public static interface TrainingJob.Builder extends SdkPojo, CopyableBuilder<TrainingJob.Builder,TrainingJob>
| Modifier and Type | Method and Description |
|---|---|
TrainingJob.Builder |
algorithmSpecification(AlgorithmSpecification algorithmSpecification)
Information about the algorithm used for training, and algorithm metadata.
|
default TrainingJob.Builder |
algorithmSpecification(Consumer<AlgorithmSpecification.Builder> algorithmSpecification)
Information about the algorithm used for training, and algorithm metadata.
|
TrainingJob.Builder |
autoMLJobArn(String autoMLJobArn)
The Amazon Resource Name (ARN) of the job.
|
TrainingJob.Builder |
billableTimeInSeconds(Integer billableTimeInSeconds)
The billable time in seconds.
|
TrainingJob.Builder |
checkpointConfig(CheckpointConfig checkpointConfig)
Sets the value of the CheckpointConfig property for this object.
|
default TrainingJob.Builder |
checkpointConfig(Consumer<CheckpointConfig.Builder> checkpointConfig)
Sets the value of the CheckpointConfig property for this object.
|
TrainingJob.Builder |
creationTime(Instant creationTime)
A timestamp that indicates when the training job was created.
|
default TrainingJob.Builder |
debugHookConfig(Consumer<DebugHookConfig.Builder> debugHookConfig)
Sets the value of the DebugHookConfig property for this object.
|
TrainingJob.Builder |
debugHookConfig(DebugHookConfig debugHookConfig)
Sets the value of the DebugHookConfig property for this object.
|
TrainingJob.Builder |
debugRuleConfigurations(Collection<DebugRuleConfiguration> debugRuleConfigurations)
Information about the debug rule configuration.
|
TrainingJob.Builder |
debugRuleConfigurations(Consumer<DebugRuleConfiguration.Builder>... debugRuleConfigurations)
Information about the debug rule configuration.
|
TrainingJob.Builder |
debugRuleConfigurations(DebugRuleConfiguration... debugRuleConfigurations)
Information about the debug rule configuration.
|
TrainingJob.Builder |
debugRuleEvaluationStatuses(Collection<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses)
Information about the evaluation status of the rules for the training job.
|
TrainingJob.Builder |
debugRuleEvaluationStatuses(Consumer<DebugRuleEvaluationStatus.Builder>... debugRuleEvaluationStatuses)
Information about the evaluation status of the rules for the training job.
|
TrainingJob.Builder |
debugRuleEvaluationStatuses(DebugRuleEvaluationStatus... debugRuleEvaluationStatuses)
Information about the evaluation status of the rules for the training job.
|
TrainingJob.Builder |
enableInterContainerTrafficEncryption(Boolean enableInterContainerTrafficEncryption)
To encrypt all communications between ML compute instances in distributed training, choose
True. |
TrainingJob.Builder |
enableManagedSpotTraining(Boolean enableManagedSpotTraining)
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of
on-demand instances.
|
TrainingJob.Builder |
enableNetworkIsolation(Boolean enableNetworkIsolation)
If the
TrainingJob was created with network isolation, the value is set to true. |
TrainingJob.Builder |
environment(Map<String,String> environment)
The environment variables to set in the Docker container.
|
default TrainingJob.Builder |
experimentConfig(Consumer<ExperimentConfig.Builder> experimentConfig)
Sets the value of the ExperimentConfig property for this object.
|
TrainingJob.Builder |
experimentConfig(ExperimentConfig experimentConfig)
Sets the value of the ExperimentConfig property for this object.
|
TrainingJob.Builder |
failureReason(String failureReason)
If the training job failed, the reason it failed.
|
TrainingJob.Builder |
finalMetricDataList(Collection<MetricData> finalMetricDataList)
A list of final metric values that are set when the training job completes.
|
TrainingJob.Builder |
finalMetricDataList(Consumer<MetricData.Builder>... finalMetricDataList)
A list of final metric values that are set when the training job completes.
|
TrainingJob.Builder |
finalMetricDataList(MetricData... finalMetricDataList)
A list of final metric values that are set when the training job completes.
|
TrainingJob.Builder |
hyperParameters(Map<String,String> hyperParameters)
Algorithm-specific parameters.
