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pub struct ProductionVariant {
    pub accelerator_type: Option<String>,
    pub core_dump_config: Option<ProductionVariantCoreDumpConfig>,
    pub initial_instance_count: i64,
    pub initial_variant_weight: Option<f32>,
    pub instance_type: String,
    pub model_name: String,
    pub variant_name: String,
}
Expand description

Identifies a model that you want to host and the resources chosen to deploy for hosting it. If you are deploying multiple models, tell Amazon SageMaker how to distribute traffic among the models by specifying variant weights.

Fields

accelerator_type: Option<String>

The size of the Elastic Inference (EI) instance to use for the production variant. EI instances provide on-demand GPU computing for inference. For more information, see Using Elastic Inference in Amazon SageMaker.

core_dump_config: Option<ProductionVariantCoreDumpConfig>

Specifies configuration for a core dump from the model container when the process crashes.

initial_instance_count: i64

Number of instances to launch initially.

initial_variant_weight: Option<f32>

Determines initial traffic distribution among all of the models that you specify in the endpoint configuration. The traffic to a production variant is determined by the ratio of the VariantWeight to the sum of all VariantWeight values across all ProductionVariants. If unspecified, it defaults to 1.0.

instance_type: String

The ML compute instance type.

model_name: String

The name of the model that you want to host. This is the name that you specified when creating the model.

variant_name: String

The name of the production variant.

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