Struct TrainedModelInferenceJobSummary 

#[non_exhaustive]
pub struct TrainedModelInferenceJobSummary {

    pub trained_model_inference_job_arn: String,
    pub configured_model_algorithm_association_arn: Option<String>,
    pub membership_identifier: String,
    pub trained_model_arn: String,
    pub trained_model_version_identifier: Option<String>,
    pub collaboration_identifier: String,
    pub status: TrainedModelInferenceJobStatus,
    pub output_configuration: Option<InferenceOutputConfiguration>,
    pub name: String,
    pub description: Option<String>,
    pub metrics_status: Option<MetricsStatus>,
    pub metrics_status_details: Option<String>,
    pub logs_status: Option<LogsStatus>,
    pub logs_status_details: Option<String>,
    pub create_time: DateTime,
    pub update_time: DateTime,
}

Provides information about the trained model inference job.

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_inference_job_arn: String

The Amazon Resource Name (ARN) of the trained model inference job.

configured_model_algorithm_association_arn: Option<String>

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for the trained model inference job.

membership_identifier: String

The membership ID of the membership that contains the trained model inference job.

trained_model_arn: String

The Amazon Resource Name (ARN) of the trained model that is used for the trained model inference job.

trained_model_version_identifier: Option<String>

The version identifier of the trained model that was used for inference in this job.

collaboration_identifier: String

The collaboration ID of the collaboration that contains the trained model inference job.

status: TrainedModelInferenceJobStatus

The status of the trained model inference job.

output_configuration: Option<InferenceOutputConfiguration>

The output configuration information of the trained model job.

name: String

The name of the trained model inference job.

description: Option<String>

The description of the trained model inference job.

metrics_status: Option<MetricsStatus>

The metric status of the trained model inference job.

metrics_status_details: Option<String>

Details about the metrics status for the trained model inference job.

logs_status: Option<LogsStatus>

The log status of the trained model inference job.

logs_status_details: Option<String>

Details about the log status for the trained model inference job.

create_time: DateTime

The time at which the trained model inference job was created.

update_time: DateTime

The most recent time at which the trained model inference job was updated.

Implementations

impl TrainedModelInferenceJobSummary

pub fn trained_model_inference_job_arn(&self) -> &str

The Amazon Resource Name (ARN) of the trained model inference job.

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

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for the trained model inference job.

pub fn membership_identifier(&self) -> &str

The membership ID of the membership that contains the trained model inference job.

pub fn trained_model_arn(&self) -> &str

The Amazon Resource Name (ARN) of the trained model that is used for the trained model inference job.

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

The version identifier of the trained model that was used for inference in this job.

pub fn collaboration_identifier(&self) -> &str

The collaboration ID of the collaboration that contains the trained model inference job.

pub fn status(&self) -> &TrainedModelInferenceJobStatus

The status of the trained model inference job.

pub fn output_configuration(&self) -> Option<&InferenceOutputConfiguration>

The output configuration information of the trained model job.

pub fn name(&self) -> &str

The name of the trained model inference job.

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

The description of the trained model inference job.

pub fn metrics_status(&self) -> Option<&MetricsStatus>

The metric status of the trained model inference job.

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

Details about the metrics status for the trained model inference job.

pub fn logs_status(&self) -> Option<&LogsStatus>

The log status of the trained model inference job.

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

Details about the log status for the trained model inference job.

pub fn create_time(&self) -> &DateTime

The time at which the trained model inference job was created.

pub fn update_time(&self) -> &DateTime

The most recent time at which the trained model inference job was updated.

impl TrainedModelInferenceJobSummary

pub fn builder() -> TrainedModelInferenceJobSummaryBuilder

Creates a new builder-style object to manufacture TrainedModelInferenceJobSummary.

Trait Implementations

impl Clone for TrainedModelInferenceJobSummary

fn clone(&self) -> TrainedModelInferenceJobSummary

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TrainedModelInferenceJobSummary

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

Formats the value using the given formatter.

impl PartialEq for TrainedModelInferenceJobSummary

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