|
TrainingJob.Builder |
inputDataConfig(Channel... inputDataConfig)
An array of
Channel objects that describes each data input channel. |
TrainingJob.Builder |
inputDataConfig(Collection<Channel> inputDataConfig)
An array of
Channel objects that describes each data input channel. |
TrainingJob.Builder |
inputDataConfig(Consumer<Channel.Builder>... inputDataConfig)
An array of
Channel objects that describes each data input channel. |
TrainingJob.Builder |
labelingJobArn(String labelingJobArn)
The Amazon Resource Name (ARN) of the labeling job.
|
TrainingJob.Builder |
lastModifiedTime(Instant lastModifiedTime)
A timestamp that indicates when the status of the training job was last modified.
|
default TrainingJob.Builder |
modelArtifacts(Consumer<ModelArtifacts.Builder> modelArtifacts)
Information about the Amazon S3 location that is configured for storing model artifacts.
|
TrainingJob.Builder |
modelArtifacts(ModelArtifacts modelArtifacts)
Information about the Amazon S3 location that is configured for storing model artifacts.
|
default TrainingJob.Builder |
outputDataConfig(Consumer<OutputDataConfig.Builder> outputDataConfig)
The S3 path where model artifacts that you configured when creating the job are stored.
|
TrainingJob.Builder |
outputDataConfig(OutputDataConfig outputDataConfig)
The S3 path where model artifacts that you configured when creating the job are stored.
|
default TrainingJob.Builder |
resourceConfig(Consumer<ResourceConfig.Builder> resourceConfig)
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
|
TrainingJob.Builder |
resourceConfig(ResourceConfig resourceConfig)
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
|
default TrainingJob.Builder |
retryStrategy(Consumer<RetryStrategy.Builder> retryStrategy)
The number of times to retry the job when the job fails due to an
InternalServerError. |
TrainingJob.Builder |
retryStrategy(RetryStrategy retryStrategy)
The number of times to retry the job when the job fails due to an
InternalServerError. |
TrainingJob.Builder |
roleArn(String roleArn)
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
|
TrainingJob.Builder |
secondaryStatus(SecondaryStatus secondaryStatus)
Provides detailed information about the state of the training job.
|
TrainingJob.Builder |
secondaryStatus(String secondaryStatus)
Provides detailed information about the state of the training job.
|
TrainingJob.Builder |
secondaryStatusTransitions(Collection<SecondaryStatusTransition> secondaryStatusTransitions)
A history of all of the secondary statuses that the training job has transitioned through.
|
TrainingJob.Builder |
secondaryStatusTransitions(Consumer<SecondaryStatusTransition.Builder>... secondaryStatusTransitions)
A history of all of the secondary statuses that the training job has transitioned through.
|
TrainingJob.Builder |
secondaryStatusTransitions(SecondaryStatusTransition... secondaryStatusTransitions)
A history of all of the secondary statuses that the training job has transitioned through.
|
default TrainingJob.Builder |
stoppingCondition(Consumer<StoppingCondition.Builder> stoppingCondition)
Specifies a limit to how long a model training job can run.
|
TrainingJob.Builder |
stoppingCondition(StoppingCondition stoppingCondition)
Specifies a limit to how long a model training job can run.
|
TrainingJob.Builder |
tags(Collection<Tag> tags)
An array of key-value pairs.
|
TrainingJob.Builder |
tags(Consumer<Tag.Builder>... tags)
An array of key-value pairs.
|
TrainingJob.Builder |
tags(Tag... tags)
An array of key-value pairs.
|
default TrainingJob.Builder |
tensorBoardOutputConfig(Consumer<TensorBoardOutputConfig.Builder> tensorBoardOutputConfig)
Sets the value of the TensorBoardOutputConfig property for this object.
|
TrainingJob.Builder |
tensorBoardOutputConfig(TensorBoardOutputConfig tensorBoardOutputConfig)
Sets the value of the TensorBoardOutputConfig property for this object.
|
TrainingJob.Builder |
trainingEndTime(Instant trainingEndTime)
Indicates the time when the training job ends on training instances.
|
TrainingJob.Builder |
trainingJobArn(String trainingJobArn)
The Amazon Resource Name (ARN) of the training job.
|
TrainingJob.Builder |
trainingJobName(String trainingJobName)
The name of the training job.
|
TrainingJob.Builder |
trainingJobStatus(String trainingJobStatus)
The status of the training job.
|
TrainingJob.Builder |
trainingJobStatus(TrainingJobStatus trainingJobStatus)
The status of the training job.
