 @@
+// 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 use the client for Amazon Machine Learning you will first need
+// to create a new instance of it.
+//
+// When creating a client for an AWS service you'll first need to have a Session
+// already created. The Session provides configuration that can be shared
+// between multiple service clients. Additional configuration can be applied to
+// the Session and service's client when they are constructed. The aws package's
+// Config type contains several fields such as Region for the AWS Region the
+// client should make API requests too. The optional Config value can be provided
+// as the variadic argument for Sessions and client creation.
+//
+// Once the service's client is created you can use it to make API requests the
+// AWS service. These clients are safe to use concurrently.
+//
+//   // Create a session to share configuration, and load external configuration.
+//   sess := session.Must(session.NewSession())
+//
+//   // Create the service's client with the session.
+//   svc := machinelearning.New(sess)
+//
+// See the SDK's documentation for more information on how to use service clients.
+// https://docs.aws.amazon.com/sdk-for-go/api/
+//
+// See aws package's Config type for more information on configuration options.
+// https://docs.aws.amazon.com/sdk-for-go/api/aws/#Config
+//
+// See the Amazon Machine Learning client MachineLearning for more
+// information on creating the service's client.
+// https://docs.aws.amazon.com/sdk-for-go/api/service/machinelearning/#New
+//
+// Once the client is created you can make an API request to the service.
+// Each API method takes a input parameter, and returns the service response
+// and an error.
+//
+// The API method will document which error codes the service can be returned
+// by the operation if the service models the API operation's errors. These
+// errors will also be available as const strings prefixed with "ErrCode".
+//
+//   result, err := svc.AddTags(params)
+//   if err != nil {
+//       // Cast err to awserr.Error to handle specific error codes.
+//       aerr, ok := err.(awserr.Error)
+//       if ok && aerr.Code() == <error code to check for> {
+//           // Specific error code handling
+//       }
+//       return err
+//   }
+//
+//   fmt.Println("AddTags result:")
+//   fmt.Println(result)
+//
+// Using the Client with Context
+//
+// The service's client also provides methods to make API requests with a Context
+// value. This allows you to control the timeout, and cancellation of pending
+// requests. These methods also take request Option as variadic parameter to apply
+// additional configuration to the API request.
+//
+//   ctx := context.Background()
+//
+//   result, err := svc.AddTagsWithContext(ctx, params)
+//
+// See the request package documentation for more information on using Context pattern
+// with the SDK.
+// https://docs.aws.amazon.com/sdk-for-go/api/aws/request/
+package machinelearning

vendor/github.com/aws/aws-sdk-go/service/machinelearning/errors.go

@@ -0,0 +1,54 @@
+// Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT.
+
+package machinelearning
+
+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"
+)

vendor/github.com/aws/aws-sdk-go/service/machinelearning/examples_test.go

@@ -0,0 +1,737 @@
+// Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT.
+
+package machinelearning_test
+
+import (
+	"bytes"
+	"fmt"
+	"time"
+
+	"github.com/aws/aws-sdk-go/aws"
+	"github.com/aws/aws-sdk-go/aws/session"
+	"github.com/aws/aws-sdk-go/service/machinelearning"
+)
+
+var _ time.Duration
+var _ bytes.Buffer
+
+func ExampleMachineLearning_AddTags() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.AddTagsInput{
+		ResourceId:   aws.String("EntityId"),             // Required
+		ResourceType: aws.String("TaggableResourceType"), // Required
+		Tags: []*machinelearning.Tag{ // Required
+			{ // Required
+				Key:   aws.String("TagKey"),
+				Value: aws.String("TagValue"),
+			},
+			// More values...
+		},
+	}
+	resp, err := svc.AddTags(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateBatchPrediction() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateBatchPredictionInput{
+		BatchPredictionDataSourceId: aws.String("EntityId"), // Required
+		BatchPredictionId:           aws.String("EntityId"), // Required
+		MLModelId:                   aws.String("EntityId"), // Required
+		OutputUri:                   aws.String("S3Url"),    // Required
+		BatchPredictionName:         aws.String("EntityName"),
+	}
+	resp, err := svc.CreateBatchPrediction(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateDataSourceFromRDS() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateDataSourceFromRDSInput{
+		DataSourceId: aws.String("EntityId"), // Required
+		RDSData: &machinelearning.RDSDataSpec{ // Required
+			DatabaseCredentials: &machinelearning.RDSDatabaseCredentials{ // Required
+				Password: aws.String("RDSDatabasePassword"), // Required
+				Username: aws.String("RDSDatabaseUsername"), // Required
+			},
+			DatabaseInformation: &machinelearning.RDSDatabase{ // Required
+				DatabaseName:       aws.String("RDSDatabaseName"),       // Required
+				InstanceIdentifier: aws.String("RDSInstanceIdentifier"), // Required
+			},
+			ResourceRole:      aws.String("EDPResourceRole"), // Required
+			S3StagingLocation: aws.String("S3Url"),           // Required
+			SecurityGroupIds: []*string{ // Required
+				aws.String("EDPSecurityGroupId"), // Required
+				// More values...
