pub struct HyperParameterTrainingJobSummary {
pub creation_time: f64,
pub failure_reason: Option<String>,
pub final_hyper_parameter_tuning_job_objective_metric: Option<FinalHyperParameterTuningJobObjectiveMetric>,
pub objective_status: Option<String>,
pub training_end_time: Option<f64>,
pub training_job_arn: String,
pub training_job_definition_name: Option<String>,
pub training_job_name: String,
pub training_job_status: String,
pub training_start_time: Option<f64>,
pub tuned_hyper_parameters: HashMap<String, String>,
pub tuning_job_name: Option<String>,
}
Expand description
Specifies summary information about a training job.
Fields
creation_time: f64
The date and time that the training job was created.
failure_reason: Option<String>
The reason that the training job failed.
final_hyper_parameter_tuning_job_objective_metric: Option<FinalHyperParameterTuningJobObjectiveMetric>
The FinalHyperParameterTuningJobObjectiveMetric object that specifies the value of the objective metric of the tuning job that launched this training job.
objective_status: Option<String>
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.
training_end_time: Option<f64>
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 Amazon SageMaker detects a job failure.
training_job_arn: String
The Amazon Resource Name (ARN) of the training job.
training_job_definition_name: Option<String>
The training job definition name.
training_job_name: String
The name of the training job.
training_job_status: String
The status of the training job.
training_start_time: Option<f64>
The date and time that the training job started.
tuned_hyper_parameters: HashMap<String, String>
A list of the hyperparameters for which you specified ranges to search.
tuning_job_name: Option<String>
The HyperParameter tuning job that launched the training job.
Trait Implementations
sourceimpl Clone for HyperParameterTrainingJobSummary
impl Clone for HyperParameterTrainingJobSummary
sourcefn clone(&self) -> HyperParameterTrainingJobSummary
fn clone(&self) -> HyperParameterTrainingJobSummary
Returns a copy of the value. Read more
1.0.0 · sourcefn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from source
. Read more
sourceimpl Default for HyperParameterTrainingJobSummary
impl Default for HyperParameterTrainingJobSummary
sourcefn default() -> HyperParameterTrainingJobSummary
fn default() -> HyperParameterTrainingJobSummary
Returns the “default value” for a type. Read more
sourceimpl<'de> Deserialize<'de> for HyperParameterTrainingJobSummary
impl<'de> Deserialize<'de> for HyperParameterTrainingJobSummary
sourcefn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
__D: Deserializer<'de>,
Deserialize this value from the given Serde deserializer. Read more
sourceimpl PartialEq<HyperParameterTrainingJobSummary> for HyperParameterTrainingJobSummary
impl PartialEq<HyperParameterTrainingJobSummary> for HyperParameterTrainingJobSummary
sourcefn eq(&self, other: &HyperParameterTrainingJobSummary) -> bool
fn eq(&self, other: &HyperParameterTrainingJobSummary) -> bool
This method tests for self
and other
values to be equal, and is used
by ==
. Read more
sourcefn ne(&self, other: &HyperParameterTrainingJobSummary) -> bool
fn ne(&self, other: &HyperParameterTrainingJobSummary) -> bool
This method tests for !=
.
impl StructuralPartialEq for HyperParameterTrainingJobSummary
Auto Trait Implementations
impl RefUnwindSafe for HyperParameterTrainingJobSummary
impl Send for HyperParameterTrainingJobSummary
impl Sync for HyperParameterTrainingJobSummary
impl Unpin for HyperParameterTrainingJobSummary
impl UnwindSafe for HyperParameterTrainingJobSummary
Blanket Implementations
sourceimpl<T> BorrowMut<T> for T where
T: ?Sized,
impl<T> BorrowMut<T> for T where
T: ?Sized,
const: unstable · sourcefn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
sourceimpl<T> Instrument for T
impl<T> Instrument for T
sourcefn instrument(self, span: Span) -> Instrumented<Self>
fn instrument(self, span: Span) -> Instrumented<Self>
sourcefn in_current_span(self) -> Instrumented<Self>
fn in_current_span(self) -> Instrumented<Self>
sourceimpl<T> ToOwned for T where
T: Clone,
impl<T> ToOwned for T where
T: Clone,
type Owned = T
type Owned = T
The resulting type after obtaining ownership.
sourcefn clone_into(&self, target: &mut T)
fn clone_into(&self, target: &mut T)
toowned_clone_into
)Uses borrowed data to replace owned data, usually by cloning. Read more
sourceimpl<T> WithSubscriber for T
impl<T> WithSubscriber for T
sourcefn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
fn with_subscriber<S>(self, subscriber: S) -> WithDispatch<Self> where
S: Into<Dispatch>,
Attaches the provided Subscriber
to this type, returning a
WithDispatch
wrapper. Read more
sourcefn with_current_subscriber(self) -> WithDispatch<Self>
fn with_current_subscriber(self) -> WithDispatch<Self>
Attaches the current default Subscriber
to this type, returning a
WithDispatch
wrapper. Read more