|
TrainingJob.Builder |
trainingStartTime(Instant trainingStartTime)
Indicates the time when the training job starts on training instances.
|
TrainingJob.Builder |
trainingTimeInSeconds(Integer trainingTimeInSeconds)
The training time in seconds.
|
TrainingJob.Builder |
tuningJobArn(String tuningJobArn)
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched
by a hyperparameter tuning job.
|
default TrainingJob.Builder |
vpcConfig(Consumer<VpcConfig.Builder> vpcConfig)
A VpcConfig object that specifies the VPC that this training job has access to.
|
TrainingJob.Builder |
vpcConfig(VpcConfig vpcConfig)
A VpcConfig object that specifies the VPC that this training job has access to.
|
equalsBySdkFields, sdkFieldscopyapplyMutation, buildTrainingJob.Builder trainingJobName(String trainingJobName)
The name of the training job.
trainingJobName - The name of the training job.TrainingJob.Builder trainingJobArn(String trainingJobArn)
The Amazon Resource Name (ARN) of the training job.
trainingJobArn - The Amazon Resource Name (ARN) of the training job.TrainingJob.Builder tuningJobArn(String tuningJobArn)
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
tuningJobArn - The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was
launched by a hyperparameter tuning job.TrainingJob.Builder labelingJobArn(String labelingJobArn)
The Amazon Resource Name (ARN) of the labeling job.
labelingJobArn - The Amazon Resource Name (ARN) of the labeling job.TrainingJob.Builder autoMLJobArn(String autoMLJobArn)
The Amazon Resource Name (ARN) of the job.
autoMLJobArn - The Amazon Resource Name (ARN) of the job.TrainingJob.Builder modelArtifacts(ModelArtifacts modelArtifacts)
Information about the Amazon S3 location that is configured for storing model artifacts.
modelArtifacts - Information about the Amazon S3 location that is configured for storing model artifacts.default TrainingJob.Builder modelArtifacts(Consumer<ModelArtifacts.Builder> modelArtifacts)
Information about the Amazon S3 location that is configured for storing model artifacts.
This is a convenience method that creates an instance of theModelArtifacts.Builder avoiding the need
to create one manually via ModelArtifacts.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to modelArtifacts(ModelArtifacts).
modelArtifacts - a consumer that will call methods on ModelArtifacts.BuildermodelArtifacts(ModelArtifacts)TrainingJob.Builder trainingJobStatus(String trainingJobStatus)
The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
trainingJobStatus - The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
TrainingJobStatus,
TrainingJobStatusTrainingJob.Builder trainingJobStatus(TrainingJobStatus trainingJobStatus)
The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
trainingJobStatus - The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
TrainingJobStatus,
TrainingJobStatusTrainingJob.Builder secondaryStatus(String secondaryStatus)
Provides detailed information about the state of the training job. For detailed information about the
secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input
mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
secondaryStatus - Provides detailed information about the state of the training job. For detailed information about the
secondary status of the training job, see StatusMessage under
SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training
input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3
location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
SecondaryStatus,
SecondaryStatusTrainingJob.Builder secondaryStatus(SecondaryStatus secondaryStatus)
Provides detailed information about the state of the training job. For detailed information about the
secondary status of the training job, see StatusMessage under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input
mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
secondaryStatus - Provides detailed information about the state of the training job. For detailed information about the
secondary status of the training job, see StatusMessage under
SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training
input mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3
location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
SecondaryStatus,
SecondaryStatusTrainingJob.Builder failureReason(String failureReason)
If the training job failed, the reason it failed.
failureReason - If the training job failed, the reason it failed.TrainingJob.Builder hyperParameters(Map<String,String> hyperParameters)
Algorithm-specific parameters.
hyperParameters - Algorithm-specific parameters.TrainingJob.Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification)
Information about the algorithm used for training, and algorithm metadata.
algorithmSpecification - Information about the algorithm used for training, and algorithm metadata.default TrainingJob.Builder algorithmSpecification(Consumer<AlgorithmSpecification.Builder> algorithmSpecification)
Information about the algorithm used for training, and algorithm metadata.
