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

Implementations§

The name of the model package being described.

If the model is a versioned model, the name of the model group that the versioned model belongs to.

The version of the model package.

The Amazon Resource Name (ARN) of the model package.

A brief summary of the model package.

A timestamp specifying when the model package was created.

Details about inference jobs that can be run with models based on this model package.

Details about the algorithm that was used to create the model package.

Configurations for one or more transform jobs that SageMaker runs to test the model package.

The current status of the model package.

Details about the current status of the model package.

Whether the model package is certified for listing on Amazon Web Services Marketplace.

The approval status of the model package.

Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.

Metadata properties of the tracking entity, trial, or trial component.

Metrics for the model.

The last time that the model package was modified.

Information about the user who created or modified an experiment, trial, trial component, lineage group, project, or model card.

A description provided for the model approval.

The metadata properties associated with the model package versions.

Represents the drift check baselines that can be used when the model monitor is set using the model package. For more information, see the topic on Drift Detection against Previous Baselines in SageMaker Pipelines in the Amazon SageMaker Developer Guide.

The machine learning domain of the model package you specified. Common machine learning domains include computer vision and natural language processing.

The machine learning task you specified that your model package accomplishes. Common machine learning tasks include object detection and image classification.

The Amazon Simple Storage Service (Amazon S3) path where the sample payload are stored. This path points to a single gzip compressed tar archive (.tar.gz suffix).

An array of additional Inference Specification objects. Each additional Inference Specification specifies artifacts based on this model package that can be used on inference endpoints. Generally used with SageMaker Neo to store the compiled artifacts.

Creates a new builder-style object to manufacture DescribeModelPackageOutput.

Trait Implementations§

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This method tests for self and other values to be equal, and is used by ==.
This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

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