+			},
+			SelectSqlQuery:    aws.String("RDSSelectSqlQuery"), // Required
+			ServiceRole:       aws.String("EDPServiceRole"),    // Required
+			SubnetId:          aws.String("EDPSubnetId"),       // Required
+			DataRearrangement: aws.String("DataRearrangement"),
+			DataSchema:        aws.String("DataSchema"),
+			DataSchemaUri:     aws.String("S3Url"),
+		},
+		RoleARN:           aws.String("RoleARN"), // Required
+		ComputeStatistics: aws.Bool(true),
+		DataSourceName:    aws.String("EntityName"),
+	}
+	resp, err := svc.CreateDataSourceFromRDS(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateDataSourceFromRedshift() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateDataSourceFromRedshiftInput{
+		DataSourceId: aws.String("EntityId"), // Required
+		DataSpec: &machinelearning.RedshiftDataSpec{ // Required
+			DatabaseCredentials: &machinelearning.RedshiftDatabaseCredentials{ // Required
+				Password: aws.String("RedshiftDatabasePassword"), // Required
+				Username: aws.String("RedshiftDatabaseUsername"), // Required
+			},
+			DatabaseInformation: &machinelearning.RedshiftDatabase{ // Required
+				ClusterIdentifier: aws.String("RedshiftClusterIdentifier"), // Required
+				DatabaseName:      aws.String("RedshiftDatabaseName"),      // Required
+			},
+			S3StagingLocation: aws.String("S3Url"),                  // Required
+			SelectSqlQuery:    aws.String("RedshiftSelectSqlQuery"), // Required
+			DataRearrangement: aws.String("DataRearrangement"),
+			DataSchema:        aws.String("DataSchema"),
+			DataSchemaUri:     aws.String("S3Url"),
+		},
+		RoleARN:           aws.String("RoleARN"), // Required
+		ComputeStatistics: aws.Bool(true),
+		DataSourceName:    aws.String("EntityName"),
+	}
+	resp, err := svc.CreateDataSourceFromRedshift(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateDataSourceFromS3() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateDataSourceFromS3Input{
+		DataSourceId: aws.String("EntityId"), // Required
+		DataSpec: &machinelearning.S3DataSpec{ // Required
+			DataLocationS3:       aws.String("S3Url"), // Required
+			DataRearrangement:    aws.String("DataRearrangement"),
+			DataSchema:           aws.String("DataSchema"),
+			DataSchemaLocationS3: aws.String("S3Url"),
+		},
+		ComputeStatistics: aws.Bool(true),
+		DataSourceName:    aws.String("EntityName"),
+	}
+	resp, err := svc.CreateDataSourceFromS3(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateEvaluation() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateEvaluationInput{
+		EvaluationDataSourceId: aws.String("EntityId"), // Required
+		EvaluationId:           aws.String("EntityId"), // Required
+		MLModelId:              aws.String("EntityId"), // Required
+		EvaluationName:         aws.String("EntityName"),
+	}
+	resp, err := svc.CreateEvaluation(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateMLModel() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateMLModelInput{
+		MLModelId:            aws.String("EntityId"),    // Required
+		MLModelType:          aws.String("MLModelType"), // Required
+		TrainingDataSourceId: aws.String("EntityId"),    // Required
+		MLModelName:          aws.String("EntityName"),
+		Parameters: map[string]*string{
+			"Key": aws.String("StringType"), // Required
+			// More values...
