com.amazonaws.services.sagemaker.model

Class HyperParameterAlgorithmSpecification

java.lang.Object

com.amazonaws.services.sagemaker.model.HyperParameterAlgorithmSpecification

All Implemented Interfaces:

StructuredPojo, Serializable, Cloneable

@Generated(value="com.amazonaws:aws-java-sdk-code-generator")
public class HyperParameterAlgorithmSpecification
extends Object
implements Serializable, Cloneable, StructuredPojo

Specifies which training algorithm to use for training jobs that a hyperparameter tuning job launches and the metrics to monitor.

See Also:

AWS API Documentation, Serialized Form

Constructor Summary

Constructors

Constructor and Description
HyperParameterAlgorithmSpecification()

Method Summary

Modifier and Type	Method and Description
HyperParameterAlgorithmSpecification	clone()
boolean	equals(Object obj)
String	getAlgorithmName() The name of the resource algorithm to use for the hyperparameter tuning job.
List<MetricDefinition>	getMetricDefinitions() An array of MetricDefinition objects that specify the metrics that the algorithm emits.
String	getTrainingImage() The registry path of the Docker image that contains the training algorithm.
String	getTrainingInputMode() The input mode that the algorithm supports: File or Pipe.
int	hashCode()
void	marshall(ProtocolMarshaller protocolMarshaller) Marshalls this structured data using the given ProtocolMarshaller.
void	setAlgorithmName(String algorithmName) The name of the resource algorithm to use for the hyperparameter tuning job.
void	setMetricDefinitions(Collection<MetricDefinition> metricDefinitions) An array of MetricDefinition objects that specify the metrics that the algorithm emits.
void	setTrainingImage(String trainingImage) The registry path of the Docker image that contains the training algorithm.
void	setTrainingInputMode(String trainingInputMode) The input mode that the algorithm supports: File or Pipe.
String	toString() Returns a string representation of this object.
HyperParameterAlgorithmSpecification	withAlgorithmName(String algorithmName) The name of the resource algorithm to use for the hyperparameter tuning job.
HyperParameterAlgorithmSpecification	withMetricDefinitions(Collection<MetricDefinition> metricDefinitions) An array of MetricDefinition objects that specify the metrics that the algorithm emits.
HyperParameterAlgorithmSpecification	withMetricDefinitions(MetricDefinition... metricDefinitions) An array of MetricDefinition objects that specify the metrics that the algorithm emits.
HyperParameterAlgorithmSpecification	withTrainingImage(String trainingImage) The registry path of the Docker image that contains the training algorithm.
HyperParameterAlgorithmSpecification	withTrainingInputMode(String trainingInputMode) The input mode that the algorithm supports: File or Pipe.
HyperParameterAlgorithmSpecification	withTrainingInputMode(TrainingInputMode trainingInputMode) The input mode that the algorithm supports: File or Pipe.

Methods inherited from class java.lang.Object

getClass, notify, notifyAll, wait, wait, wait

Constructor Detail

HyperParameterAlgorithmSpecification

public HyperParameterAlgorithmSpecification()

Method Detail

setTrainingImage

public void setTrainingImage(String trainingImage)

The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.

Parameters:

trainingImage - The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.

getTrainingImage

public String getTrainingImage()

The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.

Returns:

The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.

withTrainingImage

public HyperParameterAlgorithmSpecification withTrainingImage(String trainingImage)

The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.

Parameters:

trainingImage - The registry path of the Docker image that contains the training algorithm. For information about Docker registry paths for built-in algorithms, see Algorithms Provided by Amazon SageMaker: Common Parameters. Amazon SageMaker supports both registry/repository[:tag] and registry/repository[@digest] image path formats. For more information, see Using Your Own Algorithms with Amazon SageMaker.

