Struct aws_sdk_sagemaker::types::TrainingSpecification
source · #[non_exhaustive]pub struct TrainingSpecification { /* private fields */ }
Expand description
Defines how the algorithm is used for a training job.
Implementations§
source§impl TrainingSpecification
impl TrainingSpecification
sourcepub fn training_image(&self) -> Option<&str>
pub fn training_image(&self) -> Option<&str>
The Amazon ECR registry path of the Docker image that contains the training algorithm.
sourcepub fn training_image_digest(&self) -> Option<&str>
pub fn training_image_digest(&self) -> Option<&str>
An MD5 hash of the training algorithm that identifies the Docker image used for training.
sourcepub fn supported_hyper_parameters(
&self
) -> Option<&[HyperParameterSpecification]>
pub fn supported_hyper_parameters( &self ) -> Option<&[HyperParameterSpecification]>
A list of the HyperParameterSpecification
objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>
sourcepub fn supported_training_instance_types(
&self
) -> Option<&[TrainingInstanceType]>
pub fn supported_training_instance_types( &self ) -> Option<&[TrainingInstanceType]>
A list of the instance types that this algorithm can use for training.
sourcepub fn supports_distributed_training(&self) -> bool
pub fn supports_distributed_training(&self) -> bool
Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.
sourcepub fn metric_definitions(&self) -> Option<&[MetricDefinition]>
pub fn metric_definitions(&self) -> Option<&[MetricDefinition]>
A list of MetricDefinition
objects, which are used for parsing metrics generated by the algorithm.
sourcepub fn training_channels(&self) -> Option<&[ChannelSpecification]>
pub fn training_channels(&self) -> Option<&[ChannelSpecification]>
A list of ChannelSpecification
objects, which specify the input sources to be used by the algorithm.
sourcepub fn supported_tuning_job_objective_metrics(
&self
) -> Option<&[HyperParameterTuningJobObjective]>
pub fn supported_tuning_job_objective_metrics( &self ) -> Option<&[HyperParameterTuningJobObjective]>
A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.
source§impl TrainingSpecification
impl TrainingSpecification
sourcepub fn builder() -> TrainingSpecificationBuilder
pub fn builder() -> TrainingSpecificationBuilder
Creates a new builder-style object to manufacture TrainingSpecification
.
Trait Implementations§
source§impl Clone for TrainingSpecification
impl Clone for TrainingSpecification
source§fn clone(&self) -> TrainingSpecification
fn clone(&self) -> TrainingSpecification
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresource§impl Debug for TrainingSpecification
impl Debug for TrainingSpecification
source§impl PartialEq<TrainingSpecification> for TrainingSpecification
impl PartialEq<TrainingSpecification> for TrainingSpecification
source§fn eq(&self, other: &TrainingSpecification) -> bool
fn eq(&self, other: &TrainingSpecification) -> bool
self
and other
values to be equal, and is used
by ==
.