+		},
+		Recipe:    aws.String("Recipe"),
+		RecipeUri: aws.String("S3Url"),
+	}
+	resp, err := svc.CreateMLModel(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_CreateRealtimeEndpoint() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.CreateRealtimeEndpointInput{
+		MLModelId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.CreateRealtimeEndpoint(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DeleteBatchPrediction() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DeleteBatchPredictionInput{
+		BatchPredictionId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.DeleteBatchPrediction(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DeleteDataSource() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DeleteDataSourceInput{
+		DataSourceId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.DeleteDataSource(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DeleteEvaluation() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DeleteEvaluationInput{
+		EvaluationId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.DeleteEvaluation(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DeleteMLModel() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DeleteMLModelInput{
+		MLModelId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.DeleteMLModel(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DeleteRealtimeEndpoint() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DeleteRealtimeEndpointInput{
+		MLModelId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.DeleteRealtimeEndpoint(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DeleteTags() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DeleteTagsInput{
+		ResourceId:   aws.String("EntityId"),             // Required
+		ResourceType: aws.String("TaggableResourceType"), // Required
+		TagKeys: []*string{ // Required
+			aws.String("TagKey"), // Required
+			// More values...
+		},
+	}
+	resp, err := svc.DeleteTags(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DescribeBatchPredictions() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DescribeBatchPredictionsInput{
+		EQ:             aws.String("ComparatorValue"),
+		FilterVariable: aws.String("BatchPredictionFilterVariable"),
+		GE:             aws.String("ComparatorValue"),
+		GT:             aws.String("ComparatorValue"),
+		LE:             aws.String("ComparatorValue"),
+		LT:             aws.String("ComparatorValue"),
+		Limit:          aws.Int64(1),
+		NE:             aws.String("ComparatorValue"),
+		NextToken:      aws.String("StringType"),
+		Prefix:         aws.String("ComparatorValue"),
+		SortOrder:      aws.String("SortOrder"),
+	}
+	resp, err := svc.DescribeBatchPredictions(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DescribeDataSources() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DescribeDataSourcesInput{
+		EQ:             aws.String("ComparatorValue"),
+		FilterVariable: aws.String("DataSourceFilterVariable"),
+		GE:             aws.String("ComparatorValue"),
+		GT:             aws.String("ComparatorValue"),
+		LE:             aws.String("ComparatorValue"),
+		LT:             aws.String("ComparatorValue"),
+		Limit:          aws.Int64(1),
+		NE:             aws.String("ComparatorValue"),
+		NextToken:      aws.String("StringType"),
+		Prefix:         aws.String("ComparatorValue"),
+		SortOrder:      aws.String("SortOrder"),
+	}
+	resp, err := svc.DescribeDataSources(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DescribeEvaluations() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DescribeEvaluationsInput{
+		EQ:             aws.String("ComparatorValue"),
+		FilterVariable: aws.String("EvaluationFilterVariable"),
+		GE:             aws.String("ComparatorValue"),
+		GT:             aws.String("ComparatorValue"),
+		LE:             aws.String("ComparatorValue"),
+		LT:             aws.String("ComparatorValue"),
+		Limit:          aws.Int64(1),
+		NE:             aws.String("ComparatorValue"),
+		NextToken:      aws.String("StringType"),
+		Prefix:         aws.String("ComparatorValue"),
+		SortOrder:      aws.String("SortOrder"),
+	}
+	resp, err := svc.DescribeEvaluations(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DescribeMLModels() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DescribeMLModelsInput{
+		EQ:             aws.String("ComparatorValue"),
+		FilterVariable: aws.String("MLModelFilterVariable"),
+		GE:             aws.String("ComparatorValue"),
+		GT:             aws.String("ComparatorValue"),
+		LE:             aws.String("ComparatorValue"),
+		LT:             aws.String("ComparatorValue"),
+		Limit:          aws.Int64(1),
+		NE:             aws.String("ComparatorValue"),
+		NextToken:      aws.String("StringType"),
+		Prefix:         aws.String("ComparatorValue"),
+		SortOrder:      aws.String("SortOrder"),
+	}
+	resp, err := svc.DescribeMLModels(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_DescribeTags() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.DescribeTagsInput{
+		ResourceId:   aws.String("EntityId"),             // Required
+		ResourceType: aws.String("TaggableResourceType"), // Required
+	}
+	resp, err := svc.DescribeTags(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_GetBatchPrediction() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.GetBatchPredictionInput{
+		BatchPredictionId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.GetBatchPrediction(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_GetDataSource() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.GetDataSourceInput{
+		DataSourceId: aws.String("EntityId"), // Required
+		Verbose:      aws.Bool(true),
+	}
+	resp, err := svc.GetDataSource(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_GetEvaluation() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.GetEvaluationInput{
+		EvaluationId: aws.String("EntityId"), // Required
+	}
+	resp, err := svc.GetEvaluation(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_GetMLModel() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.GetMLModelInput{
+		MLModelId: aws.String("EntityId"), // Required
+		Verbose:   aws.Bool(true),
+	}
+	resp, err := svc.GetMLModel(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_Predict() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.PredictInput{
+		MLModelId:       aws.String("EntityId"), // Required
+		PredictEndpoint: aws.String("VipURL"),   // Required
+		Record: map[string]*string{ // Required
+			"Key": aws.String("VariableValue"), // Required
+			// More values...
