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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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:

# File 'lib/aws-sdk-sagemaker/types.rb', line 45206

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