Struct CreateDatasetInput

#[non_exhaustive]
pub struct CreateDatasetInput {
    pub flywheel_arn: Option<String>,
    pub dataset_name: Option<String>,
    pub dataset_type: Option<DatasetType>,
    pub description: Option<String>,
    pub input_data_config: Option<DatasetInputDataConfig>,
    pub client_request_token: Option<String>,
    pub tags: Option<Vec<Tag>>,
}

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

flywheel_arn: Option<String>

The Amazon Resource Number (ARN) of the flywheel of the flywheel to receive the data.

dataset_name: Option<String>

Name of the dataset.

dataset_type: Option<DatasetType>

The dataset type. You can specify that the data in a dataset is for training the model or for testing the model.

description: Option<String>

Description of the dataset.

input_data_config: Option<DatasetInputDataConfig>

Information about the input data configuration. The type of input data varies based on the format of the input and whether the data is for a classifier model or an entity recognition model.

client_request_token: Option<String>

A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.

tags: Option<Vec<Tag>>

Tags for the dataset.

Implementations

impl CreateDatasetInput

pub fn flywheel_arn(&self) -> Option<&str>

The Amazon Resource Number (ARN) of the flywheel of the flywheel to receive the data.

pub fn dataset_name(&self) -> Option<&str>

Name of the dataset.

pub fn dataset_type(&self) -> Option<&DatasetType>

The dataset type. You can specify that the data in a dataset is for training the model or for testing the model.

pub fn description(&self) -> Option<&str>

Description of the dataset.

pub fn input_data_config(&self) -> Option<&DatasetInputDataConfig>

Information about the input data configuration. The type of input data varies based on the format of the input and whether the data is for a classifier model or an entity recognition model.

pub fn client_request_token(&self) -> Option<&str>

A unique identifier for the request. If you don't set the client request token, Amazon Comprehend generates one.

pub fn tags(&self) -> &[Tag]

Tags for the dataset.

If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .tags.is_none().

impl CreateDatasetInput

pub fn builder() -> CreateDatasetInputBuilder

Creates a new builder-style object to manufacture CreateDatasetInput.

Trait Implementations

impl Clone for CreateDatasetInput

fn clone(&self) -> CreateDatasetInput

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for CreateDatasetInput

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

Formats the value using the given formatter.

impl PartialEq for CreateDatasetInput

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

Tests for self and other values to be equal, and is used by ==.

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

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl StructuralPartialEq for CreateDatasetInput