AlgorithmSpecification Class | AWS SDK for .NET V3

Specifies the training algorithm to use in a CreateTrainingJob request.

For more information about algorithms provided by SageMaker, see Algorithms. For information about using your own algorithms, see Using Your Own Algorithms with Amazon SageMaker.

Inheritance Hierarchy

System.Object
Amazon.SageMaker.Model.AlgorithmSpecification

Namespace: Amazon.SageMaker.Model
Assembly: AWSSDK.SageMaker.dll
Version: 3.x.y.z

Syntax

public class AlgorithmSpecification

The AlgorithmSpecification type exposes the following members

Constructors

	Name	Description
	AlgorithmSpecification()

Properties

Name	Type	Description
AlgorithmName	System.String	Gets and sets the property AlgorithmName. The name of the algorithm resource to use for the training job. This must be an algorithm resource that you created or subscribe to on Amazon Web Services Marketplace. You must specify either the algorithm name to the `AlgorithmName` parameter or the image URI of the algorithm container to the `TrainingImage` parameter. Note that the `AlgorithmName` parameter is mutually exclusive with the `TrainingImage` parameter. If you specify a value for the `AlgorithmName` parameter, you can't specify a value for `TrainingImage`, and vice versa. If you specify values for both parameters, the training job might break; if you don't specify any value for both parameters, the training job might raise a `null` error.
ContainerArguments	System.Collections.Generic.List<System.String>	Gets and sets the property ContainerArguments. The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
ContainerEntrypoint	System.Collections.Generic.List<System.String>	Gets and sets the property ContainerEntrypoint. The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for more information.
EnableSageMakerMetricsTimeSeries	System.Boolean	Gets and sets the property EnableSageMakerMetricsTimeSeries. To generate and save time-series metrics during training, set to `true`. The default is `false` and time-series metrics aren't generated except in the following cases: You use one of the SageMaker built-in algorithms You use one of the following Prebuilt SageMaker Docker Images: Tensorflow (version >= 1.15) MXNet (version >= 1.6) PyTorch (version >= 1.3) You specify at least one MetricDefinition
MetricDefinitions	System.Collections.Generic.List<Amazon.SageMaker.Model.MetricDefinition>	Gets and sets the property MetricDefinitions. A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. SageMaker publishes each metric to Amazon CloudWatch.
TrainingImage	System.String	Gets and sets the property TrainingImage. The registry path of the Docker image that contains the training algorithm. For information about docker registry paths for SageMaker built-in algorithms, see Docker Registry Paths and Example Code in the Amazon SageMaker developer guide. SageMaker supports both `registry/repository[:tag]` and `registry/repository[@digest]` image path formats. For more information about using your custom training container, see Using Your Own Algorithms with Amazon SageMaker. You must specify either the algorithm name to the `AlgorithmName` parameter or the image URI of the algorithm container to the `TrainingImage` parameter. For more information, see the note in the `AlgorithmName` parameter description.
TrainingImageConfig	Amazon.SageMaker.Model.TrainingImageConfig	Gets and sets the property TrainingImageConfig. The configuration to use an image from a private Docker registry for a training job.
TrainingInputMode	Amazon.SageMaker.TrainingInputMode	Gets and sets the property TrainingInputMode.

Version Information

.NET Core App:
Supported in: 3.1

.NET Standard:
Supported in: 2.0

.NET Framework:
Supported in: 4.5, 4.0, 3.5