Returns:

Returns a reference to this object so that method calls can be chained together.

setTrainingInputMode

public void setTrainingInputMode(String trainingInputMode)

The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

Parameters:

trainingInputMode - The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

See Also:

TrainingInputMode

getTrainingInputMode

public String getTrainingInputMode()

The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

Returns:

The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

See Also:

TrainingInputMode

withTrainingInputMode

public HyperParameterAlgorithmSpecification withTrainingInputMode(String trainingInputMode)

The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

Parameters:

trainingInputMode - The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

TrainingInputMode

withTrainingInputMode

public HyperParameterAlgorithmSpecification withTrainingInputMode(TrainingInputMode trainingInputMode)

The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

Parameters:

trainingInputMode - The input mode that the algorithm supports: File or Pipe. In File input mode, Amazon SageMaker downloads the training data from Amazon S3 to the storage volume that is attached to the training instance and mounts the directory to the Docker volume for the training container. In Pipe input mode, Amazon SageMaker streams data directly from Amazon S3 to the container.

If you specify File mode, make sure that you provision the storage volume that is attached to the training instance with enough capacity to accommodate the training data downloaded from Amazon S3, the model artifacts, and intermediate information.

For more information about input modes, see Algorithms.

Returns:

Returns a reference to this object so that method calls can be chained together.

See Also:

TrainingInputMode

setAlgorithmName

public void setAlgorithmName(String algorithmName)

The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.

Parameters:

algorithmName - The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.

getAlgorithmName

public String getAlgorithmName()

The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.

Returns:

The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.

withAlgorithmName

public HyperParameterAlgorithmSpecification withAlgorithmName(String algorithmName)

The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.

Parameters:

algorithmName - The name of the resource algorithm to use for the hyperparameter tuning job. If you specify a value for this parameter, do not specify a value for TrainingImage.

Returns:

Returns a reference to this object so that method calls can be chained together.

getMetricDefinitions

public List<MetricDefinition> getMetricDefinitions()

An array of MetricDefinition objects that specify the metrics that the algorithm emits.

Returns:

An array of MetricDefinition objects that specify the metrics that the algorithm emits.

setMetricDefinitions

public void setMetricDefinitions(Collection<MetricDefinition> metricDefinitions)

An array of MetricDefinition objects that specify the metrics that the algorithm emits.

Parameters:

metricDefinitions - An array of MetricDefinition objects that specify the metrics that the algorithm emits.

withMetricDefinitions

public HyperParameterAlgorithmSpecification withMetricDefinitions(MetricDefinition... metricDefinitions)

An array of MetricDefinition objects that specify the metrics that the algorithm emits.

NOTE: This method appends the values to the existing list (if any). Use setMetricDefinitions(java.util.Collection) or withMetricDefinitions(java.util.Collection) if you want to override the existing values.

Parameters:

metricDefinitions - An array of MetricDefinition objects that specify the metrics that the algorithm emits.

Returns:

Returns a reference to this object so that method calls can be chained together.

withMetricDefinitions

public HyperParameterAlgorithmSpecification withMetricDefinitions(Collection<MetricDefinition> metricDefinitions)

An array of MetricDefinition objects that specify the metrics that the algorithm emits.

Parameters:

metricDefinitions - An array of MetricDefinition objects that specify the metrics that the algorithm emits.

Returns:

Returns a reference to this object so that method calls can be chained together.

toString

public String toString()

Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.

Overrides:

toString in class Object

Returns:

A string representation of this object.

See Also:

Object.toString()

equals

public boolean equals(Object obj)

Overrides:

equals in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

clone

public HyperParameterAlgorithmSpecification clone()

Overrides:

clone in class Object

marshall

public void marshall(ProtocolMarshaller protocolMarshaller)

Description copied from interface: StructuredPojo

Marshalls this structured data using the given ProtocolMarshaller.

Specified by:

marshall in interface StructuredPojo

Parameters:

protocolMarshaller - Implementation of ProtocolMarshaller used to marshall this object's data.