Struct aws_sdk_sagemaker::types::RecommendationJobContainerConfig

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

Specifies mandatory fields for running an Inference Recommender job directly in the CreateInferenceRecommendationsJob API. The fields specified in ContainerConfig override the corresponding fields in the model package. Use ContainerConfig if you want to specify these fields for the recommendation job but don't want to edit them in your model package.

Implementations

impl RecommendationJobContainerConfig

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

The machine learning domain of the model and its components.

Valid Values: COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING

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

The machine learning task that the model accomplishes.

Valid Values: IMAGE_CLASSIFICATION | OBJECT_DETECTION | TEXT_GENERATION | IMAGE_SEGMENTATION | FILL_MASK | CLASSIFICATION | REGRESSION | OTHER

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

The machine learning framework of the container image.

Valid Values: TENSORFLOW | PYTORCH | XGBOOST | SAGEMAKER-SCIKIT-LEARN

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

The framework version of the container image.

pub fn payload_config(&self) -> Option<&RecommendationJobPayloadConfig>

Specifies the SamplePayloadUrl and all other sample payload-related fields.

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

The name of a pre-trained machine learning model benchmarked by Amazon SageMaker Inference Recommender that matches your model.

Valid Values: efficientnetb7 | unet | xgboost | faster-rcnn-resnet101 | nasnetlarge | vgg16 | inception-v3 | mask-rcnn | sagemaker-scikit-learn | densenet201-gluon | resnet18v2-gluon | xception | densenet201 | yolov4 | resnet152 | bert-base-cased | xceptionV1-keras | resnet50 | retinanet

pub fn supported_instance_types(&self) -> Option<&[String]>

A list of the instance types that are used to generate inferences in real-time.

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

Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form. This field is used for optimizing your model using SageMaker Neo. For more information, see DataInputConfig.

impl RecommendationJobContainerConfig

pub fn builder() -> RecommendationJobContainerConfigBuilder

Creates a new builder-style object to manufacture RecommendationJobContainerConfig.

Trait Implementations

impl Clone for RecommendationJobContainerConfig

fn clone(&self) -> RecommendationJobContainerConfig

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for RecommendationJobContainerConfig

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

Formats the value using the given formatter.

impl PartialEq<RecommendationJobContainerConfig> for RecommendationJobContainerConfig

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

This method tests for self and other values to be equal, and is used by ==.

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

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

impl StructuralPartialEq for RecommendationJobContainerConfig