Class: Aws::SageMaker::Types::DescribeTrainingJobResponse

Inherits:

Struct

Object
Struct
Aws::SageMaker::Types::DescribeTrainingJobResponse

show all

Includes:: Aws::Structure

Defined in:: lib/aws-sdk-sagemaker/types.rb

Overview

Instance Attribute Summary collapse

#algorithm_specification ⇒ Types::AlgorithmSpecification

Information about the algorithm used for training, and algorithm metadata.
#auto_ml_job_arn ⇒ String
#billable_time_in_seconds ⇒ Integer

The billable time in seconds.
#checkpoint_config ⇒ Types::CheckpointConfig

Contains information about the output location for managed spot training checkpoint data.
#creation_time ⇒ Time

A timestamp that indicates when the training job was created.
#debug_hook_config ⇒ Types::DebugHookConfig

Configuration information for the debug hook parameters, collection configuration, and storage paths.
#debug_rule_configurations ⇒ Array<Types::DebugRuleConfiguration>

Configuration information for debugging rules.
#debug_rule_evaluation_statuses ⇒ Array<Types::DebugRuleEvaluationStatus>

Status about the debug rule evaluation.
#enable_inter_container_traffic_encryption ⇒ Boolean

To encrypt all communications between ML compute instances in distributed training, choose ‘True`.
#enable_managed_spot_training ⇒ Boolean

A Boolean indicating whether managed spot training is enabled (‘True`) or not (`False`).
#enable_network_isolation ⇒ Boolean

If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose ‘True`.
#experiment_config ⇒ Types::ExperimentConfig

Configuration for the experiment.
#failure_reason ⇒ String

If the training job failed, the reason it failed.
#final_metric_data_list ⇒ Array<Types::MetricData>

A collection of ‘MetricData` objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
#hyper_parameters ⇒ Hash<String,String>

Algorithm-specific parameters.
#input_data_config ⇒ Array<Types::Channel>

An array of ‘Channel` objects that describes each data input channel.
#labeling_job_arn ⇒ String

The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
#last_modified_time ⇒ Time

A timestamp that indicates when the status of the training job was last modified.
#model_artifacts ⇒ Types::ModelArtifacts

Information about the Amazon S3 location that is configured for storing model artifacts.
#output_data_config ⇒ Types::OutputDataConfig

The S3 path where model artifacts that you configured when creating the job are stored.
#resource_config ⇒ Types::ResourceConfig

Resources, including ML compute instances and ML storage volumes, that are configured for model training.
#role_arn ⇒ String

The AWS Identity and Access Management (IAM) role configured for the training job.
#secondary_status ⇒ String

Provides detailed information about the state of the training job.
#secondary_status_transitions ⇒ Array<Types::SecondaryStatusTransition>

A history of all of the secondary statuses that the training job has transitioned through.
#stopping_condition ⇒ Types::StoppingCondition

Specifies a limit to how long a model training job can run.
#tensor_board_output_config ⇒ Types::TensorBoardOutputConfig

Configuration of storage locations for TensorBoard output.
#training_end_time ⇒ Time

Indicates the time when the training job ends on training instances.
#training_job_arn ⇒ String

The Amazon Resource Name (ARN) of the training job.
#training_job_name ⇒ String

Name of the model training job.
#training_job_status ⇒ String

The status of the training job.
#training_start_time ⇒ Time

Indicates the time when the training job starts on training instances.
#training_time_in_seconds ⇒ Integer

The training time in seconds.
#tuning_job_arn ⇒ String

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
#vpc_config ⇒ Types::VpcConfig

A VpcConfig object that specifies the VPC that this training job has access to.

Instance Attribute Details

#algorithm_specification ⇒ `Types::AlgorithmSpecification`

Information about the algorithm used for training, and algorithm metadata.

Returns:

(Types::AlgorithmSpecification)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#auto_ml_job_arn ⇒ `String`

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#billable_time_in_seconds ⇒ `Integer`

The billable time in seconds.

