const (

	// ErrCodeResourceInUse for service response error code
	// "ResourceInUse".
	//
	// Resource being accessed is in use.
	ErrCodeResourceInUse = "ResourceInUse"

	// ErrCodeResourceLimitExceeded for service response error code
	// "ResourceLimitExceeded".
	//
	// You have exceeded an Amazon SageMaker resource limit. For example, you might
	// have too many training jobs created.
	ErrCodeResourceLimitExceeded = "ResourceLimitExceeded"

	// ErrCodeResourceNotFound for service response error code
	// "ResourceNotFound".
	//
	// Resource being access is not found.
	ErrCodeResourceNotFound = "ResourceNotFound"
)

const (
	ServiceName = "api.sagemaker" // Service endpoint prefix API calls made to.
	EndpointsID = ServiceName     // Service ID for Regions and Endpoints metadata.
)

type AddTagsInput struct {

	// The Amazon Resource Name (ARN) of the resource that you want to tag.
	//
	// ResourceArn is a required field
	ResourceArn *string `type:"string" required:"true"`

	// An array of Tag objects. Each tag is a key-value pair. Only the key parameter
	// is required. If you don't specify a value, Amazon SageMaker sets the value
	// to an empty string.
	//
	// Tags is a required field
	Tags []Tag `type:"list" required:"true"`
	// contains filtered or unexported fields
}

type AddTagsOutput struct {

	// A list of tags associated with the Amazon SageMaker resource.
	Tags []Tag `type:"list"`
	// contains filtered or unexported fields
}

type AddTagsRequest struct {
	*aws.Request
	Input *AddTagsInput
	Copy  func(*AddTagsInput) AddTagsRequest
}

type AlgorithmSpecification struct {

	// The registry path of the Docker image that contains the training algorithm.
	// For information about docker registry paths for built-in algorithms, see
	// sagemaker-algo-docker-registry-paths.
	//
	// TrainingImage is a required field
	TrainingImage *string `type:"string" required:"true"`

	// The input mode that the algorithm supports. For the input modes that Amazon
	// SageMaker algorithms support, see Algorithms (http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html).
	// If an algorithm supports the File input mode, Amazon SageMaker downloads
	// the training data from S3 to the provisioned ML storage Volume, and mounts
	// the directory to docker volume for training container. If an algorithm supports
	// the Pipe input mode, Amazon SageMaker streams data directly from S3 to the
	// container.
	//
	// In File mode, make sure you provision ML storage volume with sufficient capacity
	// to accommodate the data download from S3. In addition to the training data,
	// the ML storage volume also stores the output model. The algorithm container
	// use ML storage volume to also store intermediate information, if any.
	//
	// For distributed algorithms using File mode, training data is distributed
	// uniformly, and your training duration is predictable if the input data objects
	// size is approximately same. Amazon SageMaker does not split the files any
	// further for model training. If the object sizes are skewed, training won't
	// be optimal as the data distribution is also skewed where one host in a training
	// cluster is overloaded, thus becoming bottleneck in training.
	//
	// TrainingInputMode is a required field
	TrainingInputMode TrainingInputMode `type:"string" required:"true" enum:"true"`
	// contains filtered or unexported fields
}

type AssemblyType string

const (
	AssemblyTypeNone AssemblyType = "None"
	AssemblyTypeLine AssemblyType = "Line"
)

type BatchStrategy string

const (
	BatchStrategyMultiRecord  BatchStrategy = "MultiRecord"
	BatchStrategySingleRecord BatchStrategy = "SingleRecord"
)

type CategoricalParameterRange struct {

	// The name of the categorical hyperparameter to tune.
	//
	// Name is a required field
	Name *string `type:"string" required:"true"`

	// A list of the categories for the hyperparameter.
	//
	// Values is a required field
	Values []string `min:"1" type:"list" required:"true"`
	// contains filtered or unexported fields
}

type Channel struct {

	// The name of the channel.
	//
	// ChannelName is a required field
	ChannelName *string `min:"1" type:"string" required:"true"`

	// If training data is compressed, the compression type. The default value is
	// None. CompressionType is used only in Pipe input mode. In File mode, leave
	// this field unset or set it to None.
	CompressionType CompressionType `type:"string" enum:"true"`

	// The MIME type of the data.
	ContentType *string `type:"string"`

	// The location of the channel data.
	//
	// DataSource is a required field
	DataSource *DataSource `type:"structure" required:"true"`

	// Specify RecordIO as the value when input data is in raw format but the training
	// algorithm requires the RecordIO format, in which case, Amazon SageMaker wraps
	// each individual S3 object in a RecordIO record. If the input data is already
	// in RecordIO format, you don't need to set this attribute. For more information,
	// see Create a Dataset Using RecordIO (https://mxnet.incubator.apache.org/architecture/note_data_loading.html#data-format)
	RecordWrapperType RecordWrapper `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type CompressionType string

const (
	CompressionTypeNone CompressionType = "None"
	CompressionTypeGzip CompressionType = "Gzip"
)

type ContainerDefinition struct {

	// The DNS host name for the container after Amazon SageMaker deploys it.
	ContainerHostname *string `type:"string"`

	// The environment variables to set in the Docker container. Each key and value
	// in the Environment string to string map can have length of up to 1024. We
	// support up to 16 entries in the map.
	Environment map[string]string `type:"map"`

	// The Amazon EC2 Container Registry (Amazon ECR) path where inference code
	// is stored. If you are using your own custom algorithm instead of an algorithm
	// provided by Amazon SageMaker, the inference code must meet Amazon SageMaker
	// requirements. Amazon SageMaker supports both registry/repository[:tag] and
	// registry/repository[@digest] image path formats. For more information, see
	// Using Your Own Algorithms with Amazon SageMaker (http://docs.aws.amazon.com/sagemaker/latest/dg/your-algorithms.html)
	//
	// Image is a required field
	Image *string `type:"string" required:"true"`

	// The S3 path where the model artifacts, which result from model training,
	// are stored. This path must point to a single gzip compressed tar archive
	// (.tar.gz suffix).
	//
	// If you provide a value for this parameter, Amazon SageMaker uses AWS Security
	// Token Service to download model artifacts from the S3 path you provide. AWS
	// STS is activated in your IAM user account by default. If you previously deactivated
	// AWS STS for a region, you need to reactivate AWS STS for that region. For
	// more information, see Activating and Deactivating AWS STS i an AWS Region
	// (http://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_temp_enable-regions.html)
	// in the AWS Identity and Access Management User Guide.
	ModelDataUrl *string `type:"string"`
	// contains filtered or unexported fields
}

type ContinuousParameterRange struct {

	// The maximum value for the hyperparameter. The tuning job uses floating-point
	// values between MinValue value and this value for tuning.
	//
	// MaxValue is a required field
	MaxValue *string `type:"string" required:"true"`

	// The minimum value for the hyperparameter. The tuning job uses floating-point
	// values between this value and MaxValuefor tuning.
	//
	// MinValue is a required field
	MinValue *string `type:"string" required:"true"`

	// The name of the continuous hyperparameter to tune.
	//
	// Name is a required field
	Name *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateEndpointConfigInput struct {

	// The name of the endpoint configuration. You specify this name in a CreateEndpoint
	// (http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpoint.html)
	// request.
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`

	// The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon
	// SageMaker uses to encrypt data on the storage volume attached to the ML compute
	// instance that hosts the endpoint.
	KmsKeyId *string `type:"string"`

	// An array of ProductionVariant objects, one for each model that you want to
	// host at this endpoint.
	//
	// ProductionVariants is a required field
	ProductionVariants []ProductionVariant `min:"1" type:"list" required:"true"`

	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags (http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []Tag `type:"list"`
	// contains filtered or unexported fields
}

type CreateEndpointConfigOutput struct {

	// The Amazon Resource Name (ARN) of the endpoint configuration.
	//
	// EndpointConfigArn is a required field
	EndpointConfigArn *string `min:"20" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateEndpointConfigRequest struct {
	*aws.Request
	Input *CreateEndpointConfigInput
	Copy  func(*CreateEndpointConfigInput) CreateEndpointConfigRequest
}

type CreateEndpointInput struct {

	// The name of an endpoint configuration. For more information, see CreateEndpointConfig
	// (http://docs.aws.amazon.com/sagemaker/latest/dg/API_CreateEndpointConfig.html).
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`

	// The name of the endpoint. The name must be unique within an AWS Region in
	// your AWS account.
	//
	// EndpointName is a required field
	EndpointName *string `type:"string" required:"true"`

	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags (http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)in
	// the AWS Billing and Cost Management User Guide.
	Tags []Tag `type:"list"`
	// contains filtered or unexported fields
}

type CreateEndpointOutput struct {

	// The Amazon Resource Name (ARN) of the endpoint.
	//
	// EndpointArn is a required field
	EndpointArn *string `min:"20" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateEndpointRequest struct {
	*aws.Request
	Input *CreateEndpointInput
	Copy  func(*CreateEndpointInput) CreateEndpointRequest
}

type CreateHyperParameterTuningJobInput struct {

	// The HyperParameterTuningJobConfig object that describes the tuning job, including
	// the search strategy, metric used to evaluate training jobs, ranges of parameters
	// to search, and resource limits for the tuning job.
	//
	// HyperParameterTuningJobConfig is a required field
	HyperParameterTuningJobConfig *HyperParameterTuningJobConfig `type:"structure" required:"true"`

	// The name of the tuning job. This name is the prefix for the names of all
	// training jobs that this tuning job launches. The name must be unique within
	// the same AWS account and AWS Region. Names are not case sensitive, and must
	// be between 1-32 characters.
	//
	// HyperParameterTuningJobName is a required field
	HyperParameterTuningJobName *string `min:"1" type:"string" required:"true"`

	// An array of key-value pairs. You can use tags to categorize your AWS resources
	// in different ways, for example, by purpose, owner, or environment. For more
	// information, see Using Cost Allocation Tags (http://docs.aws.amazon.com//awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []Tag `type:"list"`

	// The HyperParameterTrainingJobDefinition object that describes the training
	// jobs that this tuning job launches, including static hyperparameters, input
	// data configuration, output data configuration, resource configuration, and
	// stopping condition.
	//
	// TrainingJobDefinition is a required field
	TrainingJobDefinition *HyperParameterTrainingJobDefinition `type:"structure" required:"true"`
	// contains filtered or unexported fields
}

type CreateHyperParameterTuningJobOutput struct {

	// The Amazon Resource Name (ARN) of the tuning job.
	//
	// HyperParameterTuningJobArn is a required field
	HyperParameterTuningJobArn *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateHyperParameterTuningJobRequest struct {
	*aws.Request
	Input *CreateHyperParameterTuningJobInput
	Copy  func(*CreateHyperParameterTuningJobInput) CreateHyperParameterTuningJobRequest
}

type CreateModelInput struct {

	// The Amazon Resource Name (ARN) of the IAM role that Amazon SageMaker can
	// assume to access model artifacts and docker image for deployment on ML compute
	// instances or for batch transform jobs. Deploying on ML compute instances
	// is part of model hosting. For more information, see Amazon SageMaker Roles
	// (http://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html).
	//
	// To be able to pass this role to Amazon SageMaker, the caller of this API
	// must have the iam:PassRole permission.
	//
	// ExecutionRoleArn is a required field
	ExecutionRoleArn *string `min:"20" type:"string" required:"true"`

	// The name of the new model.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`

