AlgorithmSpecification

class aws_cdk.aws_stepfunctions_tasks.AlgorithmSpecification(*, algorithm_name=None, metric_definitions=None, training_image=None, training_input_mode=None)

Bases: object

(experimental) Specify the training algorithm and algorithm-specific metadata.

Parameters
  • algorithm_name (Optional[str]) – (experimental) Name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on AWS Marketplace. If you specify a value for this parameter, you can’t specify a value for TrainingImage. Default: - No algorithm is specified

  • metric_definitions (Optional[List[MetricDefinition]]) – (experimental) List of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. Default: - No metrics

  • training_image (Optional[DockerImage]) – (experimental) Registry path of the Docker image that contains the training algorithm. Default: - No Docker image is specified

  • training_input_mode (Optional[InputMode]) – (experimental) Input mode that the algorithm supports. Default: ‘File’ mode

Stability

experimental

Attributes

algorithm_name

(experimental) Name of the algorithm resource to use for the training job.

This must be an algorithm resource that you created or subscribe to on AWS Marketplace. If you specify a value for this parameter, you can’t specify a value for TrainingImage.

Default
  • No algorithm is specified

Stability

experimental

Return type

Optional[str]

metric_definitions

(experimental) List of metric definition objects.

Each object specifies the metric name and regular expressions used to parse algorithm logs.

Default
  • No metrics

Stability

experimental

Return type

Optional[List[MetricDefinition]]

training_image

(experimental) Registry path of the Docker image that contains the training algorithm.

Default
  • No Docker image is specified

Stability

experimental

Return type

Optional[DockerImage]

training_input_mode

(experimental) Input mode that the algorithm supports.

Default

‘File’ mode

Stability

experimental

Return type

Optional[InputMode]