You can calculate the savings from using managed spot training using the formula ‘(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100`. For example, if `BillableTimeInSeconds` is 100 and `TrainingTimeInSeconds` is 500, the savings is 80%.

Returns:

(Integer)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#checkpoint_config ⇒ `Types::CheckpointConfig`

Contains information about the output location for managed spot training checkpoint data.

Returns:

(Types::CheckpointConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#creation_time ⇒ `Time`

A timestamp that indicates when the training job was created.

Returns:

(Time)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#debug_hook_config ⇒ `Types::DebugHookConfig`

Configuration information for the debug hook parameters, collection configuration, and storage paths.

Returns:

(Types::DebugHookConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#debug_rule_configurations ⇒ `Array<Types::DebugRuleConfiguration>`

Configuration information for debugging rules.

Returns:

(Array<Types::DebugRuleConfiguration>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#debug_rule_evaluation_statuses ⇒ `Array<Types::DebugRuleEvaluationStatus>`

Status about the debug rule evaluation.

Returns:

(Array<Types::DebugRuleEvaluationStatus>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#enable_inter_container_traffic_encryption ⇒ `Boolean`

To encrypt all communications between ML compute instances in distributed training, choose ‘True`. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning algorithms in distributed training.

Returns:

(Boolean)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#enable_managed_spot_training ⇒ `Boolean`

A Boolean indicating whether managed spot training is enabled (‘True`) or not (`False`).

Returns:

(Boolean)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#enable_network_isolation ⇒ `Boolean`

If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose ‘True`. If you enable network isolation for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.

<note markdown=“1”> The Semantic Segmentation built-in algorithm does not support network isolation.

</note>

Returns:

(Boolean)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#experiment_config ⇒ `Types::ExperimentConfig`

Configuration for the experiment.

Returns:

(Types::ExperimentConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#failure_reason ⇒ `String`

If the training job failed, the reason it failed.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#final_metric_data_list ⇒ `Array<Types::MetricData>`

A collection of ‘MetricData` objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.

Returns:

(Array<Types::MetricData>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#hyper_parameters ⇒ `Hash<String,String>`

Algorithm-specific parameters.

Returns:

(Hash<String,String>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#input_data_config ⇒ `Array<Types::Channel>`

An array of ‘Channel` objects that describes each data input channel.

Returns:

(Array<Types::Channel>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#labeling_job_arn ⇒ `String`

The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#last_modified_time ⇒ `Time`

A timestamp that indicates when the status of the training job was last modified.

Returns:

(Time)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#model_artifacts ⇒ `Types::ModelArtifacts`

Information about the Amazon S3 location that is configured for storing model artifacts.

Returns:

(Types::ModelArtifacts)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#output_data_config ⇒ `Types::OutputDataConfig`

The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.

Returns:

(Types::OutputDataConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#resource_config ⇒ `Types::ResourceConfig`

Resources, including ML compute instances and ML storage volumes, that are configured for model training.

Returns:

(Types::ResourceConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#role_arn ⇒ `String`

The AWS Identity and Access Management (IAM) role configured for the training job.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#secondary_status ⇒ `String`

Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see ‘StatusMessage` under SecondaryStatusTransition.

Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:

InProgress : * ‘Starting` - Starting the training job.

* `Downloading` - An optional stage for algorithms that support
  `File` training input mode. It indicates that data is being
  downloaded to the ML storage volumes.

* `Training` - Training is in progress.

* `Interrupted` - The job stopped because the managed spot
  training instances were interrupted.

* `Uploading` - Training is complete and the model artifacts are
  being uploaded to the S3 location.

Completed : * ‘Completed` - The training job has completed.

Failed : * ‘Failed` - The training job has failed. The reason for the

  failure is returned in the `FailureReason` field of
  `DescribeTrainingJobResponse`.

^

Stopped : * ‘MaxRuntimeExceeded` - The job stopped because it exceeded the

  maximum allowed runtime.

