Struct HyperParameterTrainingJobSummaryBuilder

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#[non_exhaustive]
pub struct HyperParameterTrainingJobSummaryBuilder { /* private fields */ }

Expand description

A builder for HyperParameterTrainingJobSummary.

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impl HyperParameterTrainingJobSummaryBuilder

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pub fn training_job_definition_name(self, input: impl Into<String>) -> Self

The training job definition name.

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pub fn set_training_job_definition_name(self, input: Option<String>) -> Self

The training job definition name.

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pub fn get_training_job_definition_name(&self) -> &Option<String>

The training job definition name.

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pub fn training_job_name(self, input: impl Into<String>) -> Self

The name of the training job.

This field is required.

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pub fn set_training_job_name(self, input: Option<String>) -> Self

The name of the training job.

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pub fn get_training_job_name(&self) -> &Option<String>

The name of the training job.

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pub fn training_job_arn(self, input: impl Into<String>) -> Self

The Amazon Resource Name (ARN) of the training job.

This field is required.

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pub fn set_training_job_arn(self, input: Option<String>) -> Self

The Amazon Resource Name (ARN) of the training job.

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pub fn get_training_job_arn(&self) -> &Option<String>

The Amazon Resource Name (ARN) of the training job.

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pub fn tuning_job_name(self, input: impl Into<String>) -> Self

The HyperParameter tuning job that launched the training job.

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pub fn set_tuning_job_name(self, input: Option<String>) -> Self

The HyperParameter tuning job that launched the training job.

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pub fn get_tuning_job_name(&self) -> &Option<String>

The HyperParameter tuning job that launched the training job.

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pub fn creation_time(self, input: DateTime) -> Self

The date and time that the training job was created.

This field is required.

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pub fn set_creation_time(self, input: Option<DateTime>) -> Self

The date and time that the training job was created.

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pub fn get_creation_time(&self) -> &Option<DateTime>

The date and time that the training job was created.

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pub fn training_start_time(self, input: DateTime) -> Self

The date and time that the training job started.

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pub fn set_training_start_time(self, input: Option<DateTime>) -> Self

The date and time that the training job started.

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pub fn get_training_start_time(&self) -> &Option<DateTime>

The date and time that the training job started.

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pub fn training_end_time(self, input: DateTime) -> Self

Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.

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pub fn set_training_end_time(self, input: Option<DateTime>) -> Self

Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.

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pub fn get_training_end_time(&self) -> &Option<DateTime>

Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.

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pub fn training_job_status(self, input: TrainingJobStatus) -> Self

The status of the training job.

This field is required.

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pub fn set_training_job_status(self, input: Option<TrainingJobStatus>) -> Self

The status of the training job.

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pub fn get_training_job_status(&self) -> &Option<TrainingJobStatus>

The status of the training job.

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pub fn tuned_hyper_parameters( self, k: impl Into<String>, v: impl Into<String>, ) -> Self

Adds a key-value pair to tuned_hyper_parameters.

To override the contents of this collection use set_tuned_hyper_parameters.

A list of the hyperparameters for which you specified ranges to search.

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pub fn set_tuned_hyper_parameters( self, input: Option<HashMap<String, String>>, ) -> Self

A list of the hyperparameters for which you specified ranges to search.

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pub fn get_tuned_hyper_parameters(&self) -> &Option<HashMap<String, String>>

A list of the hyperparameters for which you specified ranges to search.

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pub fn failure_reason(self, input: impl Into<String>) -> Self

The reason that the training job failed.

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pub fn set_failure_reason(self, input: Option<String>) -> Self

The reason that the training job failed.

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pub fn get_failure_reason(&self) -> &Option<String>

The reason that the training job failed.

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pub fn final_hyper_parameter_tuning_job_objective_metric( self, input: FinalHyperParameterTuningJobObjectiveMetric, ) -> Self

The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.

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pub fn set_final_hyper_parameter_tuning_job_objective_metric( self, input: Option<FinalHyperParameterTuningJobObjectiveMetric>, ) -> Self

The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.

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pub fn get_final_hyper_parameter_tuning_job_objective_metric( &self, ) -> &Option<FinalHyperParameterTuningJobObjectiveMetric>

The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.

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pub fn objective_status(self, input: ObjectiveStatus) -> Self

The status of the objective metric for the training job:

Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.

Pending: The training job is in progress and evaluation of its final objective metric is pending.

Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.

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pub fn set_objective_status(self, input: Option<ObjectiveStatus>) -> Self

The status of the objective metric for the training job:

Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.

Pending: The training job is in progress and evaluation of its final objective metric is pending.

Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.

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pub fn get_objective_status(&self) -> &Option<ObjectiveStatus>

The status of the objective metric for the training job:

Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.

Pending: The training job is in progress and evaluation of its final objective metric is pending.

Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.

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pub fn build(self) -> HyperParameterTrainingJobSummary

Consumes the builder and constructs a HyperParameterTrainingJobSummary.

