@Generated(value="software.amazon.awssdk:codegen") public final class HyperParameterTrainingJobDefinition extends Object implements SdkPojo, Serializable, ToCopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>
Defines the training jobs launched by a hyperparameter tuning job.
| Modifier and Type | Class and Description |
|---|---|
static interface |
HyperParameterTrainingJobDefinition.Builder |
| Modifier and Type | Method and Description |
|---|---|
HyperParameterAlgorithmSpecification |
algorithmSpecification()
The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the
training jobs that the tuning job launches.
|
static HyperParameterTrainingJobDefinition.Builder |
builder() |
CheckpointConfig |
checkpointConfig()
Returns the value of the CheckpointConfig property for this object.
|
String |
definitionName()
The job definition name.
|
Boolean |
enableInterContainerTrafficEncryption()
To encrypt all communications between ML compute instances in distributed training, choose
True. |
Boolean |
enableManagedSpotTraining()
A Boolean indicating whether managed spot training is enabled (
True) or not (False). |
Boolean |
enableNetworkIsolation()
Isolates the training container.
|
boolean |
equals(Object obj) |
boolean |
equalsBySdkFields(Object obj) |
<T> Optional<T> |
getValueForField(String fieldName,
Class<T> clazz) |
int |
hashCode() |
boolean |
hasInputDataConfig()
Returns true if the InputDataConfig property was specified by the sender (it may be empty), or false if the
sender did not specify the value (it will be empty).
|
boolean |
hasStaticHyperParameters()
Returns true if the StaticHyperParameters property was specified by the sender (it may be empty), or false if the
sender did not specify the value (it will be empty).
|
ParameterRanges |
hyperParameterRanges()
Returns the value of the HyperParameterRanges property for this object.
|
List<Channel> |
inputDataConfig()
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
|
OutputDataConfig |
outputDataConfig()
Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning
job launches.
|
ResourceConfig |
resourceConfig()
The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning
job launches.
|
String |
roleArn()
The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
|
List<SdkField<?>> |
sdkFields() |
static Class<? extends HyperParameterTrainingJobDefinition.Builder> |
serializableBuilderClass() |
Map<String,String> |
staticHyperParameters()
Specifies the values of hyperparameters that do not change for the tuning job.
|
StoppingCondition |
stoppingCondition()
Specifies a limit to how long a model hyperparameter training job can run.
|
HyperParameterTrainingJobDefinition.Builder |
toBuilder() |
String |
toString()
Returns a string representation of this object.
|
HyperParameterTuningJobObjective |
tuningObjective()
Returns the value of the TuningObjective property for this object.
|
VpcConfig |
vpcConfig()
The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter
tuning job launches to connect to.
|
clone, finalize, getClass, notify, notifyAll, wait, wait, waitcopypublic String definitionName()
The job definition name.
public HyperParameterTuningJobObjective tuningObjective()
public ParameterRanges hyperParameterRanges()
public boolean hasStaticHyperParameters()
public Map<String,String> staticHyperParameters()
Specifies the values of hyperparameters that do not change for the tuning job.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
You can use hasStaticHyperParameters() to see if a value was sent in this field.
public HyperParameterAlgorithmSpecification algorithmSpecification()
The HyperParameterAlgorithmSpecification object that specifies the resource algorithm to use for the training jobs that the tuning job launches.
public String roleArn()
The Amazon Resource Name (ARN) of the IAM role associated with the training jobs that the tuning job launches.
public boolean hasInputDataConfig()
public List<Channel> inputDataConfig()
An array of Channel objects that specify the input for the training jobs that the tuning job launches.
Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
You can use hasInputDataConfig() to see if a value was sent in this field.
public VpcConfig vpcConfig()
The VpcConfig object that specifies the VPC that you want the training jobs that this hyperparameter tuning job launches to connect to. Control access to and from your training container by configuring the VPC. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
public OutputDataConfig outputDataConfig()
Specifies the path to the Amazon S3 bucket where you store model artifacts from the training jobs that the tuning job launches.
public ResourceConfig resourceConfig()
The resources, including the compute instances and storage volumes, to use for the training jobs that the tuning job launches.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage volumes
for scratch space. If you want Amazon SageMaker to use the storage volume to store the training data, choose
File as the TrainingInputMode in the algorithm specification. For distributed training
algorithms, specify an instance count greater than 1.
Storage volumes store model artifacts and incremental states. Training algorithms might also use storage
volumes for scratch space. If you want Amazon SageMaker to use the storage volume to store the training
data, choose File as the TrainingInputMode in the algorithm specification. For
distributed training algorithms, specify an instance count greater than 1.
public StoppingCondition stoppingCondition()
Specifies a limit to how long a model hyperparameter training job can run. It also specifies how long you are willing to wait for a managed spot training job to complete. When the job reaches the a limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.
public Boolean enableNetworkIsolation()
Isolates the training container. No inbound or outbound network calls can be made, except for calls between peers within a training cluster for distributed training. If network isolation is used for training jobs that are configured to use a VPC, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
public Boolean enableInterContainerTrafficEncryption()
To encrypt all communications between ML compute instances in distributed training, choose True.
Encryption provides greater security for distributed training, but training might take longer. How long it takes
depends on the amount of communication between compute instances, especially if you use a deep learning algorithm
in distributed training.
True. Encryption provides greater security for distributed training, but training might take
longer. How long it takes depends on the amount of communication between compute instances, especially if
you use a deep learning algorithm in distributed training.public Boolean enableManagedSpotTraining()
A Boolean indicating whether managed spot training is enabled (True) or not (False).
True) or not (
False).public CheckpointConfig checkpointConfig()
public HyperParameterTrainingJobDefinition.Builder toBuilder()
toBuilder in interface ToCopyableBuilder<HyperParameterTrainingJobDefinition.Builder,HyperParameterTrainingJobDefinition>public static HyperParameterTrainingJobDefinition.Builder builder()
public static Class<? extends HyperParameterTrainingJobDefinition.Builder> serializableBuilderClass()
public boolean equalsBySdkFields(Object obj)
equalsBySdkFields in interface SdkPojopublic String toString()
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