Class: Aws::SageMaker::Types::TrainingSpecification
- Inherits:
- 
      Struct
      
        - Object
- Struct
- Aws::SageMaker::Types::TrainingSpecification
 
- Defined in:
- gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb
Overview
Defines how the algorithm is used for a training job.
Constant Summary collapse
- SENSITIVE =
- [] 
Instance Attribute Summary collapse
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      #additional_s3_data_source  ⇒ Types::AdditionalS3DataSource 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    The additional data source used during the training job. 
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      #metric_definitions  ⇒ Array<Types::MetricDefinition> 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    A list of MetricDefinitionobjects, which are used for parsing metrics generated by the algorithm.
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      #supported_hyper_parameters  ⇒ Array<Types::HyperParameterSpecification> 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    A list of the HyperParameterSpecificationobjects, that define the supported hyperparameters.
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      #supported_training_instance_types  ⇒ Array<String> 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    A list of the instance types that this algorithm can use for training. 
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      #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. 
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      #supports_distributed_training  ⇒ Boolean 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    Indicates whether the algorithm supports distributed training. 
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      #training_channels  ⇒ Array<Types::ChannelSpecification> 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    A list of ChannelSpecificationobjects, which specify the input sources to be used by the algorithm.
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      #training_image  ⇒ String 
    
    
  
  
  
  
    
    
  
  
  
  
  
  
    The Amazon ECR registry path of the Docker image that contains the training algorithm. 
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      #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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.>
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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.
| 48992 48993 48994 48995 48996 48997 48998 48999 49000 49001 49002 49003 49004 | # File 'gems/aws-sdk-sagemaker/lib/aws-sdk-sagemaker/types.rb', line 48992 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 |