Class: Aws::SageMaker::Types::RecommendationJobContainerConfig

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::RecommendationJobContainerConfig

Includes:

Aws::Structure

Defined in:

lib/aws-sdk-sagemaker/types.rb

Overview

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.

[1]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_CreateInferenceRecommendationsJob.html

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #data_input_config ⇒ String

  Specifies the name and shape of the expected data inputs for your trained model with a JSON dictionary form.

• #domain ⇒ String

  The machine learning domain of the model and its components.

• #framework ⇒ String

  The machine learning framework of the container image.

• #framework_version ⇒ String

  The framework version of the container image.

• #nearest_model_name ⇒ String

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

• #payload_config ⇒ Types::RecommendationJobPayloadConfig

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

• #supported_endpoint_type ⇒ String

  The endpoint type to receive recommendations for.

• #supported_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.

• #task ⇒ String

  The machine learning task that the model accomplishes.

Instance Attribute Details

#data_input_config ⇒ String

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].

[1]: docs.aws.amazon.com/sagemaker/latest/APIReference/API_InputConfig.html#sagemaker-Type-InputConfig-DataInputConfig

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#domain ⇒ String

The machine learning domain of the model and its components.

Valid Values: ‘COMPUTER_VISION | NATURAL_LANGUAGE_PROCESSING | MACHINE_LEARNING`

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#framework ⇒ String

The machine learning framework of the container image.

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

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#framework_version ⇒ String

The framework version of the container image.

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#nearest_model_name ⇒ String

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`

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#payload_config ⇒ Types::RecommendationJobPayloadConfig

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

Returns:

• (Types::RecommendationJobPayloadConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#supported_endpoint_type ⇒ String

The endpoint type to receive recommendations for. By default this is null, and the results of the inference recommendation job return a combined list of both real-time and serverless benchmarks. By specifying a value for this field, you can receive a longer list of benchmarks for the desired endpoint type.

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#supported_instance_types ⇒ Array<String>

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

Returns:

• (Array<String>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#supported_response_mime_types ⇒ Array<String>

The supported MIME types for the output data.

Returns:

• (Array<String>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end

#task ⇒ String

The machine learning task that the model accomplishes.

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

Returns:

• (String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 40702

class RecommendationJobContainerConfig < Struct.new(
  :domain,
  :task,
  :framework,
  :framework_version,
  :payload_config,
  :nearest_model_name,
  :supported_instance_types,
  :supported_endpoint_type,
  :data_input_config,
  :supported_response_mime_types)
  SENSITIVE = []
  include Aws::Structure
end