	// The location of the primary docker image containing inference code, associated
	// artifacts, and custom environment map that the inference code uses when the
	// model is deployed for predictions.
	//
	// PrimaryContainer is a required field
	PrimaryContainer *ContainerDefinition `type:"structure" required:"true"`

	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags (http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []Tag `type:"list"`

	// A VpcConfig object that specifies the VPC that you want your model to connect
	// to. Control access to and from your model container by configuring the VPC.
	// VpcConfig is currently used in hosting services but not in batch transform.
	// For more information, see host-vpc.
	VpcConfig *VpcConfig `type:"structure"`
	// contains filtered or unexported fields
}

type CreateModelOutput struct {

	// The ARN of the model created in Amazon SageMaker.
	//
	// ModelArn is a required field
	ModelArn *string `min:"20" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateModelRequest struct {
	*aws.Request
	Input *CreateModelInput
	Copy  func(*CreateModelInput) CreateModelRequest
}

type CreateNotebookInstanceInput struct {

	// Sets whether Amazon SageMaker provides internet access to the notebook instance.
	// If you set this to Disabled this notebook instance will be able to access
	// resources only in your VPC, and will not be able to connect to Amazon SageMaker
	// training and endpoint services unless your configure a NAT Gateway in your
	// VPC.
	//
	// For more information, see appendix-notebook-and-internet-access. You can
	// set the value of this parameter to Disabled only if you set a value for the
	// SubnetId parameter.
	DirectInternetAccess DirectInternetAccess `type:"string" enum:"true"`

	// The type of ML compute instance to launch for the notebook instance.
	//
	// InstanceType is a required field
	InstanceType InstanceType `type:"string" required:"true" enum:"true"`

	// If you provide a AWS KMS key ID, Amazon SageMaker uses it to encrypt data
	// at rest on the ML storage volume that is attached to your notebook instance.
	KmsKeyId *string `type:"string"`

	// The name of a lifecycle configuration to associate with the notebook instance.
	// For information about lifestyle configurations, see notebook-lifecycle-config.
	LifecycleConfigName *string `type:"string"`

	// The name of the new notebook instance.
	//
	// NotebookInstanceName is a required field
	NotebookInstanceName *string `type:"string" required:"true"`

	// When you send any requests to AWS resources from the notebook instance, Amazon
	// SageMaker assumes this role to perform tasks on your behalf. You must grant
	// this role necessary permissions so Amazon SageMaker can perform these tasks.
	// The policy must allow the Amazon SageMaker service principal (sagemaker.amazonaws.com)
	// permissions to assume this role. For more information, see Amazon SageMaker
	// Roles (http://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html).
	//
	// To be able to pass this role to Amazon SageMaker, the caller of this API
	// must have the iam:PassRole permission.
	//
	// RoleArn is a required field
	RoleArn *string `min:"20" type:"string" required:"true"`

	// The VPC security group IDs, in the form sg-xxxxxxxx. The security groups
	// must be for the same VPC as specified in the subnet.
	SecurityGroupIds []string `type:"list"`

	// The ID of the subnet in a VPC to which you would like to have a connectivity
	// from your ML compute instance.
	SubnetId *string `type:"string"`

	// A list of tags to associate with the notebook instance. You can add tags
	// later by using the CreateTags API.
	Tags []Tag `type:"list"`
	// contains filtered or unexported fields
}

type CreateNotebookInstanceLifecycleConfigInput struct {

	// The name of the lifecycle configuration.
	//
	// NotebookInstanceLifecycleConfigName is a required field
	NotebookInstanceLifecycleConfigName *string `type:"string" required:"true"`

	// A shell script that runs only once, when you create a notebook instance.
	OnCreate []NotebookInstanceLifecycleHook `type:"list"`

	// A shell script that runs every time you start a notebook instance, including
	// when you create the notebook instance.
	OnStart []NotebookInstanceLifecycleHook `type:"list"`
	// contains filtered or unexported fields
}

type CreateNotebookInstanceLifecycleConfigOutput struct {

	// The Amazon Resource Name (ARN) of the lifecycle configuration.
	NotebookInstanceLifecycleConfigArn *string `type:"string"`
	// contains filtered or unexported fields
}

type CreateNotebookInstanceLifecycleConfigRequest struct {
	*aws.Request
	Input *CreateNotebookInstanceLifecycleConfigInput
	Copy  func(*CreateNotebookInstanceLifecycleConfigInput) CreateNotebookInstanceLifecycleConfigRequest
}

type CreateNotebookInstanceOutput struct {

	// The Amazon Resource Name (ARN) of the notebook instance.
	NotebookInstanceArn *string `type:"string"`
	// contains filtered or unexported fields
}

type CreateNotebookInstanceRequest struct {
	*aws.Request
	Input *CreateNotebookInstanceInput
	Copy  func(*CreateNotebookInstanceInput) CreateNotebookInstanceRequest
}

type CreatePresignedNotebookInstanceUrlInput struct {

	// The name of the notebook instance.
	//
	// NotebookInstanceName is a required field
	NotebookInstanceName *string `type:"string" required:"true"`

	// The duration of the session, in seconds. The default is 12 hours.
	SessionExpirationDurationInSeconds *int64 `min:"1800" type:"integer"`
	// contains filtered or unexported fields
}

type CreatePresignedNotebookInstanceUrlOutput struct {

	// A JSON object that contains the URL string.
	AuthorizedUrl *string `type:"string"`
	// contains filtered or unexported fields
}

type CreatePresignedNotebookInstanceUrlRequest struct {
	*aws.Request
	Input *CreatePresignedNotebookInstanceUrlInput
	Copy  func(*CreatePresignedNotebookInstanceUrlInput) CreatePresignedNotebookInstanceUrlRequest
}

type CreateTrainingJobInput struct {

	// The registry path of the Docker image that contains the training algorithm
	// and algorithm-specific metadata, including the input mode. For more information
	// about algorithms provided by Amazon SageMaker, see Algorithms (http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html).
	// For information about providing your own algorithms, see your-algorithms.
	//
	// AlgorithmSpecification is a required field
	AlgorithmSpecification *AlgorithmSpecification `type:"structure" required:"true"`

	// Algorithm-specific parameters that influence the quality of the model. You
	// set hyperparameters before you start the learning process. For a list of
	// hyperparameters for each training algorithm provided by Amazon SageMaker,
	// see Algorithms (http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html).
	//
	// You can specify a maximum of 100 hyperparameters. Each hyperparameter is
	// a key-value pair. Each key and value is limited to 256 characters, as specified
	// by the Length Constraint.
	HyperParameters map[string]string `type:"map"`

	// An array of Channel objects. Each channel is a named input source. InputDataConfig
	// describes the input data and its location.
	//
	// Algorithms can accept input data from one or more channels. For example,
	// an algorithm might have two channels of input data, training_data and validation_data.
	// The configuration for each channel provides the S3 location where the input
	// data is stored. It also provides information about the stored data: the MIME
	// type, compression method, and whether the data is wrapped in RecordIO format.
	//
	// Depending on the input mode that the algorithm supports, Amazon SageMaker
	// either copies input data files from an S3 bucket to a local directory in
	// the Docker container, or makes it available as input streams.
	//
	// InputDataConfig is a required field
	InputDataConfig []Channel `min:"1" type:"list" required:"true"`

	// Specifies the path to the S3 bucket where you want to store model artifacts.
	// Amazon SageMaker creates subfolders for the artifacts.
	//
	// OutputDataConfig is a required field
	OutputDataConfig *OutputDataConfig `type:"structure" required:"true"`

	// The resources, including the ML compute instances and ML storage volumes,
	// to use for model training.
	//
	// ML storage volumes store model artifacts and incremental states. Training
	// algorithms might also use ML storage volumes for scratch space. If you want
	// Amazon SageMaker to use the ML storage volume to store the training data,
	// choose File as the TrainingInputMode in the algorithm specification. For
	// distributed training algorithms, specify an instance count greater than 1.
	//
	// ResourceConfig is a required field
	ResourceConfig *ResourceConfig `type:"structure" required:"true"`

	// The Amazon Resource Name (ARN) of an IAM role that Amazon SageMaker can assume
	// to perform tasks on your behalf.
	//
	// During model training, Amazon SageMaker needs your permission to read input
	// data from an S3 bucket, download a Docker image that contains training code,
	// write model artifacts to an S3 bucket, write logs to Amazon CloudWatch Logs,
	// and publish metrics to Amazon CloudWatch. You grant permissions for all of
	// these tasks to an IAM role. For more information, see Amazon SageMaker Roles
	// (http://docs.aws.amazon.com/sagemaker/latest/dg/sagemaker-roles.html).
	//
	// To be able to pass this role to Amazon SageMaker, the caller of this API
	// must have the iam:PassRole permission.
	//
	// RoleArn is a required field
	RoleArn *string `min:"20" type:"string" required:"true"`

	// Sets a duration for training. Use this parameter to cap model training costs.
	// To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal, which
	// delays job termination for 120 seconds. Algorithms might use this 120-second
	// window to save the model artifacts.
	//
	// When Amazon SageMaker terminates a job because the stopping condition has
	// been met, training algorithms provided by Amazon SageMaker save the intermediate
	// results of the job. This intermediate data is a valid model artifact. You
	// can use it to create a model using the CreateModel API.
	//
	// StoppingCondition is a required field
	StoppingCondition *StoppingCondition `type:"structure" required:"true"`

	// An array of key-value pairs. For more information, see Using Cost Allocation
	// Tags (http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []Tag `type:"list"`

	// The name of the training job. The name must be unique within an AWS Region
	// in an AWS account.
	//
	// TrainingJobName is a required field
	TrainingJobName *string `min:"1" type:"string" required:"true"`

	// A VpcConfig object that specifies the VPC that you want your training job
	// to connect to. Control access to and from your training container by configuring
	// the VPC. For more information, see train-vpc
	VpcConfig *VpcConfig `type:"structure"`
	// contains filtered or unexported fields
}

type CreateTrainingJobOutput struct {

	// The Amazon Resource Name (ARN) of the training job.
	//
	// TrainingJobArn is a required field
	TrainingJobArn *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateTrainingJobRequest struct {
	*aws.Request
	Input *CreateTrainingJobInput
	Copy  func(*CreateTrainingJobInput) CreateTrainingJobRequest
}

type CreateTransformJobInput struct {

	// Determines the number of records included in a single mini-batch. SingleRecord
	// means only one record is used per mini-batch. MultiRecord means a mini-batch
	// is set to contain as many records that can fit within the MaxPayloadInMB
	// limit.
	//
	// Batch transform will automatically split your input data into whatever payload
	// size is specified if you set SplitType to Line and BatchStrategy to MultiRecord.
	// There's no need to split the dataset into smaller files or to use larger
	// payload sizes unless the records in your dataset are very large.
	BatchStrategy BatchStrategy `type:"string" enum:"true"`

	// The environment variables to set in the Docker container. We support up to
	// 16 key and values entries in the map.
	Environment map[string]string `type:"map"`

	// The maximum number of parallel requests that can be sent to each instance
	// in a transform job. This is good for algorithms that implement multiple workers
	// on larger instances . The default value is 1. To allow Amazon SageMaker to
	// determine the appropriate number for MaxConcurrentTransforms, set the value
	// to 0.
	MaxConcurrentTransforms *int64 `type:"integer"`

	// The maximum payload size allowed, in MB. A payload is the data portion of
	// a record (without metadata). The value in MaxPayloadInMB must be greater
	// or equal to the size of a single record. You can approximate the size of
	// a record by dividing the size of your dataset by the number of records. Then
	// multiply this value by the number of records you want in a mini-batch. It
	// is recommended to enter a value slightly larger than this to ensure the records
	// fit within the maximum payload size. The default value is 6 MB. For an unlimited
	// payload size, set the value to 0.
	MaxPayloadInMB *int64 `type:"integer"`