Trait Implementations§

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impl Clone for HyperParameterTrainingJobSummaryBuilder

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fn clone(&self) -> HyperParameterTrainingJobSummaryBuilder

Returns a duplicate of the value. Read more

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

Performs copy-assignment from source. Read more

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impl Debug for HyperParameterTrainingJobSummaryBuilder

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

Formats the value using the given formatter. Read more

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impl Default for HyperParameterTrainingJobSummaryBuilder

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fn default() -> HyperParameterTrainingJobSummaryBuilder

Returns the “default value” for a type. Read more

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impl PartialEq for HyperParameterTrainingJobSummaryBuilder

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

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

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

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

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impl StructuralPartialEq for HyperParameterTrainingJobSummaryBuilder

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impl UnwindSafe for HyperParameterTrainingJobSummaryBuilder

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Struct HyperParameterTrainingJobSummaryBuilderCopy item path

Implementations§

impl HyperParameterTrainingJobSummaryBuilder

pub fn training_job_definition_name(self, input: impl Into<String>) -> Self

pub fn set_training_job_definition_name(self, input: Option<String>) -> Self

pub fn get_training_job_definition_name(&self) -> &Option<String>

pub fn training_job_name(self, input: impl Into<String>) -> Self

pub fn set_training_job_name(self, input: Option<String>) -> Self

pub fn get_training_job_name(&self) -> &Option<String>

pub fn training_job_arn(self, input: impl Into<String>) -> Self

pub fn set_training_job_arn(self, input: Option<String>) -> Self

pub fn get_training_job_arn(&self) -> &Option<String>

pub fn tuning_job_name(self, input: impl Into<String>) -> Self

pub fn set_tuning_job_name(self, input: Option<String>) -> Self

pub fn get_tuning_job_name(&self) -> &Option<String>

pub fn creation_time(self, input: DateTime) -> Self

pub fn set_creation_time(self, input: Option<DateTime>) -> Self

pub fn get_creation_time(&self) -> &Option<DateTime>

pub fn training_start_time(self, input: DateTime) -> Self

pub fn set_training_start_time(self, input: Option<DateTime>) -> Self

pub fn get_training_start_time(&self) -> &Option<DateTime>

pub fn training_end_time(self, input: DateTime) -> Self

pub fn set_training_end_time(self, input: Option<DateTime>) -> Self

pub fn get_training_end_time(&self) -> &Option<DateTime>

pub fn training_job_status(self, input: TrainingJobStatus) -> Self

pub fn set_training_job_status(self, input: Option<TrainingJobStatus>) -> Self

pub fn get_training_job_status(&self) -> &Option<TrainingJobStatus>

pub fn tuned_hyper_parameters( self, k: impl Into<String>, v: impl Into<String>, ) -> Self

pub fn set_tuned_hyper_parameters( self, input: Option<HashMap<String, String>>, ) -> Self

pub fn get_tuned_hyper_parameters(&self) -> &Option<HashMap<String, String>>

pub fn failure_reason(self, input: impl Into<String>) -> Self

pub fn set_failure_reason(self, input: Option<String>) -> Self

pub fn get_failure_reason(&self) -> &Option<String>

pub fn final_hyper_parameter_tuning_job_objective_metric( self, input: FinalHyperParameterTuningJobObjectiveMetric, ) -> Self

pub fn set_final_hyper_parameter_tuning_job_objective_metric( self, input: Option<FinalHyperParameterTuningJobObjectiveMetric>, ) -> Self

pub fn get_final_hyper_parameter_tuning_job_objective_metric( &self, ) -> &Option<FinalHyperParameterTuningJobObjectiveMetric>

pub fn objective_status(self, input: ObjectiveStatus) -> Self

pub fn set_objective_status(self, input: Option<ObjectiveStatus>) -> Self

pub fn get_objective_status(&self) -> &Option<ObjectiveStatus>

pub fn build(self) -> HyperParameterTrainingJobSummary

Trait Implementations§

impl Clone for HyperParameterTrainingJobSummaryBuilder

fn clone(&self) -> HyperParameterTrainingJobSummaryBuilder

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

impl Debug for HyperParameterTrainingJobSummaryBuilder

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

impl Default for HyperParameterTrainingJobSummaryBuilder

fn default() -> HyperParameterTrainingJobSummaryBuilder

impl PartialEq for HyperParameterTrainingJobSummaryBuilder

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

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

impl StructuralPartialEq for HyperParameterTrainingJobSummaryBuilder

Auto Trait Implementations§

impl Freeze for HyperParameterTrainingJobSummaryBuilder

impl RefUnwindSafe for HyperParameterTrainingJobSummaryBuilder

impl Send for HyperParameterTrainingJobSummaryBuilder

impl Sync for HyperParameterTrainingJobSummaryBuilder

impl Unpin for HyperParameterTrainingJobSummaryBuilder

impl UnwindSafe for HyperParameterTrainingJobSummaryBuilder

Blanket Implementations§

impl<T> Any for Twhere T: 'static + ?Sized,

fn type_id(&self) -> TypeId

impl<T> Borrow<T> for Twhere T: ?Sized,

fn borrow(&self) -> &T

impl<T> BorrowMut<T> for Twhere T: ?Sized,

fn borrow_mut(&mut self) -> &mut T

impl<T> CloneToUninit for Twhere T: Clone,

unsafe fn clone_to_uninit(&self, dest: *mut u8)

impl<T> From<T> for T

fn from(t: T) -> T

impl<T> Instrument for T

fn instrument(self, span: Span) -> Instrumented<Self>

fn in_current_span(self) -> Instrumented<Self>

impl<T, U> Into<U> for Twhere U: From<T>,

fn into(self) -> U

impl<T> IntoEither for T

fn into_either(self, into_left: bool) -> Either<Self, Self>

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unsharedwhere Shared: FromUnshared<Unshared>,

fn into_shared(self) -> Shared

Struct HyperParameterTrainingJobSummaryBuilder

impl<T> Any for T
where T: 'static + ?Sized,

impl<T> Borrow<T> for T
where T: ?Sized,

impl<T> BorrowMut<T> for T
where T: ?Sized,

impl<T> CloneToUninit for T
where T: Clone,

impl<T, U> Into<U> for T
where U: From<T>,

fn into_either_with<F>(self, into_left: F) -> Either<Self, Self>
where F: FnOnce(&Self) -> bool,

impl<Unshared, Shared> IntoShared<Shared> for Unshared
where Shared: FromUnshared<Unshared>,

impl<T> Paint for T
where T: ?Sized,