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Class: Aws::SageMaker::Types::ProductionVariant
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::ProductionVariant
- Defined in:
- (unknown)
Overview
When passing ProductionVariant as input to an Aws::Client method, you can use a vanilla Hash:
{
variant_name: "VariantName", # required
model_name: "ModelName", # required
initial_instance_count: 1, # required
instance_type: "ml.t2.medium", # required, accepts ml.t2.medium, ml.t2.large, ml.t2.xlarge, ml.t2.2xlarge, ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge, ml.m5d.large, ml.m5d.xlarge, ml.m5d.2xlarge, ml.m5d.4xlarge, ml.m5d.12xlarge, ml.m5d.24xlarge, ml.c4.large, ml.c4.xlarge, ml.c4.2xlarge, ml.c4.4xlarge, ml.c4.8xlarge, ml.p2.xlarge, ml.p2.8xlarge, ml.p2.16xlarge, ml.p3.2xlarge, ml.p3.8xlarge, ml.p3.16xlarge, ml.c5.large, ml.c5.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.c5d.large, ml.c5d.xlarge, ml.c5d.2xlarge, ml.c5d.4xlarge, ml.c5d.9xlarge, ml.c5d.18xlarge, ml.g4dn.xlarge, ml.g4dn.2xlarge, ml.g4dn.4xlarge, ml.g4dn.8xlarge, ml.g4dn.12xlarge, ml.g4dn.16xlarge, ml.r5.large, ml.r5.xlarge, ml.r5.2xlarge, ml.r5.4xlarge, ml.r5.12xlarge, ml.r5.24xlarge, ml.r5d.large, ml.r5d.xlarge, ml.r5d.2xlarge, ml.r5d.4xlarge, ml.r5d.12xlarge, ml.r5d.24xlarge, ml.inf1.xlarge, ml.inf1.2xlarge, ml.inf1.6xlarge, ml.inf1.24xlarge
initial_variant_weight: 1.0,
accelerator_type: "ml.eia1.medium", # accepts ml.eia1.medium, ml.eia1.large, ml.eia1.xlarge, ml.eia2.medium, ml.eia2.large, ml.eia2.xlarge
}
Identifies a model that you want to host and the resources 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.
Instance Attribute Summary collapse
-
#accelerator_type ⇒ String
The size of the Elastic Inference (EI) instance to use for the production variant.
-
#initial_instance_count ⇒ Integer
Number of instances to launch initially.
-
#initial_variant_weight ⇒ Float
Determines initial traffic distribution among all of the models that you specify in the endpoint configuration.
-
#instance_type ⇒ String
The ML compute instance type.
-
#model_name ⇒ String
The name of the model that you want to host.
-
#variant_name ⇒ String
The name of the production variant.
Instance Attribute Details
#accelerator_type ⇒ 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.
#initial_instance_count ⇒ Integer
Number of instances to launch initially.
#initial_variant_weight ⇒ Float
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.
Possible values:
- ml.t2.medium
- ml.t2.large
- ml.t2.xlarge
- ml.t2.2xlarge
- ml.m4.xlarge
- ml.m4.2xlarge
- ml.m4.4xlarge
- ml.m4.10xlarge
- ml.m4.16xlarge
- ml.m5.large
- ml.m5.xlarge
- ml.m5.2xlarge
- ml.m5.4xlarge
- ml.m5.12xlarge
- ml.m5.24xlarge
- ml.m5d.large
- ml.m5d.xlarge
- ml.m5d.2xlarge
- ml.m5d.4xlarge
- ml.m5d.12xlarge
- ml.m5d.24xlarge
- ml.c4.large
- ml.c4.xlarge
- ml.c4.2xlarge
- ml.c4.4xlarge
- ml.c4.8xlarge
- ml.p2.xlarge
- ml.p2.8xlarge
- ml.p2.16xlarge
- ml.p3.2xlarge
- ml.p3.8xlarge
- ml.p3.16xlarge
- ml.c5.large
- ml.c5.xlarge
- ml.c5.2xlarge
- ml.c5.4xlarge
- ml.c5.9xlarge
- ml.c5.18xlarge
- ml.c5d.large
- ml.c5d.xlarge
- ml.c5d.2xlarge
- ml.c5d.4xlarge
- ml.c5d.9xlarge
- ml.c5d.18xlarge
- ml.g4dn.xlarge
- ml.g4dn.2xlarge
- ml.g4dn.4xlarge
- ml.g4dn.8xlarge
- ml.g4dn.12xlarge
- ml.g4dn.16xlarge
- ml.r5.large
- ml.r5.xlarge
- ml.r5.2xlarge
- ml.r5.4xlarge
- ml.r5.12xlarge
- ml.r5.24xlarge
- ml.r5d.large
- ml.r5d.xlarge
- ml.r5d.2xlarge
- ml.r5d.4xlarge
- ml.r5d.12xlarge
- ml.r5d.24xlarge
- ml.inf1.xlarge
- ml.inf1.2xlarge
- ml.inf1.6xlarge
- ml.inf1.24xlarge
#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.