Struct TrainedModelSummary 

#[non_exhaustive]
pub struct TrainedModelSummary {
    pub create_time: DateTime,
    pub update_time: DateTime,
    pub trained_model_arn: String,
    pub version_identifier: Option<String>,
    pub incremental_training_data_channels: Option<Vec<IncrementalTrainingDataChannelOutput>>,
    pub name: String,
    pub description: Option<String>,
    pub membership_identifier: String,
    pub collaboration_identifier: String,
    pub status: TrainedModelStatus,
    pub configured_model_algorithm_association_arn: String,
}

Summary information about the trained model.

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.

create_time: DateTime

The time at which the trained model was created.

update_time: DateTime

The most recent time at which the trained model was updated.

trained_model_arn: String

The Amazon Resource Name (ARN) of the trained model.

version_identifier: Option<String>

The version identifier of this trained model version.

incremental_training_data_channels: Option<Vec<IncrementalTrainingDataChannelOutput>>

Information about the incremental training data channels used to create this version of the trained model.

name: String

The name of the trained model.

description: Option<String>

The description of the trained model.

membership_identifier: String

The membership ID of the member that created the trained model.

collaboration_identifier: String

The collaboration ID of the collaboration that contains the trained model.

status: TrainedModelStatus

The status of the trained model.

configured_model_algorithm_association_arn: String

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

Implementations

impl TrainedModelSummary

pub fn create_time(&self) -> &DateTime

The time at which the trained model was created.

pub fn update_time(&self) -> &DateTime

The most recent time at which the trained model was updated.

pub fn trained_model_arn(&self) -> &str

The Amazon Resource Name (ARN) of the trained model.

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

The version identifier of this trained model version.

pub fn incremental_training_data_channels( &self, ) -> &[IncrementalTrainingDataChannelOutput]

Information about the incremental training data channels used to create this version of the trained model.

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

pub fn name(&self) -> &str

The name of the trained model.

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

The description of the trained model.

pub fn membership_identifier(&self) -> &str

The membership ID of the member that created the trained model.

pub fn collaboration_identifier(&self) -> &str

The collaboration ID of the collaboration that contains the trained model.

pub fn status(&self) -> &TrainedModelStatus

The status of the trained model.

pub fn configured_model_algorithm_association_arn(&self) -> &str

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

impl TrainedModelSummary

pub fn builder() -> TrainedModelSummaryBuilder

Creates a new builder-style object to manufacture TrainedModelSummary.

Trait Implementations

impl Clone for TrainedModelSummary

fn clone(&self) -> TrainedModelSummary

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TrainedModelSummary

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

Formats the value using the given formatter.

impl PartialEq for TrainedModelSummary

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

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

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 TrainedModelSummary