software.amazon.awssdk.services.sagemaker.model

Class AlgorithmSpecification

java.lang.Object

software.amazon.awssdk.services.sagemaker.model.AlgorithmSpecification

All Implemented Interfaces:

Serializable, SdkPojo, ToCopyableBuilder<AlgorithmSpecification.Builder,AlgorithmSpecification>

@Generated(value="software.amazon.awssdk:codegen")
public final class AlgorithmSpecification
extends Object
implements SdkPojo, Serializable, ToCopyableBuilder<AlgorithmSpecification.Builder,AlgorithmSpecification>

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.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static interface	AlgorithmSpecification.Builder

Method Summary

Modifier and Type	Method and Description
String	algorithmName() The name of the algorithm resource to use for the training job.
static AlgorithmSpecification.Builder	builder()
Boolean	enableSageMakerMetricsTimeSeries() To generate and save time-series metrics during training, set to true.
boolean	equals(Object obj)
boolean	equalsBySdkFields(Object obj)
<T> Optional<T>	getValueForField(String fieldName, Class<T> clazz)
int	hashCode()
boolean	hasMetricDefinitions() For responses, this returns true if the service returned a value for the MetricDefinitions property.
List<MetricDefinition>	metricDefinitions() A list of metric definition objects.
List<SdkField<?>>	sdkFields()
static Class<? extends AlgorithmSpecification.Builder>	serializableBuilderClass()
AlgorithmSpecification.Builder	toBuilder()
String	toString() Returns a string representation of this object.
String	trainingImage() The registry path of the Docker image that contains the training algorithm.
TrainingInputMode	trainingInputMode() Returns the value of the TrainingInputMode property for this object.
String	trainingInputModeAsString() Returns the value of the TrainingInputMode property for this object.

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder

copy

Method Detail

trainingImage

public final String 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.

Returns:

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.

algorithmName

public final String 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.

Returns:

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.

trainingInputMode

public final TrainingInputMode trainingInputMode()

Returns the value of the TrainingInputMode property for this object.

If the service returns an enum value that is not available in the current SDK version, trainingInputMode will return TrainingInputMode.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from trainingInputModeAsString().

Returns:

The value of the TrainingInputMode property for this object.

See Also:

TrainingInputMode

trainingInputModeAsString

public final String trainingInputModeAsString()

Returns the value of the TrainingInputMode property for this object.

If the service returns an enum value that is not available in the current SDK version, trainingInputMode will return TrainingInputMode.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from trainingInputModeAsString().

Returns:

The value of the TrainingInputMode property for this object.

See Also:

TrainingInputMode

hasMetricDefinitions

public final boolean hasMetricDefinitions()

For responses, this returns true if the service returned a value for the MetricDefinitions property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.

metricDefinitions

public final List<MetricDefinition> 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.

Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.

This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasMetricDefinitions() method.

Returns:

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.

enableSageMakerMetricsTimeSeries

public final Boolean 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

Returns:

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

toBuilder

public AlgorithmSpecification.Builder toBuilder()

Specified by:

toBuilder in interface ToCopyableBuilder<AlgorithmSpecification.Builder,AlgorithmSpecification>

builder

public static AlgorithmSpecification.Builder builder()

serializableBuilderClass

public static Class<? extends AlgorithmSpecification.Builder> serializableBuilderClass()

hashCode

public final int hashCode()

Overrides:

hashCode in class Object

equals

public final boolean equals(Object obj)

Overrides:

equals in class Object

equalsBySdkFields

public final boolean equalsBySdkFields(Object obj)

Specified by:

equalsBySdkFields in interface SdkPojo

toString

public final 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

getValueForField

public final <T> Optional<T> getValueForField(String fieldName,
                                              Class<T> clazz)

sdkFields

public final List<SdkField<?>> sdkFields()

Specified by:

sdkFields in interface SdkPojo