#[non_exhaustive]pub struct HyperParameterTuningJobSearchEntity {Show 18 fields
pub hyper_parameter_tuning_job_name: Option<String>,
pub hyper_parameter_tuning_job_arn: Option<String>,
pub hyper_parameter_tuning_job_config: Option<HyperParameterTuningJobConfig>,
pub training_job_definition: Option<HyperParameterTrainingJobDefinition>,
pub training_job_definitions: Option<Vec<HyperParameterTrainingJobDefinition>>,
pub hyper_parameter_tuning_job_status: Option<HyperParameterTuningJobStatus>,
pub creation_time: Option<DateTime>,
pub hyper_parameter_tuning_end_time: Option<DateTime>,
pub last_modified_time: Option<DateTime>,
pub training_job_status_counters: Option<TrainingJobStatusCounters>,
pub objective_status_counters: Option<ObjectiveStatusCounters>,
pub best_training_job: Option<HyperParameterTrainingJobSummary>,
pub overall_best_training_job: Option<HyperParameterTrainingJobSummary>,
pub warm_start_config: Option<HyperParameterTuningJobWarmStartConfig>,
pub failure_reason: Option<String>,
pub tuning_job_completion_details: Option<HyperParameterTuningJobCompletionDetails>,
pub consumed_resources: Option<HyperParameterTuningJobConsumedResources>,
pub tags: Option<Vec<Tag>>,
}Expand description
An entity returned by the SearchRecord API containing the properties of a hyperparameter tuning job.
Fields (Non-exhaustive)§
This struct is marked as non-exhaustive
Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.hyper_parameter_tuning_job_name: Option<String>The name of a hyperparameter tuning job.
hyper_parameter_tuning_job_arn: Option<String>The Amazon Resource Name (ARN) of a hyperparameter tuning job.
hyper_parameter_tuning_job_config: Option<HyperParameterTuningJobConfig>Configures a hyperparameter tuning job.
training_job_definition: Option<HyperParameterTrainingJobDefinition>Defines the training jobs launched by a hyperparameter tuning job.
training_job_definitions: Option<Vec<HyperParameterTrainingJobDefinition>>The job definitions included in a hyperparameter tuning job.
hyper_parameter_tuning_job_status: Option<HyperParameterTuningJobStatus>The status of a hyperparameter tuning job.
creation_time: Option<DateTime>The time that a hyperparameter tuning job was created.
hyper_parameter_tuning_end_time: Option<DateTime>The time that a hyperparameter tuning job ended.
last_modified_time: Option<DateTime>The time that a hyperparameter tuning job was last modified.
training_job_status_counters: Option<TrainingJobStatusCounters>The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
objective_status_counters: Option<ObjectiveStatusCounters>Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
best_training_job: Option<HyperParameterTrainingJobSummary>The container for the summary information about a training job.
overall_best_training_job: Option<HyperParameterTrainingJobSummary>The container for the summary information about a training job.
warm_start_config: Option<HyperParameterTuningJobWarmStartConfig>Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
failure_reason: Option<String>The error that was created when a hyperparameter tuning job failed.
tuning_job_completion_details: Option<HyperParameterTuningJobCompletionDetails>Information about either a current or completed hyperparameter tuning job.
consumed_resources: Option<HyperParameterTuningJobConsumedResources>The total amount of resources consumed by a hyperparameter tuning job.
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
Implementations§
Source§impl HyperParameterTuningJobSearchEntity
impl HyperParameterTuningJobSearchEntity
Sourcepub fn hyper_parameter_tuning_job_name(&self) -> Option<&str>
pub fn hyper_parameter_tuning_job_name(&self) -> Option<&str>
The name of a hyperparameter tuning job.
Sourcepub fn hyper_parameter_tuning_job_arn(&self) -> Option<&str>
pub fn hyper_parameter_tuning_job_arn(&self) -> Option<&str>
The Amazon Resource Name (ARN) of a hyperparameter tuning job.
Sourcepub fn hyper_parameter_tuning_job_config(
&self,
) -> Option<&HyperParameterTuningJobConfig>
pub fn hyper_parameter_tuning_job_config( &self, ) -> Option<&HyperParameterTuningJobConfig>
Configures a hyperparameter tuning job.
Sourcepub fn training_job_definition(
&self,
) -> Option<&HyperParameterTrainingJobDefinition>
pub fn training_job_definition( &self, ) -> Option<&HyperParameterTrainingJobDefinition>
Defines the training jobs launched by a hyperparameter tuning job.
Sourcepub fn training_job_definitions(&self) -> &[HyperParameterTrainingJobDefinition]
pub fn training_job_definitions(&self) -> &[HyperParameterTrainingJobDefinition]
The job definitions included in a hyperparameter tuning job.
If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .training_job_definitions.is_none().
Sourcepub fn hyper_parameter_tuning_job_status(
&self,
) -> Option<&HyperParameterTuningJobStatus>
pub fn hyper_parameter_tuning_job_status( &self, ) -> Option<&HyperParameterTuningJobStatus>
The status of a hyperparameter tuning job.
