You are viewing documentation for version 2 of the AWS SDK for Ruby. Version 3 documentation can be found here.
Class: Aws::SageMaker::Types::InferenceSpecification
- Inherits:
-
Struct
- Object
- Struct
- Aws::SageMaker::Types::InferenceSpecification
- Defined in:
- (unknown)
Overview
When passing InferenceSpecification as input to an Aws::Client method, you can use a vanilla Hash:
{
containers: [ # required
{
container_hostname: "ContainerHostname",
image: "ContainerImage", # required
image_digest: "ImageDigest",
model_data_url: "Url",
product_id: "ProductId",
},
],
supported_transform_instance_types: ["ml.m4.xlarge"], # required, accepts ml.m4.xlarge, ml.m4.2xlarge, ml.m4.4xlarge, ml.m4.10xlarge, ml.m4.16xlarge, 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.xlarge, ml.c5.2xlarge, ml.c5.4xlarge, ml.c5.9xlarge, ml.c5.18xlarge, ml.m5.large, ml.m5.xlarge, ml.m5.2xlarge, ml.m5.4xlarge, ml.m5.12xlarge, ml.m5.24xlarge
supported_realtime_inference_instance_types: ["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
supported_content_types: ["ContentType"], # required
supported_response_mime_types: ["ResponseMIMEType"], # required
}
Defines how to perform inference generation after a training job is run.
Returned by:
Instance Attribute Summary collapse
-
#containers ⇒ Array<Types::ModelPackageContainerDefinition>
The Amazon ECR registry path of the Docker image that contains the inference code.
-
#supported_content_types ⇒ Array<String>
The supported MIME types for the input data.
-
#supported_realtime_inference_instance_types ⇒ Array<String>
A list of the instance types that are used to generate inferences in real-time.
-
#supported_response_mime_types ⇒ Array<String>
The supported MIME types for the output data.
-
#supported_transform_instance_types ⇒ Array<String>
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.
Instance Attribute Details
#containers ⇒ Array<Types::ModelPackageContainerDefinition>
The Amazon ECR registry path of the Docker image that contains the inference code.
#supported_content_types ⇒ Array<String>
The supported MIME types for the input data.
#supported_realtime_inference_instance_types ⇒ Array<String>
A list of the instance types that are used to generate inferences in real-time.
#supported_response_mime_types ⇒ Array<String>
The supported MIME types for the output data.
#supported_transform_instance_types ⇒ Array<String>
A list of the instance types on which a transformation job can be run or on which an endpoint can be deployed.