+		},
+	}
+	resp, err := svc.Predict(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_UpdateBatchPrediction() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.UpdateBatchPredictionInput{
+		BatchPredictionId:   aws.String("EntityId"),   // Required
+		BatchPredictionName: aws.String("EntityName"), // Required
+	}
+	resp, err := svc.UpdateBatchPrediction(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_UpdateDataSource() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.UpdateDataSourceInput{
+		DataSourceId:   aws.String("EntityId"),   // Required
+		DataSourceName: aws.String("EntityName"), // Required
+	}
+	resp, err := svc.UpdateDataSource(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_UpdateEvaluation() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.UpdateEvaluationInput{
+		EvaluationId:   aws.String("EntityId"),   // Required
+		EvaluationName: aws.String("EntityName"), // Required
+	}
+	resp, err := svc.UpdateEvaluation(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}
+
+func ExampleMachineLearning_UpdateMLModel() {
+	sess := session.Must(session.NewSession())
+
+	svc := machinelearning.New(sess)
+
+	params := &machinelearning.UpdateMLModelInput{
+		MLModelId:      aws.String("EntityId"), // Required
+		MLModelName:    aws.String("EntityName"),
+		ScoreThreshold: aws.Float64(1.0),
+	}
+	resp, err := svc.UpdateMLModel(params)
+
+	if err != nil {
+		// Print the error, cast err to awserr.Error to get the Code and
+		// Message from an error.
+		fmt.Println(err.Error())
+		return
+	}
+
+	// Pretty-print the response data.
+	fmt.Println(resp)
+}

vendor/github.com/aws/aws-sdk-go/service/machinelearning/machinelearningiface/interface.go

@@ -0,0 +1,200 @@
+// Code generated by private/model/cli/gen-api/main.go. DO NOT EDIT.
+
+// Package machinelearningiface provides an interface to enable mocking the Amazon Machine Learning service client
+// for testing your code.
+//
+// It is important to note that this interface will have breaking changes
+// when the service model is updated and adds new API operations, paginators,
+// and waiters.
+package machinelearningiface
+
+import (
+	"github.com/aws/aws-sdk-go/aws"
+	"github.com/aws/aws-sdk-go/aws/request"
+	"github.com/aws/aws-sdk-go/service/machinelearning"
+)
+
+// MachineLearningAPI provides an interface to enable mocking the
+// machinelearning.MachineLearning service client's API operation,
+// paginators, and waiters. This make unit testing your code that calls out
+// to the SDK's service client's calls easier.
+//
+// The best way to use this interface is so the SDK's service client's calls
+// can be stubbed out for unit testing your code with the SDK without needing
+// to inject custom request handlers into the the SDK's request pipeline.
+//
+//    // myFunc uses an SDK service client to make a request to
+//    // Amazon Machine Learning.
+//    func myFunc(svc machinelearningiface.MachineLearningAPI) bool {
+//        // Make svc.AddTags request
+//    }
+//
+//    func main() {
+//        sess := session.New()
+//        svc := machinelearning.New(sess)
+//
+//        myFunc(svc)
+//    }
+//
+// In your _test.go file:
+//
+//    // Define a mock struct to be used in your unit tests of myFunc.
+//    type mockMachineLearningClient struct {
+//        machinelearningiface.MachineLearningAPI
+//    }
+//    func (m *mockMachineLearningClient) AddTags(input *machinelearning.AddTagsInput) (*machinelearning.AddTagsOutput, error) {
+//        // mock response/functionality
+//    }
+//
+//    func TestMyFunc(t *testing.T) {
+//        // Setup Test
+//        mockSvc := &mockMachineLearningClient{}
+//
+//        myfunc(mockSvc)
+//
+//        // Verify myFunc's functionality
+//    }
+//
+// It is important to note that this interface will have breaking changes
+// when the service model is updated and adds new API operations, paginators,
+// and waiters. Its suggested to use the pattern above for testing, or using
+// tooling to generate mocks to satisfy the interfaces.