	// The name of the model that you want to use for the transform job. ModelName
	// must be the name of an existing Amazon SageMaker model within an AWS Region
	// in an AWS account.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`

	// An array of key-value pairs. Adding tags is optional. For more information,
	// see Using Cost Allocation Tags (http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/cost-alloc-tags.html#allocation-what)
	// in the AWS Billing and Cost Management User Guide.
	Tags []Tag `type:"list"`

	// Describes the input source and the way the transform job consumes it.
	//
	// TransformInput is a required field
	TransformInput *TransformInput `type:"structure" required:"true"`

	// The name of the transform job. The name must be unique within an AWS Region
	// in an AWS account.
	//
	// TransformJobName is a required field
	TransformJobName *string `min:"1" type:"string" required:"true"`

	// Describes the results of the transform job.
	//
	// TransformOutput is a required field
	TransformOutput *TransformOutput `type:"structure" required:"true"`

	// Describes the resources, including ML instance types and ML instance count,
	// to use for the transform job.
	//
	// TransformResources is a required field
	TransformResources *TransformResources `type:"structure" required:"true"`
	// contains filtered or unexported fields
}

type CreateTransformJobOutput struct {

	// The Amazon Resource Name (ARN) of the transform job.
	//
	// TransformJobArn is a required field
	TransformJobArn *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type CreateTransformJobRequest struct {
	*aws.Request
	Input *CreateTransformJobInput
	Copy  func(*CreateTransformJobInput) CreateTransformJobRequest
}

type DataSource struct {

	// The S3 location of the data source that is associated with a channel.
	//
	// S3DataSource is a required field
	S3DataSource *S3DataSource `type:"structure" required:"true"`
	// contains filtered or unexported fields
}

type DeleteEndpointConfigInput struct {

	// The name of the endpoint configuration that you want to delete.
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DeleteEndpointConfigOutput struct {
	// contains filtered or unexported fields
}

type DeleteEndpointConfigRequest struct {
	*aws.Request
	Input *DeleteEndpointConfigInput
	Copy  func(*DeleteEndpointConfigInput) DeleteEndpointConfigRequest
}

type DeleteEndpointInput struct {

	// The name of the endpoint that you want to delete.
	//
	// EndpointName is a required field
	EndpointName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DeleteEndpointOutput struct {
	// contains filtered or unexported fields
}

type DeleteEndpointRequest struct {
	*aws.Request
	Input *DeleteEndpointInput
	Copy  func(*DeleteEndpointInput) DeleteEndpointRequest
}

type DeleteModelInput struct {

	// The name of the model to delete.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DeleteModelOutput struct {
	// contains filtered or unexported fields
}

type DeleteModelRequest struct {
	*aws.Request
	Input *DeleteModelInput
	Copy  func(*DeleteModelInput) DeleteModelRequest
}

type DeleteNotebookInstanceInput struct {

	// The name of the Amazon SageMaker notebook instance to delete.
	//
	// NotebookInstanceName is a required field
	NotebookInstanceName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DeleteNotebookInstanceLifecycleConfigInput struct {

	// The name of the lifecycle configuration to delete.
	//
	// NotebookInstanceLifecycleConfigName is a required field
	NotebookInstanceLifecycleConfigName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DeleteNotebookInstanceLifecycleConfigOutput struct {
	// contains filtered or unexported fields
}

type DeleteNotebookInstanceLifecycleConfigRequest struct {
	*aws.Request
	Input *DeleteNotebookInstanceLifecycleConfigInput
	Copy  func(*DeleteNotebookInstanceLifecycleConfigInput) DeleteNotebookInstanceLifecycleConfigRequest
}

type DeleteNotebookInstanceOutput struct {
	// contains filtered or unexported fields
}

type DeleteNotebookInstanceRequest struct {
	*aws.Request
	Input *DeleteNotebookInstanceInput
	Copy  func(*DeleteNotebookInstanceInput) DeleteNotebookInstanceRequest
}

type DeleteTagsInput struct {

	// The Amazon Resource Name (ARN) of the resource whose tags you want to delete.
	//
	// ResourceArn is a required field
	ResourceArn *string `type:"string" required:"true"`

	// An array or one or more tag keys to delete.
	//
	// TagKeys is a required field
	TagKeys []string `min:"1" type:"list" required:"true"`
	// contains filtered or unexported fields
}

type DeleteTagsOutput struct {
	// contains filtered or unexported fields
}

type DeleteTagsRequest struct {
	*aws.Request
	Input *DeleteTagsInput
	Copy  func(*DeleteTagsInput) DeleteTagsRequest
}

type DeployedImage struct {

	// The date and time when the image path for the model resolved to the ResolvedImage
	ResolutionTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The specific digest path of the image hosted in this ProductionVariant.
	ResolvedImage *string `type:"string"`

	// The image path you specified when you created the model.
	SpecifiedImage *string `type:"string"`
	// contains filtered or unexported fields
}

type DescribeEndpointConfigInput struct {

	// The name of the endpoint configuration.
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeEndpointConfigOutput struct {

	// A timestamp that shows when the endpoint configuration was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The Amazon Resource Name (ARN) of the endpoint configuration.
	//
	// EndpointConfigArn is a required field
	EndpointConfigArn *string `min:"20" type:"string" required:"true"`

	// Name of the Amazon SageMaker endpoint configuration.
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`

	// AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the
	// ML storage volume attached to the instance.
	KmsKeyId *string `type:"string"`

	// An array of ProductionVariant objects, one for each model that you want to
	// host at this endpoint.
	//
	// ProductionVariants is a required field
	ProductionVariants []ProductionVariant `min:"1" type:"list" required:"true"`
	// contains filtered or unexported fields
}

type DescribeEndpointConfigRequest struct {
	*aws.Request
	Input *DescribeEndpointConfigInput
	Copy  func(*DescribeEndpointConfigInput) DescribeEndpointConfigRequest
}

type DescribeEndpointInput struct {

	// The name of the endpoint.
	//
	// EndpointName is a required field
	EndpointName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeEndpointOutput struct {

	// A timestamp that shows when the endpoint was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The Amazon Resource Name (ARN) of the endpoint.
	//
	// EndpointArn is a required field
	EndpointArn *string `min:"20" type:"string" required:"true"`

	// The name of the endpoint configuration associated with this endpoint.
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`

	// Name of the endpoint.
	//
	// EndpointName is a required field
	EndpointName *string `type:"string" required:"true"`

	// The status of the endpoint.
	//
	// EndpointStatus is a required field
	EndpointStatus EndpointStatus `type:"string" required:"true" enum:"true"`

	// If the status of the endpoint is Failed, the reason why it failed.
	FailureReason *string `type:"string"`

	// A timestamp that shows when the endpoint was last modified.
	//
	// LastModifiedTime is a required field
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// An array of ProductionVariantSummary objects, one for each model hosted behind
	// this endpoint.
	ProductionVariants []ProductionVariantSummary `min:"1" type:"list"`
	// contains filtered or unexported fields
}

type DescribeEndpointRequest struct {
	*aws.Request
	Input *DescribeEndpointInput
	Copy  func(*DescribeEndpointInput) DescribeEndpointRequest
}

type DescribeHyperParameterTuningJobInput struct {

	// The name of the tuning job to describe.
	//
	// HyperParameterTuningJobName is a required field
	HyperParameterTuningJobName *string `min:"1" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeHyperParameterTuningJobOutput struct {

	// A TrainingJobSummary object that describes the training job that completed
	// with the best current HyperParameterTuningJobObjective.
	BestTrainingJob *HyperParameterTrainingJobSummary `type:"structure"`

	// The date and time that the tuning job started.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// If the tuning job failed, the reason it failed.
	FailureReason *string `type:"string"`

	// The date and time that the tuning job ended.
	HyperParameterTuningEndTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the tuning job.
	//
	// HyperParameterTuningJobArn is a required field
	HyperParameterTuningJobArn *string `type:"string" required:"true"`

	// The HyperParameterTuningJobConfig object that specifies the configuration
	// of the tuning job.
	//
	// HyperParameterTuningJobConfig is a required field
	HyperParameterTuningJobConfig *HyperParameterTuningJobConfig `type:"structure" required:"true"`

	// The name of the tuning job.
	//
	// HyperParameterTuningJobName is a required field
	HyperParameterTuningJobName *string `min:"1" type:"string" required:"true"`

	// The status of the tuning job: InProgress, Completed, Failed, Stopping, or
	// Stopped.
	//
	// HyperParameterTuningJobStatus is a required field
	HyperParameterTuningJobStatus HyperParameterTuningJobStatus `type:"string" required:"true" enum:"true"`

	// The date and time that the status of the tuning job was modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The ObjectiveStatusCounters object that specifies the number of training
	// jobs, categorized by the status of their final objective metric, that this
	// tuning job launched.
	//
	// ObjectiveStatusCounters is a required field
	ObjectiveStatusCounters *ObjectiveStatusCounters `type:"structure" required:"true"`

	// The HyperParameterTrainingJobDefinition object that specifies the definition
	// of the training jobs that this tuning job launches.
	//
	// TrainingJobDefinition is a required field
	TrainingJobDefinition *HyperParameterTrainingJobDefinition `type:"structure" required:"true"`

	// The TrainingJobStatusCounters object that specifies the number of training
	// jobs, categorized by status, that this tuning job launched.
	//
	// TrainingJobStatusCounters is a required field
	TrainingJobStatusCounters *TrainingJobStatusCounters `type:"structure" required:"true"`
	// contains filtered or unexported fields
}

type DescribeHyperParameterTuningJobRequest struct {
	*aws.Request
	Input *DescribeHyperParameterTuningJobInput
	Copy  func(*DescribeHyperParameterTuningJobInput) DescribeHyperParameterTuningJobRequest
}

type DescribeModelInput struct {

	// The name of the model.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeModelOutput struct {

	// A timestamp that shows when the model was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The Amazon Resource Name (ARN) of the IAM role that you specified for the
	// model.
	//
	// ExecutionRoleArn is a required field
	ExecutionRoleArn *string `min:"20" type:"string" required:"true"`

	// The Amazon Resource Name (ARN) of the model.
	//
	// ModelArn is a required field
	ModelArn *string `min:"20" type:"string" required:"true"`

	// Name of the Amazon SageMaker model.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`

	// The location of the primary inference code, associated artifacts, and custom
	// environment map that the inference code uses when it is deployed in production.
	//
	// PrimaryContainer is a required field
	PrimaryContainer *ContainerDefinition `type:"structure" required:"true"`

	// A VpcConfig object that specifies the VPC that this model has access to.
	// For more information, see host-vpc
	VpcConfig *VpcConfig `type:"structure"`
	// contains filtered or unexported fields
}

type DescribeModelRequest struct {
	*aws.Request
	Input *DescribeModelInput
	Copy  func(*DescribeModelInput) DescribeModelRequest
}

type DescribeNotebookInstanceInput struct {

	// The name of the notebook instance that you want information about.
	//
	// NotebookInstanceName is a required field
	NotebookInstanceName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeNotebookInstanceLifecycleConfigInput struct {

	// The name of the lifecycle configuration to describe.
	//
	// NotebookInstanceLifecycleConfigName is a required field
	NotebookInstanceLifecycleConfigName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeNotebookInstanceLifecycleConfigOutput struct {

