Struct ModelDescription 

#[non_exhaustive]
pub struct ModelDescription {

    pub model_version: Option<String>,
    pub model_arn: Option<String>,
    pub creation_timestamp: Option<DateTime>,
    pub description: Option<String>,
    pub status: Option<ModelStatus>,
    pub status_message: Option<String>,
    pub performance: Option<ModelPerformance>,
    pub output_config: Option<OutputConfig>,
    pub evaluation_manifest: Option<OutputS3Object>,
    pub evaluation_result: Option<OutputS3Object>,
    pub evaluation_end_timestamp: Option<DateTime>,
    pub kms_key_id: Option<String>,
    pub min_inference_units: Option<i32>,
    pub max_inference_units: Option<i32>,
}

Describes an Amazon Lookout for Vision model.

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.

model_version: Option<String>

The version of the model

model_arn: Option<String>

The Amazon Resource Name (ARN) of the model.

creation_timestamp: Option<DateTime>

The unix timestamp for the date and time that the model was created.

description: Option<String>

The description for the model.

status: Option<ModelStatus>

The status of the model.

status_message: Option<String>

The status message for the model.

performance: Option<ModelPerformance>

Performance metrics for the model. Created during training.

output_config: Option<OutputConfig>

The S3 location where Amazon Lookout for Vision saves model training files.

evaluation_manifest: Option<OutputS3Object>

The S3 location where Amazon Lookout for Vision saves the manifest file that was used to test the trained model and generate the performance scores.

evaluation_result: Option<OutputS3Object>

The S3 location where Amazon Lookout for Vision saves the performance metrics.

evaluation_end_timestamp: Option<DateTime>

The unix timestamp for the date and time that the evaluation ended.

kms_key_id: Option<String>

The identifer for the AWS Key Management Service (AWS KMS) key that was used to encrypt the model during training.

min_inference_units: Option<i32>

The minimum number of inference units used by the model. For more information, see StartModel

max_inference_units: Option<i32>

The maximum number of inference units Amazon Lookout for Vision uses to auto-scale the model. For more information, see StartModel.

Implementations

impl ModelDescription

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

The version of the model

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

The Amazon Resource Name (ARN) of the model.

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

The unix timestamp for the date and time that the model was created.

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

The description for the model.

pub fn status(&self) -> Option<&ModelStatus>

The status of the model.

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

The status message for the model.

pub fn performance(&self) -> Option<&ModelPerformance>

Performance metrics for the model. Created during training.

pub fn output_config(&self) -> Option<&OutputConfig>

The S3 location where Amazon Lookout for Vision saves model training files.

pub fn evaluation_manifest(&self) -> Option<&OutputS3Object>

The S3 location where Amazon Lookout for Vision saves the manifest file that was used to test the trained model and generate the performance scores.

pub fn evaluation_result(&self) -> Option<&OutputS3Object>

The S3 location where Amazon Lookout for Vision saves the performance metrics.

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

The unix timestamp for the date and time that the evaluation ended.

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

The identifer for the AWS Key Management Service (AWS KMS) key that was used to encrypt the model during training.

pub fn min_inference_units(&self) -> Option<i32>

The minimum number of inference units used by the model. For more information, see StartModel

pub fn max_inference_units(&self) -> Option<i32>

The maximum number of inference units Amazon Lookout for Vision uses to auto-scale the model. For more information, see StartModel.

impl ModelDescription

pub fn builder() -> ModelDescriptionBuilder

Creates a new builder-style object to manufacture ModelDescription.

Trait Implementations

impl Clone for ModelDescription

fn clone(&self) -> ModelDescription

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ModelDescription

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

Formats the value using the given formatter.

impl PartialEq for ModelDescription

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