+type MachineLearningAPI interface {
+	AddTags(*machinelearning.AddTagsInput) (*machinelearning.AddTagsOutput, error)
+	AddTagsWithContext(aws.Context, *machinelearning.AddTagsInput, ...request.Option) (*machinelearning.AddTagsOutput, error)
+	AddTagsRequest(*machinelearning.AddTagsInput) (*request.Request, *machinelearning.AddTagsOutput)
+
+	CreateBatchPrediction(*machinelearning.CreateBatchPredictionInput) (*machinelearning.CreateBatchPredictionOutput, error)
+	CreateBatchPredictionWithContext(aws.Context, *machinelearning.CreateBatchPredictionInput, ...request.Option) (*machinelearning.CreateBatchPredictionOutput, error)
+	CreateBatchPredictionRequest(*machinelearning.CreateBatchPredictionInput) (*request.Request, *machinelearning.CreateBatchPredictionOutput)
+
+	CreateDataSourceFromRDS(*machinelearning.CreateDataSourceFromRDSInput) (*machinelearning.CreateDataSourceFromRDSOutput, error)
+	CreateDataSourceFromRDSWithContext(aws.Context, *machinelearning.CreateDataSourceFromRDSInput, ...request.Option) (*machinelearning.CreateDataSourceFromRDSOutput, error)
+	CreateDataSourceFromRDSRequest(*machinelearning.CreateDataSourceFromRDSInput) (*request.Request, *machinelearning.CreateDataSourceFromRDSOutput)
+
+	CreateDataSourceFromRedshift(*machinelearning.CreateDataSourceFromRedshiftInput) (*machinelearning.CreateDataSourceFromRedshiftOutput, error)
+	CreateDataSourceFromRedshiftWithContext(aws.Context, *machinelearning.CreateDataSourceFromRedshiftInput, ...request.Option) (*machinelearning.CreateDataSourceFromRedshiftOutput, error)
+	CreateDataSourceFromRedshiftRequest(*machinelearning.CreateDataSourceFromRedshiftInput) (*request.Request, *machinelearning.CreateDataSourceFromRedshiftOutput)
+
+	CreateDataSourceFromS3(*machinelearning.CreateDataSourceFromS3Input) (*machinelearning.CreateDataSourceFromS3Output, error)
+	CreateDataSourceFromS3WithContext(aws.Context, *machinelearning.CreateDataSourceFromS3Input, ...request.Option) (*machinelearning.CreateDataSourceFromS3Output, error)
+	CreateDataSourceFromS3Request(*machinelearning.CreateDataSourceFromS3Input) (*request.Request, *machinelearning.CreateDataSourceFromS3Output)
+
+	CreateEvaluation(*machinelearning.CreateEvaluationInput) (*machinelearning.CreateEvaluationOutput, error)
+	CreateEvaluationWithContext(aws.Context, *machinelearning.CreateEvaluationInput, ...request.Option) (*machinelearning.CreateEvaluationOutput, error)
+	CreateEvaluationRequest(*machinelearning.CreateEvaluationInput) (*request.Request, *machinelearning.CreateEvaluationOutput)
+
+	CreateMLModel(*machinelearning.CreateMLModelInput) (*machinelearning.CreateMLModelOutput, error)
+	CreateMLModelWithContext(aws.Context, *machinelearning.CreateMLModelInput, ...request.Option) (*machinelearning.CreateMLModelOutput, error)
+	CreateMLModelRequest(*machinelearning.CreateMLModelInput) (*request.Request, *machinelearning.CreateMLModelOutput)
+
+	CreateRealtimeEndpoint(*machinelearning.CreateRealtimeEndpointInput) (*machinelearning.CreateRealtimeEndpointOutput, error)
+	CreateRealtimeEndpointWithContext(aws.Context, *machinelearning.CreateRealtimeEndpointInput, ...request.Option) (*machinelearning.CreateRealtimeEndpointOutput, error)
+	CreateRealtimeEndpointRequest(*machinelearning.CreateRealtimeEndpointInput) (*request.Request, *machinelearning.CreateRealtimeEndpointOutput)
+
+	DeleteBatchPrediction(*machinelearning.DeleteBatchPredictionInput) (*machinelearning.DeleteBatchPredictionOutput, error)
+	DeleteBatchPredictionWithContext(aws.Context, *machinelearning.DeleteBatchPredictionInput, ...request.Option) (*machinelearning.DeleteBatchPredictionOutput, error)