This is a convenience method that creates an instance of theAlgorithmSpecification.Builder avoiding
the need to create one manually via AlgorithmSpecification.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and
its result is passed to algorithmSpecification(AlgorithmSpecification).
algorithmSpecification - a consumer that will call methods on AlgorithmSpecification.BuilderalgorithmSpecification(AlgorithmSpecification)TrainingJob.Builder roleArn(String roleArn)
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
roleArn - The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.TrainingJob.Builder inputDataConfig(Collection<Channel> inputDataConfig)
An array of Channel objects that describes each data input channel.
inputDataConfig - An array of Channel objects that describes each data input channel.TrainingJob.Builder inputDataConfig(Channel... inputDataConfig)
An array of Channel objects that describes each data input channel.
inputDataConfig - An array of Channel objects that describes each data input channel.TrainingJob.Builder inputDataConfig(Consumer<Channel.Builder>... inputDataConfig)
An array of Channel objects that describes each data input channel.
Channel.Builder avoiding the need to create one
manually via Channel.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately and its
result is passed to #inputDataConfig(List.
inputDataConfig - a consumer that will call methods on
Channel.Builder#inputDataConfig(java.util.Collection) TrainingJob.Builder outputDataConfig(OutputDataConfig outputDataConfig)
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
outputDataConfig - The S3 path where model artifacts that you configured when creating the job are stored. SageMaker
creates subfolders for model artifacts.default TrainingJob.Builder outputDataConfig(Consumer<OutputDataConfig.Builder> outputDataConfig)
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
This is a convenience method that creates an instance of theOutputDataConfig.Builder avoiding the
need to create one manually via OutputDataConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to outputDataConfig(OutputDataConfig).
outputDataConfig - a consumer that will call methods on OutputDataConfig.BuilderoutputDataConfig(OutputDataConfig)TrainingJob.Builder resourceConfig(ResourceConfig resourceConfig)
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
resourceConfig - Resources, including ML compute instances and ML storage volumes, that are configured for model
training.default TrainingJob.Builder resourceConfig(Consumer<ResourceConfig.Builder> resourceConfig)
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
This is a convenience method that creates an instance of theResourceConfig.Builder avoiding the need
to create one manually via ResourceConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to resourceConfig(ResourceConfig).
resourceConfig - a consumer that will call methods on ResourceConfig.BuilderresourceConfig(ResourceConfig)TrainingJob.Builder vpcConfig(VpcConfig vpcConfig)
A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
vpcConfig - A VpcConfig object that specifies the VPC that this training job has access to. For more
information, see Protect
Training Jobs by Using an Amazon Virtual Private Cloud.default TrainingJob.Builder vpcConfig(Consumer<VpcConfig.Builder> vpcConfig)
A VpcConfig object that specifies the VPC that this training job has access to. For more information, see Protect Training Jobs by Using an Amazon Virtual Private Cloud.
This is a convenience method that creates an instance of theVpcConfig.Builder avoiding the need to
create one manually via VpcConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its result
is passed to vpcConfig(VpcConfig).
vpcConfig - a consumer that will call methods on VpcConfig.BuildervpcConfig(VpcConfig)TrainingJob.Builder stoppingCondition(StoppingCondition stoppingCondition)
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination
for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of
training are not lost.
stoppingCondition - Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot
training job has to complete. When the job reaches the time limit, SageMaker ends the training job.
Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job
termination for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so
the results of training are not lost.
default TrainingJob.Builder stoppingCondition(Consumer<StoppingCondition.Builder> stoppingCondition)
Specifies a limit to how long a model training job can run. It also specifies how long a managed Spot training job has to complete. When the job reaches the time limit, SageMaker ends the training job. Use this API to cap model training costs.
To stop a job, SageMaker sends the algorithm the SIGTERM signal, which delays job termination
for 120 seconds. Algorithms can use this 120-second window to save the model artifacts, so the results of
training are not lost.
StoppingCondition.Builder avoiding the
need to create one manually via StoppingCondition.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to stoppingCondition(StoppingCondition).
stoppingCondition - a consumer that will call methods on StoppingCondition.BuilderstoppingCondition(StoppingCondition)TrainingJob.Builder creationTime(Instant creationTime)
A timestamp that indicates when the training job was created.
creationTime - A timestamp that indicates when the training job was created.TrainingJob.Builder trainingStartTime(Instant trainingStartTime)
Indicates the time when the training job starts on training instances. You are billed for the time interval
between this time and the value of TrainingEndTime. The start time in CloudWatch Logs might be
later than this time. The difference is due to the time it takes to download the training data and to the
size of the training container.
