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Class: Aws::SageMaker::Types::ContainerDefinition

Inherits:
Struct
  • Object
show all
Defined in:
gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb

Overview

Note:

When making an API call, you may pass ContainerDefinition data as a hash:

{
  container_hostname: "ContainerHostname",
  image: "Image", # required
  model_data_url: "Url",
  environment: {
    "EnvironmentKey" => "EnvironmentValue",
  },
}

Describes the container, as part of model definition.

Instance Attribute Summary collapse

Instance Attribute Details

#container_hostnameString

The DNS host name for the container after Amazon SageMaker deploys it.

Returns:

  • (String)


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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 266

class ContainerDefinition < Struct.new(
  :container_hostname,
  :image,
  :model_data_url,
  :environment)
  include Aws::Structure
end

#environmentHash<String,String>

The environment variables to set in the Docker container. Each key and value in the Environment string to string map can have length of up to 1024. We support up to 16 entries in the map.

Returns:

  • (Hash<String,String>)


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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 266

class ContainerDefinition < Struct.new(
  :container_hostname,
  :image,
  :model_data_url,
  :environment)
  include Aws::Structure
end

#imageString

The Amazon EC2 Container Registry (Amazon ECR) path where inference code is stored. If you are using your own custom algorithm instead of an algorithm provided by Amazon SageMaker, the inference code must meet Amazon SageMaker requirements. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker

Returns:

  • (String)


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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 266

class ContainerDefinition < Struct.new(
  :container_hostname,
  :image,
  :model_data_url,
  :environment)
  include Aws::Structure
end

#model_data_urlString

The S3 path where the model artifacts, which result from model training, are stored. This path must point to a single gzip compressed tar archive (.tar.gz suffix).

If you provide a value for this parameter, Amazon SageMaker uses AWS Security Token Service to download model artifacts from the S3 path you provide. AWS STS is activated in your IAM user account by default. If you previously deactivated AWS STS for a region, you need to reactivate AWS STS for that region. For more information, see Activating and Deactivating AWS STS i an AWS Region in the AWS Identity and Access Management User Guide.

Returns:

  • (String)


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# File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 266

class ContainerDefinition < Struct.new(
  :container_hostname,
  :image,
  :model_data_url,
  :environment)
  include Aws::Structure
end