Class AlgorithmSpecification
- java.lang.Object
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- software.amazon.awssdk.services.sagemaker.model.AlgorithmSpecification
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- All Implemented Interfaces:
Serializable
,SdkPojo
,ToCopyableBuilder<AlgorithmSpecification.Builder,AlgorithmSpecification>
@Generated("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.
SageMaker uses its own SageMaker account credentials to pull and access built-in algorithms so built-in algorithms are universally accessible across all Amazon Web Services accounts. As a result, built-in algorithms have standard, unrestricted access. You cannot restrict built-in algorithms using IAM roles. Use custom algorithms if you require specific access controls.
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
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Nested Class Summary
Nested Classes Modifier and Type Class Description static interface
AlgorithmSpecification.Builder
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description String
algorithmName()
The name of the algorithm resource to use for the training job.static AlgorithmSpecification.Builder
builder()
List<String>
containerArguments()
The arguments for a container used to run a training job.List<String>
containerEntrypoint()
The entrypoint script for a Docker container used to run a training job.Boolean
enableSageMakerMetricsTimeSeries()
To generate and save time-series metrics during training, set totrue
.boolean
equals(Object obj)
boolean
equalsBySdkFields(Object obj)
<T> Optional<T>
getValueForField(String fieldName, Class<T> clazz)
boolean
hasContainerArguments()
For responses, this returns true if the service returned a value for the ContainerArguments property.boolean
hasContainerEntrypoint()
For responses, this returns true if the service returned a value for the ContainerEntrypoint property.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.Map<String,SdkField<?>>
sdkFieldNameToField()
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.TrainingImageConfig
trainingImageConfig()
The configuration to use an image from a private Docker registry for a training job.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
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Methods inherited from interface software.amazon.awssdk.utils.builder.ToCopyableBuilder
copy
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Method Detail
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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]
andregistry/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 theTrainingImage
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]
andregistry/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 theTrainingImage
parameter.For more information, see the note in the
AlgorithmName
parameter description.
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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 theTrainingImage
parameter.Note that the
AlgorithmName
parameter is mutually exclusive with theTrainingImage
parameter. If you specify a value for theAlgorithmName
parameter, you can't specify a value forTrainingImage
, 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 theTrainingImage
parameter.Note that the
AlgorithmName
parameter is mutually exclusive with theTrainingImage
parameter. If you specify a value for theAlgorithmName
parameter, you can't specify a value forTrainingImage
, 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.
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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 returnTrainingInputMode.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available fromtrainingInputModeAsString()
.- Returns:
- The value of the TrainingInputMode property for this object.
- See Also:
TrainingInputMode
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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 returnTrainingInputMode.UNKNOWN_TO_SDK_VERSION
. The raw value returned by the service is available fromtrainingInputModeAsString()
.- Returns:
- The value of the TrainingInputMode property for this object.
- See Also:
TrainingInputMode
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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 theisEmpty()
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.
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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.
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enableSageMakerMetricsTimeSeries
public final Boolean enableSageMakerMetricsTimeSeries()
To generate and save time-series metrics during training, set to
true
. The default isfalse
and time-series metrics aren't generated except in the following cases:-
You use one of the SageMaker built-in algorithms
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You use one of the following Prebuilt SageMaker Docker Images:
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Tensorflow (version >= 1.15)
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MXNet (version >= 1.6)
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PyTorch (version >= 1.3)
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You specify at least one MetricDefinition
- Returns:
- To generate and save time-series metrics during training, set to
true
. The default isfalse
and time-series metrics aren't generated except in the following cases:-
You use one of the SageMaker built-in algorithms
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You use one of the following Prebuilt SageMaker Docker Images:
-
Tensorflow (version >= 1.15)
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MXNet (version >= 1.6)
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PyTorch (version >= 1.3)
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You specify at least one MetricDefinition
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hasContainerEntrypoint
public final boolean hasContainerEntrypoint()
For responses, this returns true if the service returned a value for the ContainerEntrypoint property. This DOES NOT check that the value is non-empty (for which, you should check theisEmpty()
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.
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containerEntrypoint
public final List<String> 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.
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
hasContainerEntrypoint()
method.- Returns:
- 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.
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hasContainerArguments
public final boolean hasContainerArguments()
For responses, this returns true if the service returned a value for the ContainerArguments property. This DOES NOT check that the value is non-empty (for which, you should check theisEmpty()
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.
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containerArguments
public final List<String> containerArguments()
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
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
hasContainerArguments()
method.- Returns:
- The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information.
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trainingImageConfig
public final TrainingImageConfig trainingImageConfig()
The configuration to use an image from a private Docker registry for a training job.
- Returns:
- The configuration to use an image from a private Docker registry for a training job.
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toBuilder
public AlgorithmSpecification.Builder toBuilder()
- Specified by:
toBuilder
in interfaceToCopyableBuilder<AlgorithmSpecification.Builder,AlgorithmSpecification>
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builder
public static AlgorithmSpecification.Builder builder()
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serializableBuilderClass
public static Class<? extends AlgorithmSpecification.Builder> serializableBuilderClass()
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equalsBySdkFields
public final boolean equalsBySdkFields(Object obj)
- Specified by:
equalsBySdkFields
in interfaceSdkPojo
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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.
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sdkFieldNameToField
public final Map<String,SdkField<?>> sdkFieldNameToField()
- Specified by:
sdkFieldNameToField
in interfaceSdkPojo
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