Class: Aws::SageMaker::Types::TrainingSpecification

Inherits:

Struct

• Object
• Struct
• Aws::SageMaker::Types::TrainingSpecification

Includes:

Aws::Structure

Defined in:

lib/aws-sdk-sagemaker/types.rb

Overview

Defines how the algorithm is used for a training job.

See Also:

• AWS API Documentation

Constant Summary

SENSITIVE =

[]

Instance Attribute Summary

• #additional_s3_data_source ⇒ Types::AdditionalS3DataSource

  The additional data source used during the training job.

• #metric_definitions ⇒ Array<Types::MetricDefinition>

  A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

• #supported_hyper_parameters ⇒ Array<Types::HyperParameterSpecification>

  A list of the HyperParameterSpecification objects, that define the supported hyperparameters.

• #supported_training_instance_types ⇒ Array<String>

  A list of the instance types that this algorithm can use for training.

• #supported_tuning_job_objective_metrics ⇒ Array<Types::HyperParameterTuningJobObjective>

  A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

• #supports_distributed_training ⇒ Boolean

  Indicates whether the algorithm supports distributed training.

• #training_channels ⇒ Array<Types::ChannelSpecification>

  A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.

• #training_image ⇒ String

  The Amazon ECR registry path of the Docker image that contains the training algorithm.

• #training_image_digest ⇒ String

  An MD5 hash of the training algorithm that identifies the Docker image used for training.

Instance Attribute Details

#additional_s3_data_source ⇒ Types::AdditionalS3DataSource

The additional data source used during the training job.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#metric_definitions ⇒ Array<Types::MetricDefinition>

A list of MetricDefinition objects, which are used for parsing metrics generated by the algorithm.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#supported_hyper_parameters ⇒ Array<Types::HyperParameterSpecification>

A list of the HyperParameterSpecification objects, that define the supported hyperparameters. This is required if the algorithm supports automatic model tuning.>

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#supported_training_instance_types ⇒ Array<String>

A list of the instance types that this algorithm can use for training.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#supported_tuning_job_objective_metrics ⇒ Array<Types::HyperParameterTuningJobObjective>

A list of the metrics that the algorithm emits that can be used as the objective metric in a hyperparameter tuning job.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#supports_distributed_training ⇒ Boolean

Indicates whether the algorithm supports distributed training. If set to false, buyers can't request more than one instance during training.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#training_channels ⇒ Array<Types::ChannelSpecification>

A list of ChannelSpecification objects, which specify the input sources to be used by the algorithm.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#training_image ⇒ String

The Amazon ECR registry path of the Docker image that contains the training algorithm.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end

#training_image_digest ⇒ String

An MD5 hash of the training algorithm that identifies the Docker image used for training.

# File 'lib/aws-sdk-sagemaker/types.rb', line 55113

class TrainingSpecification < Struct.new(
  :training_image,
  :training_image_digest,
  :supported_hyper_parameters,
  :supported_training_instance_types,
  :supports_distributed_training,
  :metric_definitions,
  :training_channels,
  :supported_tuning_job_objective_metrics,
  :additional_s3_data_source)
  SENSITIVE = []
  include Aws::Structure
end