* `MaxWaitTmeExceeded` - The job stopped because it exceeded the
  maximum allowed wait time.

* `Stopped` - The training job has stopped.

Stopping : * ‘Stopping` - Stopping the training job.

Valid values for ‘SecondaryStatus` are subject to change.

We no longer support the following secondary statuses:

‘LaunchingMLInstances`
‘PreparingTrainingStack`
‘DownloadingTrainingImage`

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#secondary_status_transitions ⇒ `Array<Types::SecondaryStatusTransition>`

A history of all of the secondary statuses that the training job has transitioned through.

Returns:

(Array<Types::SecondaryStatusTransition>)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#stopping_condition ⇒ `Types::StoppingCondition`

Specifies a limit to how long a model training job can run. It also specifies the maximum time to wait for a spot instance. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.

To stop a job, Amazon SageMaker sends the algorithm the ‘SIGTERM` signal, which delays job termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of training are not lost.

Returns:

(Types::StoppingCondition)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#tensor_board_output_config ⇒ `Types::TensorBoardOutputConfig`

Configuration of storage locations for TensorBoard output.

Returns:

(Types::TensorBoardOutputConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#training_end_time ⇒ `Time`

Indicates the time when the training job ends on training instances. You are billed for the time interval between the value of ‘TrainingStartTime` and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when Amazon SageMaker detects a job failure.

Returns:

(Time)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#training_job_arn ⇒ `String`

The Amazon Resource Name (ARN) of the training job.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#training_job_name ⇒ `String`

Name of the model training job.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#training_job_status ⇒ `String`

The status of the training job.

Amazon SageMaker provides the following training job statuses:

‘InProgress` - The training is in progress.
‘Completed` - The training job has completed.
‘Failed` - The training job has failed. To see the reason for the failure, see the `FailureReason` field in the response to a `DescribeTrainingJobResponse` call.
‘Stopping` - The training job is stopping.
‘Stopped` - The training job has stopped.

For more detailed information, see ‘SecondaryStatus`.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#training_start_time ⇒ `Time`

Indicates the time when the training job starts on training instances. You are billed for the time interval between this time and the value of ‘TrainingEndTime`. The start time in CloudWatch Logs might be later than this time. The difference is due to the time it takes to download the training data and to the size of the training container.

Returns:

(Time)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#training_time_in_seconds ⇒ `Integer`

The training time in seconds.

Returns:

(Integer)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#tuning_job_arn ⇒ `String`

The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.

Returns:

(String)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

#vpc_config ⇒ `Types::VpcConfig`

A VpcConfig object that specifies the VPC that this training job has access to. For more information, see [Protect Training Jobs by Using an Amazon Virtual Private Cloud].

[1]: docs.aws.amazon.com/sagemaker/latest/dg/train-vpc.html

Returns:

(Types::VpcConfig)

# File 'lib/aws-sdk-sagemaker/types.rb', line 8151

class DescribeTrainingJobResponse < Struct.new(
  :training_job_name,
  :training_job_arn,
  :tuning_job_arn,
  :labeling_job_arn,
  :auto_ml_job_arn,
  :model_artifacts,
  :training_job_status,
  :secondary_status,
  :failure_reason,
  :hyper_parameters,
  :algorithm_specification,
  :role_arn,
  :input_data_config,
  :output_data_config,
  :resource_config,
  :vpc_config,
  :stopping_condition,
  :creation_time,
  :training_start_time,
  :training_end_time,
  :last_modified_time,
  :secondary_status_transitions,
  :final_metric_data_list,
  :enable_network_isolation,
  :enable_inter_container_traffic_encryption,
  :enable_managed_spot_training,
  :checkpoint_config,
  :training_time_in_seconds,
  :billable_time_in_seconds,
  :debug_hook_config,
  :experiment_config,
  :debug_rule_configurations,
  :tensor_board_output_config,
  :debug_rule_evaluation_statuses)
  include Aws::Structure
end