Sourcepub fn creation_time(&self) -> Option<&DateTime>
pub fn creation_time(&self) -> Option<&DateTime>
The time that a hyperparameter tuning job was created.
Sourcepub fn hyper_parameter_tuning_end_time(&self) -> Option<&DateTime>
pub fn hyper_parameter_tuning_end_time(&self) -> Option<&DateTime>
The time that a hyperparameter tuning job ended.
Sourcepub fn last_modified_time(&self) -> Option<&DateTime>
pub fn last_modified_time(&self) -> Option<&DateTime>
The time that a hyperparameter tuning job was last modified.
Sourcepub fn training_job_status_counters(&self) -> Option<&TrainingJobStatusCounters>
pub fn training_job_status_counters(&self) -> Option<&TrainingJobStatusCounters>
The numbers of training jobs launched by a hyperparameter tuning job, categorized by status.
Sourcepub fn objective_status_counters(&self) -> Option<&ObjectiveStatusCounters>
pub fn objective_status_counters(&self) -> Option<&ObjectiveStatusCounters>
Specifies the number of training jobs that this hyperparameter tuning job launched, categorized by the status of their objective metric. The objective metric status shows whether the final objective metric for the training job has been evaluated by the tuning job and used in the hyperparameter tuning process.
Sourcepub fn best_training_job(&self) -> Option<&HyperParameterTrainingJobSummary>
pub fn best_training_job(&self) -> Option<&HyperParameterTrainingJobSummary>
The container for the summary information about a training job.
Sourcepub fn overall_best_training_job(
&self,
) -> Option<&HyperParameterTrainingJobSummary>
pub fn overall_best_training_job( &self, ) -> Option<&HyperParameterTrainingJobSummary>
The container for the summary information about a training job.
Sourcepub fn warm_start_config(
&self,
) -> Option<&HyperParameterTuningJobWarmStartConfig>
pub fn warm_start_config( &self, ) -> Option<&HyperParameterTuningJobWarmStartConfig>
Specifies the configuration for a hyperparameter tuning job that uses one or more previous hyperparameter tuning jobs as a starting point. The results of previous tuning jobs are used to inform which combinations of hyperparameters to search over in the new tuning job.
All training jobs launched by the new hyperparameter tuning job are evaluated by using the objective metric, and the training job that performs the best is compared to the best training jobs from the parent tuning jobs. From these, the training job that performs the best as measured by the objective metric is returned as the overall best training job.
All training jobs launched by parent hyperparameter tuning jobs and the new hyperparameter tuning jobs count against the limit of training jobs for the tuning job.
Sourcepub fn failure_reason(&self) -> Option<&str>
pub fn failure_reason(&self) -> Option<&str>
The error that was created when a hyperparameter tuning job failed.
Sourcepub fn tuning_job_completion_details(
&self,
) -> Option<&HyperParameterTuningJobCompletionDetails>
pub fn tuning_job_completion_details( &self, ) -> Option<&HyperParameterTuningJobCompletionDetails>
Information about either a current or completed hyperparameter tuning job.
Sourcepub fn consumed_resources(
&self,
) -> Option<&HyperParameterTuningJobConsumedResources>
pub fn consumed_resources( &self, ) -> Option<&HyperParameterTuningJobConsumedResources>
The total amount of resources consumed by a hyperparameter tuning job.
The tags associated with a hyperparameter tuning job. For more information see Tagging Amazon Web Services resources.
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().
Source§impl HyperParameterTuningJobSearchEntity
impl HyperParameterTuningJobSearchEntity
Sourcepub fn builder() -> HyperParameterTuningJobSearchEntityBuilder
pub fn builder() -> HyperParameterTuningJobSearchEntityBuilder
Creates a new builder-style object to manufacture HyperParameterTuningJobSearchEntity.
Trait Implementations§
Source§impl Clone for HyperParameterTuningJobSearchEntity
impl Clone for HyperParameterTuningJobSearchEntity
Source§fn clone(&self) -> HyperParameterTuningJobSearchEntity
fn clone(&self) -> HyperParameterTuningJobSearchEntity
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source. Read moreSource§impl PartialEq for HyperParameterTuningJobSearchEntity
impl PartialEq for HyperParameterTuningJobSearchEntity
Source§fn eq(&self, other: &HyperParameterTuningJobSearchEntity) -> bool
fn eq(&self, other: &HyperParameterTuningJobSearchEntity) -> bool
self and other values to be equal, and is used by ==.impl StructuralPartialEq for HyperParameterTuningJobSearchEntity
Auto Trait Implementations§
impl Freeze for HyperParameterTuningJobSearchEntity
impl RefUnwindSafe for HyperParameterTuningJobSearchEntity
impl Send for HyperParameterTuningJobSearchEntity
impl Sync for HyperParameterTuningJobSearchEntity
impl Unpin for HyperParameterTuningJobSearchEntity
impl UnwindSafe for HyperParameterTuningJobSearchEntity
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