	// A timestamp that tells when the lifecycle configuration was created.
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A timestamp that tells when the lifecycle configuration was last modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the lifecycle configuration.
	NotebookInstanceLifecycleConfigArn *string `type:"string"`

	// The name of the lifecycle configuration.
	NotebookInstanceLifecycleConfigName *string `type:"string"`

	// The shell script that runs only once, when you create a notebook instance.
	OnCreate []NotebookInstanceLifecycleHook `type:"list"`

	// The shell script that runs every time you start a notebook instance, including
	// when you create the notebook instance.
	OnStart []NotebookInstanceLifecycleHook `type:"list"`
	// contains filtered or unexported fields
}

type DescribeNotebookInstanceLifecycleConfigRequest struct {
	*aws.Request
	Input *DescribeNotebookInstanceLifecycleConfigInput
	Copy  func(*DescribeNotebookInstanceLifecycleConfigInput) DescribeNotebookInstanceLifecycleConfigRequest
}

type DescribeNotebookInstanceOutput struct {

	// A timestamp. Use this parameter to return the time when the notebook instance
	// was created
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// Describes whether Amazon SageMaker provides internet access to the notebook
	// instance. If this value is set to Disabled, he notebook instance does not
	// have internet access, and cannot connect to Amazon SageMaker training and
	// endpoint services.
	//
	// For more information, see appendix-notebook-and-internet-access.
	DirectInternetAccess DirectInternetAccess `type:"string" enum:"true"`

	// If status is failed, the reason it failed.
	FailureReason *string `type:"string"`

	// The type of ML compute instance running on the notebook instance.
	InstanceType InstanceType `type:"string" enum:"true"`

	// AWS KMS key ID Amazon SageMaker uses to encrypt data when storing it on the
	// ML storage volume attached to the instance.
	KmsKeyId *string `type:"string"`

	// A timestamp. Use this parameter to retrieve the time when the notebook instance
	// was last modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// Network interface IDs that Amazon SageMaker created at the time of creating
	// the instance.
	NetworkInterfaceId *string `type:"string"`

	// The Amazon Resource Name (ARN) of the notebook instance.
	NotebookInstanceArn *string `type:"string"`

	// Returns the name of a notebook instance lifecycle configuration.
	//
	// For information about notebook instance lifestyle configurations, see notebook-lifecycle-config.
	NotebookInstanceLifecycleConfigName *string `type:"string"`

	// Name of the Amazon SageMaker notebook instance.
	NotebookInstanceName *string `type:"string"`

	// The status of the notebook instance.
	NotebookInstanceStatus NotebookInstanceStatus `type:"string" enum:"true"`

	// Amazon Resource Name (ARN) of the IAM role associated with the instance.
	RoleArn *string `min:"20" type:"string"`

	// The IDs of the VPC security groups.
	SecurityGroups []string `type:"list"`

	// The ID of the VPC subnet.
	SubnetId *string `type:"string"`

	// The URL that you use to connect to the Jupyter notebook that is running in
	// your notebook instance.
	Url *string `type:"string"`
	// contains filtered or unexported fields
}

type DescribeNotebookInstanceRequest struct {
	*aws.Request
	Input *DescribeNotebookInstanceInput
	Copy  func(*DescribeNotebookInstanceInput) DescribeNotebookInstanceRequest
}

type DescribeTrainingJobInput struct {

	// The name of the training job.
	//
	// TrainingJobName is a required field
	TrainingJobName *string `min:"1" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeTrainingJobOutput struct {

	// Information about the algorithm used for training, and algorithm metadata.
	//
	// AlgorithmSpecification is a required field
	AlgorithmSpecification *AlgorithmSpecification `type:"structure" required:"true"`

	// A timestamp that indicates when the training job was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// If the training job failed, the reason it failed.
	FailureReason *string `type:"string"`

	// Algorithm-specific parameters.
	HyperParameters map[string]string `type:"map"`

	// An array of Channel objects that describes each data input channel.
	//
	// InputDataConfig is a required field
	InputDataConfig []Channel `min:"1" type:"list" required:"true"`

	// A timestamp that indicates when the status of the training job was last modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// Information about the Amazon S3 location that is configured for storing model
	// artifacts.
	//
	// ModelArtifacts is a required field
	ModelArtifacts *ModelArtifacts `type:"structure" required:"true"`

	// The S3 path where model artifacts that you configured when creating the job
	// are stored. Amazon SageMaker creates subfolders for model artifacts.
	OutputDataConfig *OutputDataConfig `type:"structure"`

	// Resources, including ML compute instances and ML storage volumes, that are
	// configured for model training.
	//
	// ResourceConfig is a required field
	ResourceConfig *ResourceConfig `type:"structure" required:"true"`

	// The AWS Identity and Access Management (IAM) role configured for the training
	// job.
	RoleArn *string `min:"20" type:"string"`

	// Provides granular information about the system state. For more information,
	// see TrainingJobStatus.
	//
	//    * Starting - starting the training job.
	//
	//    * Downloading - downloading the input data.
	//
	//    * Training - model training is in progress.
	//
	//    * Uploading - uploading the trained model.
	//
	//    * Stopping - stopping the training job.
	//
	//    * Stopped - the training job has stopped.
	//
	//    * MaxRuntimeExceeded - the training job exceeded the specified max run
	//    time and has been stopped.
	//
	//    * Completed - the training job has completed.
	//
	//    * Failed - the training job has failed. The failure reason is stored in
	//    the FailureReason field of DescribeTrainingJobResponse.
	//
	// The valid values for SecondaryStatus are subject to change. They primarily
	// provide information on the progress of the training job.
	//
	// SecondaryStatus is a required field
	SecondaryStatus SecondaryStatus `type:"string" required:"true" enum:"true"`

	// To give an overview of the training job lifecycle, SecondaryStatusTransitions
	// is a log of time-ordered secondary statuses that a training job has transitioned.
	SecondaryStatusTransitions []SecondaryStatusTransition `type:"list"`

	// The condition under which to stop the training job.
	//
	// StoppingCondition is a required field
	StoppingCondition *StoppingCondition `type:"structure" required:"true"`

	// Indicates the time when the training job ends on training instances. You
	// are billed for the time interval between the value of TrainingStartTime and
	// this time. For successful jobs and stopped jobs, this is the time after model
	// artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker
	// detects a job failure.
	TrainingEndTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the training job.
	//
	// TrainingJobArn is a required field
	TrainingJobArn *string `type:"string" required:"true"`

	// Name of the model training job.
	//
	// TrainingJobName is a required field
	TrainingJobName *string `min:"1" type:"string" required:"true"`

	// The status of the training job.
	//
	// For the InProgress status, Amazon SageMaker can return these secondary statuses:
	//
	//    * Starting - Preparing for training.
	//
	//    * Downloading - Optional stage for algorithms that support File training
	//    input mode. It indicates data is being downloaded to ML storage volumes.
	//
	//    * Training - Training is in progress.
	//
	//    * Uploading - Training is complete and model upload is in progress.
	//
	// For the Stopped training status, Amazon SageMaker can return these secondary
	// statuses:
	//
	//    * MaxRuntimeExceeded - Job stopped as a result of maximum allowed runtime
	//    exceeded.
	//
	// TrainingJobStatus is a required field
	TrainingJobStatus TrainingJobStatus `type:"string" required:"true" enum:"true"`

	// Indicates the time when the training job starts on training instances. You
	// are billed for the time interval between this time and the value of TrainingEndTime.
	// The start time in CloudWatch Logs might be later than this time. The difference
	// is due to the time it takes to download the training data and to the size
	// of the training container.
	TrainingStartTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the associated hyperparameter tuning job
	// if the training job was launched by a hyperparameter tuning job.
	TuningJobArn *string `type:"string"`

	// A VpcConfig object that specifies the VPC that this training job has access
	// to. For more information, see train-vpc.
	VpcConfig *VpcConfig `type:"structure"`
	// contains filtered or unexported fields
}

type DescribeTrainingJobRequest struct {
	*aws.Request
	Input *DescribeTrainingJobInput
	Copy  func(*DescribeTrainingJobInput) DescribeTrainingJobRequest
}

type DescribeTransformJobInput struct {

	// The name of the transform job that you want to view details of.
	//
	// TransformJobName is a required field
	TransformJobName *string `min:"1" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DescribeTransformJobOutput struct {

	// SingleRecord means only one record was used per a batch. MultiRecord means
	// batches contained as many records that could possibly fit within the MaxPayloadInMB
	// limit.
	BatchStrategy BatchStrategy `type:"string" enum:"true"`

	// A timestamp that shows when the transform Job was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	Environment map[string]string `type:"map"`

	// If the transform job failed, the reason that it failed.
	FailureReason *string `type:"string"`

	// The maximum number of parallel requests on each instance node that can be
	// launched in a transform job. The default value is 1.
	MaxConcurrentTransforms *int64 `type:"integer"`

	// The maximum payload size , in MB used in the transform job.
	MaxPayloadInMB *int64 `type:"integer"`

	// The name of the model used in the transform job.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`

	// Indicates when the transform job is Completed, Stopped, or Failed. You are
	// billed for the time interval between this time and the value of TransformStartTime.
	TransformEndTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// Describes the dataset to be transformed and the Amazon S3 location where
	// it is stored.
	//
	// TransformInput is a required field
	TransformInput *TransformInput `type:"structure" required:"true"`

	// The Amazon Resource Name (ARN) of the transform job.
	//
	// TransformJobArn is a required field
	TransformJobArn *string `type:"string" required:"true"`

	// The name of the transform job.
	//
	// TransformJobName is a required field
	TransformJobName *string `min:"1" type:"string" required:"true"`

	// The status of the transform job. If the transform job failed, the reason
	// is returned in the FailureReason field.
	//
	// TransformJobStatus is a required field
	TransformJobStatus TransformJobStatus `type:"string" required:"true" enum:"true"`

	// Identifies the Amazon S3 location where you want Amazon SageMaker to save
	// the results from the transform job.
	TransformOutput *TransformOutput `type:"structure"`

	// Describes the resources, including ML instance types and ML instance count,
	// to use for the transform job.
	//
	// TransformResources is a required field
	TransformResources *TransformResources `type:"structure" required:"true"`

	// Indicates when the transform job starts on ML instances. You are billed for
	// the time interval between this time and the value of TransformEndTime.
	TransformStartTime *time.Time `type:"timestamp" timestampFormat:"unix"`
	// contains filtered or unexported fields
}

type DescribeTransformJobRequest struct {
	*aws.Request
	Input *DescribeTransformJobInput
	Copy  func(*DescribeTransformJobInput) DescribeTransformJobRequest
}

type DesiredWeightAndCapacity struct {

	// The variant's capacity.
	DesiredInstanceCount *int64 `min:"1" type:"integer"`

	// The variant's weight.
	DesiredWeight *float64 `type:"float"`

	// The name of the variant to update.
	//
	// VariantName is a required field
	VariantName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type DirectInternetAccess string

const (
	DirectInternetAccessEnabled  DirectInternetAccess = "Enabled"
	DirectInternetAccessDisabled DirectInternetAccess = "Disabled"
)

type EndpointConfigSortKey string

const (
	EndpointConfigSortKeyName         EndpointConfigSortKey = "Name"
	EndpointConfigSortKeyCreationTime EndpointConfigSortKey = "CreationTime"
)

type EndpointConfigSummary struct {

	// A timestamp that shows when the endpoint configuration was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The Amazon Resource Name (ARN) of the endpoint configuration.
	//
	// EndpointConfigArn is a required field
	EndpointConfigArn *string `min:"20" type:"string" required:"true"`

