Struct IncrementalTrainingDataChannel 

#[non_exhaustive]
pub struct IncrementalTrainingDataChannel {
    pub trained_model_arn: String,
    pub version_identifier: Option<String>,
    pub channel_name: String,
}

Defines an incremental training data channel that references a previously trained model. Incremental training allows you to update an existing trained model with new data, building upon the knowledge from a base model rather than training from scratch. This can significantly reduce training time and computational costs while improving model performance with additional data.

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.

trained_model_arn: String

The Amazon Resource Name (ARN) of the base trained model to use for incremental training. This model serves as the starting point for the incremental training process.

version_identifier: Option<String>

The version identifier of the base trained model to use for incremental training. If not specified, the latest version of the trained model is used.

channel_name: String

The name of the incremental training data channel. This name is used to identify the channel during the training process and must be unique within the training job.

Implementations

impl IncrementalTrainingDataChannel

pub fn trained_model_arn(&self) -> &str

The Amazon Resource Name (ARN) of the base trained model to use for incremental training. This model serves as the starting point for the incremental training process.

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

The version identifier of the base trained model to use for incremental training. If not specified, the latest version of the trained model is used.

pub fn channel_name(&self) -> &str

The name of the incremental training data channel. This name is used to identify the channel during the training process and must be unique within the training job.

impl IncrementalTrainingDataChannel

pub fn builder() -> IncrementalTrainingDataChannelBuilder

Creates a new builder-style object to manufacture IncrementalTrainingDataChannel.

Trait Implementations

impl Clone for IncrementalTrainingDataChannel

fn clone(&self) -> IncrementalTrainingDataChannel

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for IncrementalTrainingDataChannel

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

Formats the value using the given formatter.

impl PartialEq for IncrementalTrainingDataChannel

fn eq(&self, other: &IncrementalTrainingDataChannel) -> 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 IncrementalTrainingDataChannel