+	DeleteBatchPredictionRequest(*machinelearning.DeleteBatchPredictionInput) (*request.Request, *machinelearning.DeleteBatchPredictionOutput)
+
+	DeleteDataSource(*machinelearning.DeleteDataSourceInput) (*machinelearning.DeleteDataSourceOutput, error)
+	DeleteDataSourceWithContext(aws.Context, *machinelearning.DeleteDataSourceInput, ...request.Option) (*machinelearning.DeleteDataSourceOutput, error)
+	DeleteDataSourceRequest(*machinelearning.DeleteDataSourceInput) (*request.Request, *machinelearning.DeleteDataSourceOutput)
+
+	DeleteEvaluation(*machinelearning.DeleteEvaluationInput) (*machinelearning.DeleteEvaluationOutput, error)
+	DeleteEvaluationWithContext(aws.Context, *machinelearning.DeleteEvaluationInput, ...request.Option) (*machinelearning.DeleteEvaluationOutput, error)
+	DeleteEvaluationRequest(*machinelearning.DeleteEvaluationInput) (*request.Request, *machinelearning.DeleteEvaluationOutput)
+
+	DeleteMLModel(*machinelearning.DeleteMLModelInput) (*machinelearning.DeleteMLModelOutput, error)
+	DeleteMLModelWithContext(aws.Context, *machinelearning.DeleteMLModelInput, ...request.Option) (*machinelearning.DeleteMLModelOutput, error)
+	DeleteMLModelRequest(*machinelearning.DeleteMLModelInput) (*request.Request, *machinelearning.DeleteMLModelOutput)
+
+	DeleteRealtimeEndpoint(*machinelearning.DeleteRealtimeEndpointInput) (*machinelearning.DeleteRealtimeEndpointOutput, error)
+	DeleteRealtimeEndpointWithContext(aws.Context, *machinelearning.DeleteRealtimeEndpointInput, ...request.Option) (*machinelearning.DeleteRealtimeEndpointOutput, error)
+	DeleteRealtimeEndpointRequest(*machinelearning.DeleteRealtimeEndpointInput) (*request.Request, *machinelearning.DeleteRealtimeEndpointOutput)
+
+	DeleteTags(*machinelearning.DeleteTagsInput) (*machinelearning.DeleteTagsOutput, error)
+	DeleteTagsWithContext(aws.Context, *machinelearning.DeleteTagsInput, ...request.Option) (*machinelearning.DeleteTagsOutput, error)
+	DeleteTagsRequest(*machinelearning.DeleteTagsInput) (*request.Request, *machinelearning.DeleteTagsOutput)
+
+	DescribeBatchPredictions(*machinelearning.DescribeBatchPredictionsInput) (*machinelearning.DescribeBatchPredictionsOutput, error)
+	DescribeBatchPredictionsWithContext(aws.Context, *machinelearning.DescribeBatchPredictionsInput, ...request.Option) (*machinelearning.DescribeBatchPredictionsOutput, error)
+	DescribeBatchPredictionsRequest(*machinelearning.DescribeBatchPredictionsInput) (*request.Request, *machinelearning.DescribeBatchPredictionsOutput)
+
+	DescribeBatchPredictionsPages(*machinelearning.DescribeBatchPredictionsInput, func(*machinelearning.DescribeBatchPredictionsOutput, bool) bool) error
+	DescribeBatchPredictionsPagesWithContext(aws.Context, *machinelearning.DescribeBatchPredictionsInput, func(*machinelearning.DescribeBatchPredictionsOutput, bool) bool, ...request.Option) error
+
+	DescribeDataSources(*machinelearning.DescribeDataSourcesInput) (*machinelearning.DescribeDataSourcesOutput, error)
+	DescribeDataSourcesWithContext(aws.Context, *machinelearning.DescribeDataSourcesInput, ...request.Option) (*machinelearning.DescribeDataSourcesOutput, error)
+	DescribeDataSourcesRequest(*machinelearning.DescribeDataSourcesInput) (*request.Request, *machinelearning.DescribeDataSourcesOutput)
+
+	DescribeDataSourcesPages(*machinelearning.DescribeDataSourcesInput, func(*machinelearning.DescribeDataSourcesOutput, bool) bool) error
+	DescribeDataSourcesPagesWithContext(aws.Context, *machinelearning.DescribeDataSourcesInput, func(*machinelearning.DescribeDataSourcesOutput, bool) bool, ...request.Option) error
+
+	DescribeEvaluations(*machinelearning.DescribeEvaluationsInput) (*machinelearning.DescribeEvaluationsOutput, error)