	// The name of the endpoint configuration.
	//
	// EndpointConfigName is a required field
	EndpointConfigName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type EndpointSortKey string

const (
	EndpointSortKeyName         EndpointSortKey = "Name"
	EndpointSortKeyCreationTime EndpointSortKey = "CreationTime"
	EndpointSortKeyStatus       EndpointSortKey = "Status"
)

type EndpointStatus string

const (
	EndpointStatusOutOfService   EndpointStatus = "OutOfService"
	EndpointStatusCreating       EndpointStatus = "Creating"
	EndpointStatusUpdating       EndpointStatus = "Updating"
	EndpointStatusSystemUpdating EndpointStatus = "SystemUpdating"
	EndpointStatusRollingBack    EndpointStatus = "RollingBack"
	EndpointStatusInService      EndpointStatus = "InService"
	EndpointStatusDeleting       EndpointStatus = "Deleting"
	EndpointStatusFailed         EndpointStatus = "Failed"
)

type EndpointSummary struct {

	// A timestamp that shows when the endpoint was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The Amazon Resource Name (ARN) of the endpoint.
	//
	// EndpointArn is a required field
	EndpointArn *string `min:"20" type:"string" required:"true"`

	// The name of the endpoint.
	//
	// EndpointName is a required field
	EndpointName *string `type:"string" required:"true"`

	// The status of the endpoint.
	//
	// EndpointStatus is a required field
	EndpointStatus EndpointStatus `type:"string" required:"true" enum:"true"`

	// A timestamp that shows when the endpoint was last modified.
	//
	// LastModifiedTime is a required field
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`
	// contains filtered or unexported fields
}

type FinalHyperParameterTuningJobObjectiveMetric struct {

	// The name of the objective metric.
	//
	// MetricName is a required field
	MetricName *string `min:"1" type:"string" required:"true"`

	// Whether to minimize or maximize the objective metric. Valid values are Minimize
	// and Maximize.
	Type HyperParameterTuningJobObjectiveType `type:"string" enum:"true"`

	// The value of the objective metric.
	//
	// Value is a required field
	Value *float64 `type:"float" required:"true"`
	// contains filtered or unexported fields
}

type HyperParameterAlgorithmSpecification struct {

	// An array of MetricDefinition objects that specify the metrics that the algorithm
	// emits.
	MetricDefinitions []MetricDefinition `type:"list"`

	// The registry path of the Docker image that contains the training algorithm.
	// For information about Docker registry paths for built-in algorithms, see
	// sagemaker-algo-docker-registry-paths.
	//
	// TrainingImage is a required field
	TrainingImage *string `type:"string" required:"true"`

	// The input mode that the algorithm supports: File or Pipe. In File input mode,
	// Amazon SageMaker downloads the training data from Amazon S3 to the storage
	// volume that is attached to the training instance and mounts the directory
	// to the Docker volume for the training container. In Pipe input mode, Amazon
	// SageMaker streams data directly from Amazon S3 to the container.
	//
	// If you specify File mode, make sure that you provision the storage volume
	// that is attached to the training instance with enough capacity to accommodate
	// the training data downloaded from Amazon S3, the model artifacts, and intermediate
	// information.
	//
	// For more information about input modes, see Algorithms (http://docs.aws.amazon.com/sagemaker/latest/dg/algos.html)
	//
	// TrainingInputMode is a required field
	TrainingInputMode TrainingInputMode `type:"string" required:"true" enum:"true"`
	// contains filtered or unexported fields
}

type HyperParameterTrainingJobDefinition struct {

	// The HyperParameterAlgorithmSpecification object that specifies the algorithm
	// to use for the training jobs that the tuning job launches.
	//
	// AlgorithmSpecification is a required field
	AlgorithmSpecification *HyperParameterAlgorithmSpecification `type:"structure" required:"true"`

	// An array of Channel objects that specify the input for the training jobs
	// that the tuning job launches.
	//
	// InputDataConfig is a required field
	InputDataConfig []Channel `min:"1" type:"list" required:"true"`

	// Specifies the path to the Amazon S3 bucket where you store model artifacts
	// from the training jobs that the tuning job launches.
	//
	// OutputDataConfig is a required field
	OutputDataConfig *OutputDataConfig `type:"structure" required:"true"`

	// The resources, including the compute instances and storage volumes, to use
	// for the training jobs that the tuning job launches.
	//
	// Storage volumes store model artifacts and incremental states. Training algorithms
	// might also use storage volumes for scratch space. If you want Amazon SageMaker
	// to use the storage volume to store the training data, choose File as the
	// TrainingInputMode in the algorithm specification. For distributed training
	// algorithms, specify an instance count greater than 1.
	//
	// ResourceConfig is a required field
	ResourceConfig *ResourceConfig `type:"structure" required:"true"`

	// The Amazon Resource Name (ARN) of the IAM role associated with the training
	// jobs that the tuning job launches.
	//
	// RoleArn is a required field
	RoleArn *string `min:"20" type:"string" required:"true"`

	// Specifies the values of hyperparameters that do not change for the tuning
	// job.
	StaticHyperParameters map[string]string `type:"map"`

	// Sets a maximum duration for the training jobs that the tuning job launches.
	// Use this parameter to limit model training costs.
	//
	// To stop a job, Amazon SageMaker sends the algorithm the SIGTERM signal. This
	// delays job termination for 120 seconds. Algorithms might use this 120-second
	// window to save the model artifacts.
	//
	// When Amazon SageMaker terminates a job because the stopping condition has
	// been met, training algorithms provided by Amazon SageMaker save the intermediate
	// results of the job.
	//
	// StoppingCondition is a required field
	StoppingCondition *StoppingCondition `type:"structure" required:"true"`

	// The VpcConfig object that specifies the VPC that you want the training jobs
	// that this hyperparameter tuning job launches to connect to. Control access
	// to and from your training container by configuring the VPC. For more information,
	// see train-vpc.
	VpcConfig *VpcConfig `type:"structure"`
	// contains filtered or unexported fields
}

type HyperParameterTrainingJobSummary struct {

	// The date and time that the training job was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The reason that the training job failed.
	FailureReason *string `type:"string"`

	// The FinalHyperParameterTuningJobObjectiveMetric object that specifies the
	// value of the objective metric of the tuning job that launched this training
	// job.
	FinalHyperParameterTuningJobObjectiveMetric *FinalHyperParameterTuningJobObjectiveMetric `type:"structure"`

	// The status of the objective metric for the training job:
	//
	//    * Succeeded: The final objective metric for the training job was evaluated
	//    by the hyperparameter tuning job and used in the hyperparameter tuning
	//    process.
	//
	//    * Pending: The training job is in progress and evaluation of its final
	//    objective metric is pending.
	//
	//    * Failed: The final objective metric for the training job was not evaluated,
	//    and was not used in the hyperparameter tuning process. This typically
	//    occurs when the training job failed or did not emit an objective metric.
	ObjectiveStatus ObjectiveStatus `type:"string" enum:"true"`

	// The date and time that the training job ended.
	TrainingEndTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the training job.
	//
	// TrainingJobArn is a required field
	TrainingJobArn *string `type:"string" required:"true"`

	// The name of the training job.
	//
	// TrainingJobName is a required field
	TrainingJobName *string `min:"1" type:"string" required:"true"`

	// The status of the training job.
	//
	// TrainingJobStatus is a required field
	TrainingJobStatus TrainingJobStatus `type:"string" required:"true" enum:"true"`

	// The date and time that the training job started.
	TrainingStartTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A list of the hyperparameters for which you specified ranges to search.
	//
	// TunedHyperParameters is a required field
	TunedHyperParameters map[string]string `type:"map" required:"true"`
	// contains filtered or unexported fields
}

type HyperParameterTuningJobConfig struct {

	// The HyperParameterTuningJobObjective object that specifies the objective
	// metric for this tuning job.
	//
	// HyperParameterTuningJobObjective is a required field
	HyperParameterTuningJobObjective *HyperParameterTuningJobObjective `type:"structure" required:"true"`

	// The ParameterRanges object that specifies the ranges of hyperparameters that
	// this tuning job searches.
	//
	// ParameterRanges is a required field
	ParameterRanges *ParameterRanges `type:"structure" required:"true"`

	// The ResourceLimits object that specifies the maximum number of training jobs
	// and parallel training jobs for this tuning job.
	//
	// ResourceLimits is a required field
	ResourceLimits *ResourceLimits `type:"structure" required:"true"`

	// Specifies the search strategy for hyperparameters. Currently, the only valid
	// value is Bayesian.
	//
	// Strategy is a required field
	Strategy HyperParameterTuningJobStrategyType `type:"string" required:"true" enum:"true"`
	// contains filtered or unexported fields
}

type HyperParameterTuningJobObjective struct {

	// The name of the metric to use for the objective metric.
	//
	// MetricName is a required field
	MetricName *string `min:"1" type:"string" required:"true"`

	// Whether to minimize or maximize the objective metric.
	//
	// Type is a required field
	Type HyperParameterTuningJobObjectiveType `type:"string" required:"true" enum:"true"`
	// contains filtered or unexported fields
}

type HyperParameterTuningJobObjectiveType string

const (
	HyperParameterTuningJobObjectiveTypeMaximize HyperParameterTuningJobObjectiveType = "Maximize"
	HyperParameterTuningJobObjectiveTypeMinimize HyperParameterTuningJobObjectiveType = "Minimize"
)

type HyperParameterTuningJobSortByOptions string

const (
	HyperParameterTuningJobSortByOptionsName         HyperParameterTuningJobSortByOptions = "Name"
	HyperParameterTuningJobSortByOptionsStatus       HyperParameterTuningJobSortByOptions = "Status"
	HyperParameterTuningJobSortByOptionsCreationTime HyperParameterTuningJobSortByOptions = "CreationTime"
)

type HyperParameterTuningJobStatus string

const (
	HyperParameterTuningJobStatusCompleted  HyperParameterTuningJobStatus = "Completed"
	HyperParameterTuningJobStatusInProgress HyperParameterTuningJobStatus = "InProgress"
	HyperParameterTuningJobStatusFailed     HyperParameterTuningJobStatus = "Failed"
	HyperParameterTuningJobStatusStopped    HyperParameterTuningJobStatus = "Stopped"
	HyperParameterTuningJobStatusStopping   HyperParameterTuningJobStatus = "Stopping"
)

type HyperParameterTuningJobStrategyType string

const (
	HyperParameterTuningJobStrategyTypeBayesian HyperParameterTuningJobStrategyType = "Bayesian"
)

type HyperParameterTuningJobSummary struct {

	// The date and time that the tuning job was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The date and time that the tuning job ended.
	HyperParameterTuningEndTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the tuning job.
	//
	// HyperParameterTuningJobArn is a required field
	HyperParameterTuningJobArn *string `type:"string" required:"true"`

	// The name of the tuning job.
	//
	// HyperParameterTuningJobName is a required field
	HyperParameterTuningJobName *string `min:"1" type:"string" required:"true"`

	// The status of the tuning job.
	//
	// HyperParameterTuningJobStatus is a required field
	HyperParameterTuningJobStatus HyperParameterTuningJobStatus `type:"string" required:"true" enum:"true"`

	// The date and time that the tuning job was modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The ObjectiveStatusCounters object that specifies the numbers of training
	// jobs, categorized by objective metric status, that this tuning job launched.
	//
	// ObjectiveStatusCounters is a required field
	ObjectiveStatusCounters *ObjectiveStatusCounters `type:"structure" required:"true"`