Class: Aws::SageMaker::Types::DescribeTrainingJobResponse

Overview

Instance Attribute Summary collapse

Instance Attribute Details

#algorithm_specification ⇒ Types::AlgorithmSpecification

#auto_ml_job_arn ⇒ String

#billable_time_in_seconds ⇒ Integer

#checkpoint_config ⇒ Types::CheckpointConfig

#creation_time ⇒ Time

#debug_hook_config ⇒ Types::DebugHookConfig

#debug_rule_configurations ⇒ Array<Types::DebugRuleConfiguration>

#debug_rule_evaluation_statuses ⇒ Array<Types::DebugRuleEvaluationStatus>

#enable_inter_container_traffic_encryption ⇒ Boolean

#enable_managed_spot_training ⇒ Boolean

#enable_network_isolation ⇒ Boolean

#experiment_config ⇒ Types::ExperimentConfig

#failure_reason ⇒ String

#final_metric_data_list ⇒ Array<Types::MetricData>

#hyper_parameters ⇒ Hash<String,String>

#input_data_config ⇒ Array<Types::Channel>

#labeling_job_arn ⇒ String

#last_modified_time ⇒ Time

#model_artifacts ⇒ Types::ModelArtifacts

#output_data_config ⇒ Types::OutputDataConfig

#resource_config ⇒ Types::ResourceConfig

#role_arn ⇒ String

#secondary_status ⇒ String

#secondary_status_transitions ⇒ Array<Types::SecondaryStatusTransition>

#stopping_condition ⇒ Types::StoppingCondition

#tensor_board_output_config ⇒ Types::TensorBoardOutputConfig

#training_end_time ⇒ Time

#training_job_arn ⇒ String

#training_job_name ⇒ String

#training_job_status ⇒ String

#training_start_time ⇒ Time

#training_time_in_seconds ⇒ Integer

#tuning_job_arn ⇒ String

#vpc_config ⇒ Types::VpcConfig

#algorithm_specification ⇒ `Types::AlgorithmSpecification`

#auto_ml_job_arn ⇒ `String`

#billable_time_in_seconds ⇒ `Integer`

#checkpoint_config ⇒ `Types::CheckpointConfig`

#creation_time ⇒ `Time`

#debug_hook_config ⇒ `Types::DebugHookConfig`

#debug_rule_configurations ⇒ `Array<Types::DebugRuleConfiguration>`

#debug_rule_evaluation_statuses ⇒ `Array<Types::DebugRuleEvaluationStatus>`

#enable_inter_container_traffic_encryption ⇒ `Boolean`

#enable_managed_spot_training ⇒ `Boolean`

#enable_network_isolation ⇒ `Boolean`

#experiment_config ⇒ `Types::ExperimentConfig`

#failure_reason ⇒ `String`

#final_metric_data_list ⇒ `Array<Types::MetricData>`

#hyper_parameters ⇒ `Hash<String,String>`

#input_data_config ⇒ `Array<Types::Channel>`

#labeling_job_arn ⇒ `String`

#last_modified_time ⇒ `Time`

#model_artifacts ⇒ `Types::ModelArtifacts`

#output_data_config ⇒ `Types::OutputDataConfig`

#resource_config ⇒ `Types::ResourceConfig`

#role_arn ⇒ `String`

#secondary_status ⇒ `String`

#secondary_status_transitions ⇒ `Array<Types::SecondaryStatusTransition>`

#stopping_condition ⇒ `Types::StoppingCondition`

#tensor_board_output_config ⇒ `Types::TensorBoardOutputConfig`

#training_end_time ⇒ `Time`

#training_job_arn ⇒ `String`

#training_job_name ⇒ `String`

#training_job_status ⇒ `String`

#training_start_time ⇒ `Time`

#training_time_in_seconds ⇒ `Integer`

#tuning_job_arn ⇒ `String`

#vpc_config ⇒ `Types::VpcConfig`