+	DescribeEvaluationsWithContext(aws.Context, *machinelearning.DescribeEvaluationsInput, ...request.Option) (*machinelearning.DescribeEvaluationsOutput, error)
+	DescribeEvaluationsRequest(*machinelearning.DescribeEvaluationsInput) (*request.Request, *machinelearning.DescribeEvaluationsOutput)
+
+	DescribeEvaluationsPages(*machinelearning.DescribeEvaluationsInput, func(*machinelearning.DescribeEvaluationsOutput, bool) bool) error
+	DescribeEvaluationsPagesWithContext(aws.Context, *machinelearning.DescribeEvaluationsInput, func(*machinelearning.DescribeEvaluationsOutput, bool) bool, ...request.Option) error
+
+	DescribeMLModels(*machinelearning.DescribeMLModelsInput) (*machinelearning.DescribeMLModelsOutput, error)
+	DescribeMLModelsWithContext(aws.Context, *machinelearning.DescribeMLModelsInput, ...request.Option) (*machinelearning.DescribeMLModelsOutput, error)
+	DescribeMLModelsRequest(*machinelearning.DescribeMLModelsInput) (*request.Request, *machinelearning.DescribeMLModelsOutput)
+
+	DescribeMLModelsPages(*machinelearning.DescribeMLModelsInput, func(*machinelearning.DescribeMLModelsOutput, bool) bool) error
+	DescribeMLModelsPagesWithContext(aws.Context, *machinelearning.DescribeMLModelsInput, func(*machinelearning.DescribeMLModelsOutput, bool) bool, ...request.Option) error
+
+	DescribeTags(*machinelearning.DescribeTagsInput) (*machinelearning.DescribeTagsOutput, error)
+	DescribeTagsWithContext(aws.Context, *machinelearning.DescribeTagsInput, ...request.Option) (*machinelearning.DescribeTagsOutput, error)
+	DescribeTagsRequest(*machinelearning.DescribeTagsInput) (*request.Request, *machinelearning.DescribeTagsOutput)
+
+	GetBatchPrediction(*machinelearning.GetBatchPredictionInput) (*machinelearning.GetBatchPredictionOutput, error)
+	GetBatchPredictionWithContext(aws.Context, *machinelearning.GetBatchPredictionInput, ...request.Option) (*machinelearning.GetBatchPredictionOutput, error)
+	GetBatchPredictionRequest(*machinelearning.GetBatchPredictionInput) (*request.Request, *machinelearning.GetBatchPredictionOutput)
+
+	GetDataSource(*machinelearning.GetDataSourceInput) (*machinelearning.GetDataSourceOutput, error)
+	GetDataSourceWithContext(aws.Context, *machinelearning.GetDataSourceInput, ...request.Option) (*machinelearning.GetDataSourceOutput, error)
+	GetDataSourceRequest(*machinelearning.GetDataSourceInput) (*request.Request, *machinelearning.GetDataSourceOutput)
+
+	GetEvaluation(*machinelearning.GetEvaluationInput) (*machinelearning.GetEvaluationOutput, error)
+	GetEvaluationWithContext(aws.Context, *machinelearning.GetEvaluationInput, ...request.Option) (*machinelearning.GetEvaluationOutput, error)
+	GetEvaluationRequest(*machinelearning.GetEvaluationInput) (*request.Request, *machinelearning.GetEvaluationOutput)
+
+	GetMLModel(*machinelearning.GetMLModelInput) (*machinelearning.GetMLModelOutput, error)
+	GetMLModelWithContext(aws.Context, *machinelearning.GetMLModelInput, ...request.Option) (*machinelearning.GetMLModelOutput, error)
+	GetMLModelRequest(*machinelearning.GetMLModelInput) (*request.Request, *machinelearning.GetMLModelOutput)
+
+	Predict(*machinelearning.PredictInput) (*machinelearning.PredictOutput, error)
+	PredictWithContext(aws.Context, *machinelearning.PredictInput, ...request.Option) (*machinelearning.PredictOutput, error)
+	PredictRequest(*machinelearning.PredictInput) (*request.Request, *machinelearning.PredictOutput)
+
+	UpdateBatchPrediction(*machinelearning.UpdateBatchPredictionInput) (*machinelearning.UpdateBatchPredictionOutput, error)
+	UpdateBatchPredictionWithContext(aws.Context, *machinelearning.UpdateBatchPredictionInput, ...request.Option) (*machinelearning.UpdateBatchPredictionOutput, error)