	// The ResourceLimits object that specifies the maximum number of training jobs
	// and parallel training jobs allowed for this tuning job.
	ResourceLimits *ResourceLimits `type:"structure"`

	// Specifies the search strategy hyperparameter tuning uses to choose which
	// hyperparameters to use for each iteration. Currently, the only valid value
	// is Bayesian.
	//
	// Strategy is a required field
	Strategy HyperParameterTuningJobStrategyType `type:"string" required:"true" enum:"true"`

	// The TrainingJobStatusCounters object that specifies the numbers of training
	// jobs, categorized by status, that this tuning job launched.
	//
	// TrainingJobStatusCounters is a required field
	TrainingJobStatusCounters *TrainingJobStatusCounters `type:"structure" required:"true"`
	// contains filtered or unexported fields
}

type InstanceType string

const (
	InstanceTypeMlT2Medium   InstanceType = "ml.t2.medium"
	InstanceTypeMlT2Large    InstanceType = "ml.t2.large"
	InstanceTypeMlT2Xlarge   InstanceType = "ml.t2.xlarge"
	InstanceTypeMlT22xlarge  InstanceType = "ml.t2.2xlarge"
	InstanceTypeMlM4Xlarge   InstanceType = "ml.m4.xlarge"
	InstanceTypeMlM42xlarge  InstanceType = "ml.m4.2xlarge"
	InstanceTypeMlM44xlarge  InstanceType = "ml.m4.4xlarge"
	InstanceTypeMlM410xlarge InstanceType = "ml.m4.10xlarge"
	InstanceTypeMlM416xlarge InstanceType = "ml.m4.16xlarge"
	InstanceTypeMlP2Xlarge   InstanceType = "ml.p2.xlarge"
	InstanceTypeMlP28xlarge  InstanceType = "ml.p2.8xlarge"
	InstanceTypeMlP216xlarge InstanceType = "ml.p2.16xlarge"
	InstanceTypeMlP32xlarge  InstanceType = "ml.p3.2xlarge"
	InstanceTypeMlP38xlarge  InstanceType = "ml.p3.8xlarge"
	InstanceTypeMlP316xlarge InstanceType = "ml.p3.16xlarge"
)

type IntegerParameterRange struct {

	// The maximum value of the hyperparameter to search.
	//
	// MaxValue is a required field
	MaxValue *string `type:"string" required:"true"`

	// The minimum value of the hyperparameter to search.
	//
	// MinValue is a required field
	MinValue *string `type:"string" required:"true"`

	// The name of the hyperparameter to search.
	//
	// Name is a required field
	Name *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type ListEndpointConfigsInput struct {

	// A filter that returns only endpoint configurations created after the specified
	// time (timestamp).
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only endpoint configurations created before the specified
	// time (timestamp).
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of training jobs to return in the response.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the endpoint configuration name. This filter returns only endpoint
	// configurations whose name contains the specified string.
	NameContains *string `type:"string"`

	// If the result of the previous ListEndpointConfig request was truncated, the
	// response includes a NextToken. To retrieve the next set of endpoint configurations,
	// use the token in the next request.
	NextToken *string `type:"string"`

	// The field to sort results by. The default is CreationTime.
	SortBy EndpointConfigSortKey `type:"string" enum:"true"`

	// The sort order for results. The default is Ascending.
	SortOrder OrderKey `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListEndpointConfigsOutput struct {

	// An array of endpoint configurations.
	//
	// EndpointConfigs is a required field
	EndpointConfigs []EndpointConfigSummary `type:"list" required:"true"`

	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of endpoint configurations, use it in the subsequent request
	NextToken *string `type:"string"`
	// contains filtered or unexported fields
}

type ListEndpointConfigsPager struct {
	aws.Pager
}

type ListEndpointConfigsRequest struct {
	*aws.Request
	Input *ListEndpointConfigsInput
	Copy  func(*ListEndpointConfigsInput) ListEndpointConfigsRequest
}

type ListEndpointsInput struct {

	// A filter that returns only endpoints that were created after the specified
	// time (timestamp).
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only endpoints that were created before the specified
	// time (timestamp).
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only endpoints that were modified after the specified
	// timestamp.
	LastModifiedTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only endpoints that were modified before the specified
	// timestamp.
	LastModifiedTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of endpoints to return in the response.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in endpoint names. This filter returns only endpoints whose name
	// contains the specified string.
	NameContains *string `type:"string"`

	// If the result of a ListEndpoints request was truncated, the response includes
	// a NextToken. To retrieve the next set of endpoints, use the token in the
	// next request.
	NextToken *string `type:"string"`

	// Sorts the list of results. The default is CreationTime.
	SortBy EndpointSortKey `type:"string" enum:"true"`

	// The sort order for results. The default is Ascending.
	SortOrder OrderKey `type:"string" enum:"true"`

	// A filter that returns only endpoints with the specified status.
	StatusEquals EndpointStatus `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListEndpointsOutput struct {

	// An array or endpoint objects.
	//
	// Endpoints is a required field
	Endpoints []EndpointSummary `type:"list" required:"true"`

	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of training jobs, use it in the subsequent request.
	NextToken *string `type:"string"`
	// contains filtered or unexported fields
}

type ListEndpointsPager struct {
	aws.Pager
}

type ListEndpointsRequest struct {
	*aws.Request
	Input *ListEndpointsInput
	Copy  func(*ListEndpointsInput) ListEndpointsRequest
}

type ListHyperParameterTuningJobsInput struct {

	// A filter that returns only tuning jobs that were created after the specified
	// time.
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only tuning jobs that were created before the specified
	// time.
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only tuning jobs that were modified after the specified
	// time.
	LastModifiedTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only tuning jobs that were modified before the specified
	// time.
	LastModifiedTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of tuning jobs to return. The default value is 10.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the tuning job name. This filter returns only tuning jobs whose
	// name contains the specified string.
	NameContains *string `type:"string"`

	// If the result of the previous ListHyperParameterTuningJobs request was truncated,
	// the response includes a NextToken. To retrieve the next set of tuning jobs,
	// use the token in the next request.
	NextToken *string `type:"string"`

	// The field to sort results by. The default is Name.
	SortBy HyperParameterTuningJobSortByOptions `type:"string" enum:"true"`

	// The sort order for results. The default is Ascending.
	SortOrder SortOrder `type:"string" enum:"true"`

	// A filter that returns only tuning jobs with the specified status.
	StatusEquals HyperParameterTuningJobStatus `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListHyperParameterTuningJobsOutput struct {

	// A list of HyperParameterTuningJobSummary objects that describe the tuning
	// jobs that the ListHyperParameterTuningJobs request returned.
	//
	// HyperParameterTuningJobSummaries is a required field
	HyperParameterTuningJobSummaries []HyperParameterTuningJobSummary `type:"list" required:"true"`

	// If the result of this ListHyperParameterTuningJobs request was truncated,
	// the response includes a NextToken. To retrieve the next set of tuning jobs,
	// use the token in the next request.
	NextToken *string `type:"string"`
	// contains filtered or unexported fields
}

type ListHyperParameterTuningJobsPager struct {
	aws.Pager
}

type ListHyperParameterTuningJobsRequest struct {
	*aws.Request
	Input *ListHyperParameterTuningJobsInput
	Copy  func(*ListHyperParameterTuningJobsInput) ListHyperParameterTuningJobsRequest
}

type ListModelsInput struct {

	// A filter that returns only models created after the specified time (timestamp).
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only models created before the specified time (timestamp).
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of models to return in the response.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the training job name. This filter returns only models in the
	// training job whose name contains the specified string.
	NameContains *string `type:"string"`

	// If the response to a previous ListModels request was truncated, the response
	// includes a NextToken. To retrieve the next set of models, use the token in
	// the next request.
	NextToken *string `type:"string"`

	// Sorts the list of results. The default is CreationTime.
	SortBy ModelSortKey `type:"string" enum:"true"`

	// The sort order for results. The default is Ascending.
	SortOrder OrderKey `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListModelsOutput struct {

	// An array of ModelSummary objects, each of which lists a model.
	//
	// Models is a required field
	Models []ModelSummary `type:"list" required:"true"`

	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of models, use it in the subsequent request.
	NextToken *string `type:"string"`
	// contains filtered or unexported fields
}

type ListModelsPager struct {
	aws.Pager
}

type ListModelsRequest struct {
	*aws.Request
	Input *ListModelsInput
	Copy  func(*ListModelsInput) ListModelsRequest
}

type ListNotebookInstanceLifecycleConfigsInput struct {

	// A filter that returns only lifecycle configurations that were created after
	// the specified time (timestamp).
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only lifecycle configurations that were created before
	// the specified time (timestamp).
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only lifecycle configurations that were modified after
	// the specified time (timestamp).
	LastModifiedTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only lifecycle configurations that were modified before
	// the specified time (timestamp).
	LastModifiedTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of lifecycle configurations to return in the response.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the lifecycle configuration name. This filter returns only lifecycle
	// configurations whose name contains the specified string.
	NameContains *string `type:"string"`

	// If the result of a ListNotebookInstanceLifecycleConfigs request was truncated,
	// the response includes a NextToken. To get the next set of lifecycle configurations,
	// use the token in the next request.
	NextToken *string `type:"string"`

	// Sorts the list of results. The default is CreationTime.
	SortBy NotebookInstanceLifecycleConfigSortKey `type:"string" enum:"true"`

	// The sort order for results.
	SortOrder NotebookInstanceLifecycleConfigSortOrder `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListNotebookInstanceLifecycleConfigsOutput struct {

	// If the response is truncated, Amazon SageMaker returns this token. To get
	// the next set of lifecycle configurations, use it in the next request.
	NextToken *string `type:"string"`

	// An array of NotebookInstanceLifecycleConfiguration objects, each listing
	// a lifecycle configuration.
	NotebookInstanceLifecycleConfigs []NotebookInstanceLifecycleConfigSummary `type:"list"`
	// contains filtered or unexported fields
}

type ListNotebookInstanceLifecycleConfigsPager struct {
	aws.Pager
}

type ListNotebookInstanceLifecycleConfigsRequest struct {
	*aws.Request
	Input *ListNotebookInstanceLifecycleConfigsInput
	Copy  func(*ListNotebookInstanceLifecycleConfigsInput) ListNotebookInstanceLifecycleConfigsRequest
}

type ListNotebookInstancesInput struct {

	// A filter that returns only notebook instances that were created after the
	// specified time (timestamp).
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only notebook instances that were created before the
	// specified time (timestamp).
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only notebook instances that were modified after the
	// specified time (timestamp).
	LastModifiedTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only notebook instances that were modified before the
	// specified time (timestamp).
	LastModifiedTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of notebook instances to return.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the notebook instances' name. This filter returns only notebook
	// instances whose name contains the specified string.
	NameContains *string `type:"string"`

	// If the previous call to the ListNotebookInstances is truncated, the response
	// includes a NextToken. You can use this token in your subsequent ListNotebookInstances
	// request to fetch the next set of notebook instances.
	//
	// You might specify a filter or a sort order in your request. When response
	// is truncated, you must use the same values for the filer and sort order in
	// the next request.
	NextToken *string `type:"string"`

	// A string in the name of a notebook instances lifecycle configuration associated
	// with this notebook instance. This filter returns only notebook instances
	// associated with a lifecycle configuration with a name that contains the specified
	// string.
	NotebookInstanceLifecycleConfigNameContains *string `type:"string"`

	// The field to sort results by. The default is Name.
	SortBy NotebookInstanceSortKey `type:"string" enum:"true"`

