Struct rusoto_sagemaker::CreateTransformJobRequest

pub struct CreateTransformJobRequest {
    pub batch_strategy: Option<String>,
    pub environment: Option<HashMap<String, String>>,
    pub max_concurrent_transforms: Option<i64>,
    pub max_payload_in_mb: Option<i64>,
    pub model_name: String,
    pub tags: Option<Vec<Tag>>,
    pub transform_input: TransformInput,
    pub transform_job_name: String,
    pub transform_output: TransformOutput,
    pub transform_resources: TransformResources,
}

Fields

batch_strategy: Option<String>

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.

environment: Option<HashMap<String, String>>

The environment variables to set in the Docker container. We support up to 16 key and values entries in the map.

max_concurrent_transforms: Option<i64>

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.

max_payload_in_mb: Option<i64>

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.

model_name: String

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.

tags: Option<Vec<Tag>>

An array of key-value pairs. Adding tags is optional. For more information, see Using Cost Allocation Tags in the AWS Billing and Cost Management User Guide.

transform_input: TransformInput

Describes the input source and the way the transform job consumes it.

transform_job_name: String

The name of the transform job. The name must be unique within an AWS Region in an AWS account.

transform_output: TransformOutput

Describes the results of the transform job.

transform_resources: TransformResources

Describes the resources, including ML instance types and ML instance count, to use for the transform job.

Trait Implementations

impl Clone for CreateTransformJobRequest

fn clone(&self) -> CreateTransformJobRequest

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Default for CreateTransformJobRequest

fn default() -> CreateTransformJobRequest

Returns the "default value" for a type.

impl PartialEq<CreateTransformJobRequest> for CreateTransformJobRequest

fn eq(&self, other: &CreateTransformJobRequest) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &CreateTransformJobRequest) -> bool

This method tests for !=.

impl Debug for CreateTransformJobRequest

fn fmt(&self, f: &mut Formatter) -> Result

Formats the value using the given formatter.

impl Serialize for CreateTransformJobRequest

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where     __S: Serializer,

Serialize this value into the given Serde serializer.