+	UpdateBatchPredictionRequest(*machinelearning.UpdateBatchPredictionInput) (*request.Request, *machinelearning.UpdateBatchPredictionOutput)
+
+	UpdateDataSource(*machinelearning.UpdateDataSourceInput) (*machinelearning.UpdateDataSourceOutput, error)
+	UpdateDataSourceWithContext(aws.Context, *machinelearning.UpdateDataSourceInput, ...request.Option) (*machinelearning.UpdateDataSourceOutput, error)
+	UpdateDataSourceRequest(*machinelearning.UpdateDataSourceInput) (*request.Request, *machinelearning.UpdateDataSourceOutput)
+
+	UpdateEvaluation(*machinelearning.UpdateEvaluationInput) (*machinelearning.UpdateEvaluationOutput, error)
+	UpdateEvaluationWithContext(aws.Context, *machinelearning.UpdateEvaluationInput, ...request.Option) (*machinelearning.UpdateEvaluationOutput, error)
+	UpdateEvaluationRequest(*machinelearning.UpdateEvaluationInput) (*request.Request, *machinelearning.UpdateEvaluationOutput)
+
+	UpdateMLModel(*machinelearning.UpdateMLModelInput) (*machinelearning.UpdateMLModelOutput, error)
+	UpdateMLModelWithContext(aws.Context, *machinelearning.UpdateMLModelInput, ...request.Option) (*machinelearning.UpdateMLModelOutput, error)
+	UpdateMLModelRequest(*machinelearning.UpdateMLModelInput) (*request.Request, *machinelearning.UpdateMLModelOutput)
+
+	WaitUntilBatchPredictionAvailable(*machinelearning.DescribeBatchPredictionsInput) error
+	WaitUntilBatchPredictionAvailableWithContext(aws.Context, *machinelearning.DescribeBatchPredictionsInput, ...request.WaiterOption) error
+
+	WaitUntilDataSourceAvailable(*machinelearning.DescribeDataSourcesInput) error
+	WaitUntilDataSourceAvailableWithContext(aws.Context, *machinelearning.DescribeDataSourcesInput, ...request.WaiterOption) error
+
+	WaitUntilEvaluationAvailable(*machinelearning.DescribeEvaluationsInput) error
+	WaitUntilEvaluationAvailableWithContext(aws.Context, *machinelearning.DescribeEvaluationsInput, ...request.WaiterOption) error
+
+	WaitUntilMLModelAvailable(*machinelearning.DescribeMLModelsInput) error
+	WaitUntilMLModelAvailableWithContext(aws.Context, *machinelearning.DescribeMLModelsInput, ...request.WaiterOption) error
+}
+
+var _ MachineLearningAPI = (*machinelearning.MachineLearning)(nil)

vendor/github.com/aws/aws-sdk-go/service/machinelearning/service.go

@@ -0,0 +1,95 @@
+// 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/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" // Service endpoint prefix API calls made to.
+	EndpointsID = ServiceName       // Service ID for Regions and Endpoints metadata.
+)
+
+// 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:
+//     // 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...)
+	return newClient(*c.Config, c.Handlers, c.Endpoint, c.SigningRegion, c.SigningName)
+}
+
+// newClient creates, initializes and returns a new service client instance.
+func newClient(cfg aws.Config, handlers request.Handlers, endpoint, signingRegion, signingName string) *MachineLearning {
+	svc := &MachineLearning{
+		Client: client.New(
+			cfg,
+			metadata.ClientInfo{
+				ServiceName:   ServiceName,
+				SigningName:   signingName,
+				SigningRegion: signingRegion,
+				Endpoint:      endpoint,
+				APIVersion:    "2014-12-12",
+				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(jsonrpc.UnmarshalErrorHandler)
+
+	// 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
+}

vendor/github.com/aws/aws-sdk-go/service/machinelearning/waiters.go

@@ -0,0 +1,214 @@
+// 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 meet 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 meet 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 meet 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 meet 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)
+}