	// The sort order for results.
	SortOrder NotebookInstanceSortOrder `type:"string" enum:"true"`

	// A filter that returns only notebook instances with the specified status.
	StatusEquals NotebookInstanceStatus `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListNotebookInstancesOutput struct {

	// If the response to the previous ListNotebookInstances request was truncated,
	// Amazon SageMaker returns this token. To retrieve the next set of notebook
	// instances, use the token in the next request.
	NextToken *string `type:"string"`

	// An array of NotebookInstanceSummary objects, one for each notebook instance.
	NotebookInstances []NotebookInstanceSummary `type:"list"`
	// contains filtered or unexported fields
}

type ListNotebookInstancesPager struct {
	aws.Pager
}

type ListNotebookInstancesRequest struct {
	*aws.Request
	Input *ListNotebookInstancesInput
	Copy  func(*ListNotebookInstancesInput) ListNotebookInstancesRequest
}

type ListTagsInput struct {

	// Maximum number of tags to return.
	MaxResults *int64 `min:"50" type:"integer"`

	// If the response to the previous ListTags request is truncated, Amazon SageMaker
	// returns this token. To retrieve the next set of tags, use it in the subsequent
	// request.
	NextToken *string `type:"string"`

	// The Amazon Resource Name (ARN) of the resource whose tags you want to retrieve.
	//
	// ResourceArn is a required field
	ResourceArn *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type ListTagsOutput struct {

	// If response is truncated, Amazon SageMaker includes a token in the response.
	// You can use this token in your subsequent request to fetch next set of tokens.
	NextToken *string `type:"string"`

	// An array of Tag objects, each with a tag key and a value.
	Tags []Tag `type:"list"`
	// contains filtered or unexported fields
}

type ListTagsPager struct {
	aws.Pager
}

type ListTagsRequest struct {
	*aws.Request
	Input *ListTagsInput
	Copy  func(*ListTagsInput) ListTagsRequest
}

type ListTrainingJobsForHyperParameterTuningJobInput struct {

	// The name of the tuning job whose training jobs you want to list.
	//
	// HyperParameterTuningJobName is a required field
	HyperParameterTuningJobName *string `min:"1" type:"string" required:"true"`

	// The maximum number of training jobs to return. The default value is 10.
	MaxResults *int64 `min:"1" type:"integer"`

	// If the result of the previous ListTrainingJobsForHyperParameterTuningJob
	// request was truncated, the response includes a NextToken. To retrieve the
	// next set of training jobs, use the token in the next request.
	NextToken *string `type:"string"`

	// The field to sort results by. The default is Name.
	//
	// If the value of this field is FinalObjectiveMetricValue, any training jobs
	// that did not return an objective metric are not listed.
	SortBy TrainingJobSortByOptions `type:"string" enum:"true"`

	// The sort order for results. The default is Ascending.
	SortOrder SortOrder `type:"string" enum:"true"`

	// A filter that returns only training jobs with the specified status.
	StatusEquals TrainingJobStatus `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListTrainingJobsForHyperParameterTuningJobOutput struct {

	// If the result of this ListTrainingJobsForHyperParameterTuningJob request
	// was truncated, the response includes a NextToken. To retrieve the next set
	// of training jobs, use the token in the next request.
	NextToken *string `type:"string"`

	// A list of TrainingJobSummary objects that describe the training jobs that
	// the ListTrainingJobsForHyperParameterTuningJob request returned.
	//
	// TrainingJobSummaries is a required field
	TrainingJobSummaries []HyperParameterTrainingJobSummary `type:"list" required:"true"`
	// contains filtered or unexported fields
}

type ListTrainingJobsForHyperParameterTuningJobPager struct {
	aws.Pager
}

type ListTrainingJobsForHyperParameterTuningJobRequest struct {
	*aws.Request
	Input *ListTrainingJobsForHyperParameterTuningJobInput
	Copy  func(*ListTrainingJobsForHyperParameterTuningJobInput) ListTrainingJobsForHyperParameterTuningJobRequest
}

type ListTrainingJobsInput struct {

	// A filter that returns only training jobs created after the specified time
	// (timestamp).
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only training jobs created before the specified time
	// (timestamp).
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only training jobs modified after the specified time
	// (timestamp).
	LastModifiedTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only training jobs modified before the specified time
	// (timestamp).
	LastModifiedTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of training jobs to return in the response.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the training job name. This filter returns only training jobs
	// whose name contains the specified string.
	NameContains *string `type:"string"`

	// If the result of the previous ListTrainingJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of training jobs,
	// use the token in the next request.
	NextToken *string `type:"string"`

	// The field to sort results by. The default is CreationTime.
	SortBy SortBy `type:"string" enum:"true"`

	// The sort order for results. The default is Ascending.
	SortOrder SortOrder `type:"string" enum:"true"`

	// A filter that retrieves only training jobs with a specific status.
	StatusEquals TrainingJobStatus `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListTrainingJobsOutput struct {

	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of training jobs, use it in the subsequent request.
	NextToken *string `type:"string"`

	// An array of TrainingJobSummary objects, each listing a training job.
	//
	// TrainingJobSummaries is a required field
	TrainingJobSummaries []TrainingJobSummary `type:"list" required:"true"`
	// contains filtered or unexported fields
}

type ListTrainingJobsPager struct {
	aws.Pager
}

type ListTrainingJobsRequest struct {
	*aws.Request
	Input *ListTrainingJobsInput
	Copy  func(*ListTrainingJobsInput) ListTrainingJobsRequest
}

type ListTransformJobsInput struct {

	// A filter that returns only transform jobs created after the specified time.
	CreationTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only transform jobs created before the specified time.
	CreationTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only transform jobs modified after the specified time.
	LastModifiedTimeAfter *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A filter that returns only transform jobs modified before the specified time.
	LastModifiedTimeBefore *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The maximum number of transform jobs to return in the response. The default
	// value is 10.
	MaxResults *int64 `min:"1" type:"integer"`

	// A string in the transform job name. This filter returns only transform jobs
	// whose name contains the specified string.
	NameContains *string `type:"string"`

	// If the result of the previous ListTransformJobs request was truncated, the
	// response includes a NextToken. To retrieve the next set of transform jobs,
	// use the token in the next request.
	NextToken *string `type:"string"`

	// The field to sort results by. The default is CreationTime.
	SortBy SortBy `type:"string" enum:"true"`

	// The sort order for results. The default is Descending.
	SortOrder SortOrder `type:"string" enum:"true"`

	// A filter that retrieves only transform jobs with a specific status.
	StatusEquals TransformJobStatus `type:"string" enum:"true"`
	// contains filtered or unexported fields
}

type ListTransformJobsOutput struct {

	// If the response is truncated, Amazon SageMaker returns this token. To retrieve
	// the next set of transform jobs, use it in the next request.
	NextToken *string `type:"string"`

	// An array of TransformJobSummary objects.
	//
	// TransformJobSummaries is a required field
	TransformJobSummaries []TransformJobSummary `type:"list" required:"true"`
	// contains filtered or unexported fields
}

type ListTransformJobsPager struct {
	aws.Pager
}

type ListTransformJobsRequest struct {
	*aws.Request
	Input *ListTransformJobsInput
	Copy  func(*ListTransformJobsInput) ListTransformJobsRequest
}

type MetricDefinition struct {

	// The name of the metric.
	//
	// Name is a required field
	Name *string `min:"1" type:"string" required:"true"`

	// A regular expression that searches the output of a training job and gets
	// the value of the metric. For more information about using regular expressions
	// to define metrics, see automatic-model-tuning-define-metrics.
	//
	// Regex is a required field
	Regex *string `min:"1" type:"string" required:"true"`
	// contains filtered or unexported fields
}

type ModelArtifacts struct {

	// The path of the S3 object that contains the model artifacts. For example,
	// s3://bucket-name/keynameprefix/model.tar.gz.
	//
	// S3ModelArtifacts is a required field
	S3ModelArtifacts *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type ModelSortKey string

const (
	ModelSortKeyName         ModelSortKey = "Name"
	ModelSortKeyCreationTime ModelSortKey = "CreationTime"
)

type ModelSummary struct {

	// A timestamp that indicates when the model was created.
	//
	// CreationTime is a required field
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix" required:"true"`

	// The Amazon Resource Name (ARN) of the model.
	//
	// ModelArn is a required field
	ModelArn *string `min:"20" type:"string" required:"true"`

	// The name of the model that you want a summary for.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type NotebookInstanceLifecycleConfigSortKey string

const (
	NotebookInstanceLifecycleConfigSortKeyName             NotebookInstanceLifecycleConfigSortKey = "Name"
	NotebookInstanceLifecycleConfigSortKeyCreationTime     NotebookInstanceLifecycleConfigSortKey = "CreationTime"
	NotebookInstanceLifecycleConfigSortKeyLastModifiedTime NotebookInstanceLifecycleConfigSortKey = "LastModifiedTime"
)

type NotebookInstanceLifecycleConfigSortOrder string

const (
	NotebookInstanceLifecycleConfigSortOrderAscending  NotebookInstanceLifecycleConfigSortOrder = "Ascending"
	NotebookInstanceLifecycleConfigSortOrderDescending NotebookInstanceLifecycleConfigSortOrder = "Descending"
)

type NotebookInstanceLifecycleConfigSummary struct {

	// A timestamp that tells when the lifecycle configuration was created.
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// A timestamp that tells when the lifecycle configuration was last modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the lifecycle configuration.
	//
	// NotebookInstanceLifecycleConfigArn is a required field
	NotebookInstanceLifecycleConfigArn *string `type:"string" required:"true"`

	// The name of the lifecycle configuration.
	//
	// NotebookInstanceLifecycleConfigName is a required field
	NotebookInstanceLifecycleConfigName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type NotebookInstanceLifecycleHook struct {

	// A base64-encoded string that contains a shell script for a notebook instance
	// lifecycle configuration.
	Content *string `min:"1" type:"string"`
	// contains filtered or unexported fields
}

type NotebookInstanceSortKey string

const (
	NotebookInstanceSortKeyName         NotebookInstanceSortKey = "Name"
	NotebookInstanceSortKeyCreationTime NotebookInstanceSortKey = "CreationTime"
	NotebookInstanceSortKeyStatus       NotebookInstanceSortKey = "Status"
)

type NotebookInstanceSortOrder string

const (
	NotebookInstanceSortOrderAscending  NotebookInstanceSortOrder = "Ascending"
	NotebookInstanceSortOrderDescending NotebookInstanceSortOrder = "Descending"
)

type NotebookInstanceStatus string

const (
	NotebookInstanceStatusPending   NotebookInstanceStatus = "Pending"
	NotebookInstanceStatusInService NotebookInstanceStatus = "InService"
	NotebookInstanceStatusStopping  NotebookInstanceStatus = "Stopping"
	NotebookInstanceStatusStopped   NotebookInstanceStatus = "Stopped"
	NotebookInstanceStatusFailed    NotebookInstanceStatus = "Failed"
	NotebookInstanceStatusDeleting  NotebookInstanceStatus = "Deleting"
	NotebookInstanceStatusUpdating  NotebookInstanceStatus = "Updating"
)

type NotebookInstanceSummary struct {

	// A timestamp that shows when the notebook instance was created.
	CreationTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The type of ML compute instance that the notebook instance is running on.
	InstanceType InstanceType `type:"string" enum:"true"`

	// A timestamp that shows when the notebook instance was last modified.
	LastModifiedTime *time.Time `type:"timestamp" timestampFormat:"unix"`

	// The Amazon Resource Name (ARN) of the notebook instance.
	//
	// NotebookInstanceArn is a required field
	NotebookInstanceArn *string `type:"string" required:"true"`

	// The name of a notebook instance lifecycle configuration associated with this
	// notebook instance.
	//
	// For information about notebook instance lifestyle configurations, see notebook-lifecycle-config.
	NotebookInstanceLifecycleConfigName *string `type:"string"`

	// The name of the notebook instance that you want a summary for.
	//
	// NotebookInstanceName is a required field
	NotebookInstanceName *string `type:"string" required:"true"`

	// The status of the notebook instance.
	NotebookInstanceStatus NotebookInstanceStatus `type:"string" enum:"true"`

	// The URL that you use to connect to the Jupyter instance running in your notebook
	// instance.
	Url *string `type:"string"`
	// contains filtered or unexported fields
}

type ObjectiveStatus string

const (
	ObjectiveStatusSucceeded ObjectiveStatus = "Succeeded"
	ObjectiveStatusPending   ObjectiveStatus = "Pending"
	ObjectiveStatusFailed    ObjectiveStatus = "Failed"
)

type ObjectiveStatusCounters struct {

	// The number of training jobs whose final objective metric was not evaluated
	// and used in the hyperparameter tuning process. This typically occurs when
	// the training job failed or did not emit an objective metric.
	Failed *int64 `type:"integer"`

	// The number of training jobs that are in progress and pending evaluation of
	// their final objective metric.
	Pending *int64 `type:"integer"`

	// The number of training jobs whose final objective metric was evaluated by
	// the hyperparameter tuning job and used in the hyperparameter tuning process.
	Succeeded *int64 `type:"integer"`
	// contains filtered or unexported fields
}

type OrderKey string

const (
	OrderKeyAscending  OrderKey = "Ascending"
	OrderKeyDescending OrderKey = "Descending"
)

type OutputDataConfig struct {

	// The AWS Key Management Service (AWS KMS) key that Amazon SageMaker uses to
	// encrypt the model artifacts at rest using Amazon S3 server-side encryption.
	//
	// If you don't provide the KMS key ID, Amazon SageMaker uses the default KMS
	// key for Amazon S3 for your role's account. For more information, see KMS-Managed
	// Encryption Keys (https://docs.aws.amazon.com/AmazonS3/latest/dev/UsingKMSEncryption.html)
	// in Amazon Simple Storage Service developer guide.
	//
	// The KMS key policy must grant permission to the IAM role you specify in your
	// CreateTrainingJob request. Using Key Policies in AWS KMS (http://docs.aws.amazon.com/kms/latest/developerguide/key-policies.html)
	// in the AWS Key Management Service Developer Guide.
	KmsKeyId *string `type:"string"`

	// Identifies the S3 path where you want Amazon SageMaker to store the model
	// artifacts. For example, s3://bucket-name/key-name-prefix.
	//
	// S3OutputPath is a required field
	S3OutputPath *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type ParameterRanges struct {

	// The array of CategoricalParameterRange objects that specify ranges of categorical
	// hyperparameters that a hyperparameter tuning job searches.
	CategoricalParameterRanges []CategoricalParameterRange `type:"list"`

	// The array of ContinuousParameterRange objects that specify ranges of continuous
	// hyperparameters that a hyperparameter tuning job searches.
	ContinuousParameterRanges []ContinuousParameterRange `type:"list"`

	// The array of IntegerParameterRange objects that specify ranges of integer
	// hyperparameters that a hyperparameter tuning job searches.
	IntegerParameterRanges []IntegerParameterRange `type:"list"`
	// contains filtered or unexported fields
}

type ProductionVariant struct {

	// Number of instances to launch initially.
	//
	// InitialInstanceCount is a required field
	InitialInstanceCount *int64 `min:"1" type:"integer" required:"true"`

	// Determines initial traffic distribution among all of the models that you
	// specify in the endpoint configuration. The traffic to a production variant
	// is determined by the ratio of the VariantWeight to the sum of all VariantWeight
	// values across all ProductionVariants. If unspecified, it defaults to 1.0.
	InitialVariantWeight *float64 `type:"float"`

	// The ML compute instance type.
	//
	// InstanceType is a required field
	InstanceType ProductionVariantInstanceType `type:"string" required:"true" enum:"true"`

	// The name of the model that you want to host. This is the name that you specified
	// when creating the model.
	//
	// ModelName is a required field
	ModelName *string `type:"string" required:"true"`

	// The name of the production variant.
	//
	// VariantName is a required field
	VariantName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type ProductionVariantInstanceType string

const (
	ProductionVariantInstanceTypeMlT2Medium   ProductionVariantInstanceType = "ml.t2.medium"
	ProductionVariantInstanceTypeMlT2Large    ProductionVariantInstanceType = "ml.t2.large"
	ProductionVariantInstanceTypeMlT2Xlarge   ProductionVariantInstanceType = "ml.t2.xlarge"
	ProductionVariantInstanceTypeMlT22xlarge  ProductionVariantInstanceType = "ml.t2.2xlarge"
	ProductionVariantInstanceTypeMlM4Xlarge   ProductionVariantInstanceType = "ml.m4.xlarge"
	ProductionVariantInstanceTypeMlM42xlarge  ProductionVariantInstanceType = "ml.m4.2xlarge"
	ProductionVariantInstanceTypeMlM44xlarge  ProductionVariantInstanceType = "ml.m4.4xlarge"
	ProductionVariantInstanceTypeMlM410xlarge ProductionVariantInstanceType = "ml.m4.10xlarge"
	ProductionVariantInstanceTypeMlM416xlarge ProductionVariantInstanceType = "ml.m4.16xlarge"
	ProductionVariantInstanceTypeMlM5Large    ProductionVariantInstanceType = "ml.m5.large"
	ProductionVariantInstanceTypeMlM5Xlarge   ProductionVariantInstanceType = "ml.m5.xlarge"
	ProductionVariantInstanceTypeMlM52xlarge  ProductionVariantInstanceType = "ml.m5.2xlarge"
	ProductionVariantInstanceTypeMlM54xlarge  ProductionVariantInstanceType = "ml.m5.4xlarge"
	ProductionVariantInstanceTypeMlM512xlarge ProductionVariantInstanceType = "ml.m5.12xlarge"
	ProductionVariantInstanceTypeMlM524xlarge ProductionVariantInstanceType = "ml.m5.24xlarge"
	ProductionVariantInstanceTypeMlC4Large    ProductionVariantInstanceType = "ml.c4.large"
	ProductionVariantInstanceTypeMlC4Xlarge   ProductionVariantInstanceType = "ml.c4.xlarge"
	ProductionVariantInstanceTypeMlC42xlarge  ProductionVariantInstanceType = "ml.c4.2xlarge"
	ProductionVariantInstanceTypeMlC44xlarge  ProductionVariantInstanceType = "ml.c4.4xlarge"
	ProductionVariantInstanceTypeMlC48xlarge  ProductionVariantInstanceType = "ml.c4.8xlarge"
	ProductionVariantInstanceTypeMlP2Xlarge   ProductionVariantInstanceType = "ml.p2.xlarge"
	ProductionVariantInstanceTypeMlP28xlarge  ProductionVariantInstanceType = "ml.p2.8xlarge"
	ProductionVariantInstanceTypeMlP216xlarge ProductionVariantInstanceType = "ml.p2.16xlarge"
	ProductionVariantInstanceTypeMlP32xlarge  ProductionVariantInstanceType = "ml.p3.2xlarge"
	ProductionVariantInstanceTypeMlP38xlarge  ProductionVariantInstanceType = "ml.p3.8xlarge"
	ProductionVariantInstanceTypeMlP316xlarge ProductionVariantInstanceType = "ml.p3.16xlarge"
	ProductionVariantInstanceTypeMlC5Large    ProductionVariantInstanceType = "ml.c5.large"
	ProductionVariantInstanceTypeMlC5Xlarge   ProductionVariantInstanceType = "ml.c5.xlarge"
	ProductionVariantInstanceTypeMlC52xlarge  ProductionVariantInstanceType = "ml.c5.2xlarge"
	ProductionVariantInstanceTypeMlC54xlarge  ProductionVariantInstanceType = "ml.c5.4xlarge"
	ProductionVariantInstanceTypeMlC59xlarge  ProductionVariantInstanceType = "ml.c5.9xlarge"
	ProductionVariantInstanceTypeMlC518xlarge ProductionVariantInstanceType = "ml.c5.18xlarge"
)

type ProductionVariantSummary struct {

	// The number of instances associated with the variant.
	CurrentInstanceCount *int64 `min:"1" type:"integer"`

	// The weight associated with the variant.
	CurrentWeight *float64 `type:"float"`

	// An array of DeployedImage objects that specify the Amazon EC2 Container Registry
	// paths of the inference images deployed on instances of this ProductionVariant.
	DeployedImages []DeployedImage `type:"list"`

	// The number of instances requested in the UpdateEndpointWeightsAndCapacities
	// request.
	DesiredInstanceCount *int64 `min:"1" type:"integer"`

	// The requested weight, as specified in the UpdateEndpointWeightsAndCapacities
	// request.
	DesiredWeight *float64 `type:"float"`

	// The name of the variant.
	//
	// VariantName is a required field
	VariantName *string `type:"string" required:"true"`
	// contains filtered or unexported fields
}

type RecordWrapper string

const (
	RecordWrapperNone     RecordWrapper = "None"
	RecordWrapperRecordIo RecordWrapper = "RecordIO"
)

type ResourceConfig struct {

	// The number of ML compute instances to use. For distributed training, provide
	// a value greater than 1.
	//
	// InstanceCount is a required field
	InstanceCount *int64 `min:"1" type:"integer" required:"true"`

	// The ML compute instance type.
	//
	// InstanceType is a required field
	InstanceType TrainingInstanceType `type:"string" required:"true" enum:"true"`

	// The Amazon Resource Name (ARN) of a AWS Key Management Service key that Amazon
	// SageMaker uses to encrypt data on the storage volume attached to the ML compute
	// instance(s) that run the training job.
	VolumeKmsKeyId *string `type:"string"`

	// The size of the ML storage volume that you want to provision.
	//
	// ML storage volumes store model artifacts and incremental states. Training
	// algorithms might also use the ML storage volume for scratch space. If you
	// want to store the training data in the ML storage volume, choose File as
	// the TrainingInputMode in the algorithm specification.
	//
	// You must specify sufficient ML storage for your scenario.
	//
	// Amazon SageMaker supports only the General Purpose SSD (gp2) ML storage volume
	// type.
	//
	// VolumeSizeInGB is a required field
	VolumeSizeInGB *int64 `min:"1" type:"integer" required:"true"`
	// contains filtered or unexported fields
}

type ResourceLimits struct {

	// The maximum number of training jobs that a hyperparameter tuning job can
	// launch.
	//
	// MaxNumberOfTrainingJobs is a required field
	MaxNumberOfTrainingJobs *int64 `min:"1" type:"integer" required:"true"`

	// The maximum number of concurrent training jobs that a hyperparameter tuning
	// job can launch.
	//
	// MaxParallelTrainingJobs is a required field
	MaxParallelTrainingJobs *int64 `min:"1" type:"integer" required:"true"`
	// contains filtered or unexported fields
}

type S3DataDistribution string

const (
	S3DataDistributionFullyReplicated S3DataDistribution = "FullyReplicated"
	S3DataDistributionShardedByS3key  S3DataDistribution = "ShardedByS3Key"
)