trainingStartTime - Indicates the time when the training job starts on training instances. You are billed for the time
interval between this time and the value of TrainingEndTime. The start time in CloudWatch
Logs might be later than this time. The difference is due to the time it takes to download the
training data and to the size of the training container.TrainingJob.Builder trainingEndTime(Instant trainingEndTime)
Indicates the time when the training job ends on training instances. You are billed for the time interval
between the value of TrainingStartTime and this time. For successful jobs and stopped jobs, this
is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a
job failure.
trainingEndTime - Indicates the time when the training job ends on training instances. You are billed for the time
interval between the value of TrainingStartTime and this time. For successful jobs and
stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time
when SageMaker detects a job failure.TrainingJob.Builder lastModifiedTime(Instant lastModifiedTime)
A timestamp that indicates when the status of the training job was last modified.
lastModifiedTime - A timestamp that indicates when the status of the training job was last modified.TrainingJob.Builder secondaryStatusTransitions(Collection<SecondaryStatusTransition> secondaryStatusTransitions)
A history of all of the secondary statuses that the training job has transitioned through.
secondaryStatusTransitions - A history of all of the secondary statuses that the training job has transitioned through.TrainingJob.Builder secondaryStatusTransitions(SecondaryStatusTransition... secondaryStatusTransitions)
A history of all of the secondary statuses that the training job has transitioned through.
secondaryStatusTransitions - A history of all of the secondary statuses that the training job has transitioned through.TrainingJob.Builder secondaryStatusTransitions(Consumer<SecondaryStatusTransition.Builder>... secondaryStatusTransitions)
A history of all of the secondary statuses that the training job has transitioned through.
This is a convenience method that creates an instance of theSecondaryStatusTransition.Builder avoiding the need
to create one manually via
SecondaryStatusTransition.builder().
When the Consumer completes,
SdkBuilder.build() is called
immediately and its result is passed to #secondaryStatusTransitions(List.
secondaryStatusTransitions - a consumer that will call methods on
SecondaryStatusTransition.Builder#secondaryStatusTransitions(java.util.Collection) TrainingJob.Builder finalMetricDataList(Collection<MetricData> finalMetricDataList)
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
finalMetricDataList - A list of final metric values that are set when the training job completes. Used only if the training
job was configured to use metrics.TrainingJob.Builder finalMetricDataList(MetricData... finalMetricDataList)
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
finalMetricDataList - A list of final metric values that are set when the training job completes. Used only if the training
job was configured to use metrics.TrainingJob.Builder finalMetricDataList(Consumer<MetricData.Builder>... finalMetricDataList)
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
This is a convenience method that creates an instance of theMetricData.Builder avoiding the need to create one
manually via MetricData.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately and
its result is passed to #finalMetricDataList(List.
finalMetricDataList - a consumer that will call methods on
MetricData.Builder#finalMetricDataList(java.util.Collection) TrainingJob.Builder enableNetworkIsolation(Boolean enableNetworkIsolation)
If the TrainingJob was created with network isolation, the value is set to true. If
network isolation is enabled, nodes can't communicate beyond the VPC they run in.
enableNetworkIsolation - If the TrainingJob was created with network isolation, the value is set to
true. If network isolation is enabled, nodes can't communicate beyond the VPC they run
in.TrainingJob.Builder enableInterContainerTrafficEncryption(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.
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.TrainingJob.Builder enableManagedSpotTraining(Boolean enableManagedSpotTraining)
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
enableManagedSpotTraining - When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead
of on-demand instances. For more information, see Managed Spot
Training.TrainingJob.Builder checkpointConfig(CheckpointConfig checkpointConfig)
checkpointConfig - The new value for the CheckpointConfig property for this object.default TrainingJob.Builder checkpointConfig(Consumer<CheckpointConfig.Builder> checkpointConfig)
CheckpointConfig.Builder avoiding the
need to create one manually via CheckpointConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to checkpointConfig(CheckpointConfig).
checkpointConfig - a consumer that will call methods on CheckpointConfig.BuildercheckpointConfig(CheckpointConfig)TrainingJob.Builder trainingTimeInSeconds(Integer trainingTimeInSeconds)
The training time in seconds.
trainingTimeInSeconds - The training time in seconds.TrainingJob.Builder billableTimeInSeconds(Integer billableTimeInSeconds)
The billable time in seconds.
billableTimeInSeconds - The billable time in seconds.TrainingJob.Builder debugHookConfig(DebugHookConfig debugHookConfig)
debugHookConfig - The new value for the DebugHookConfig property for this object.default TrainingJob.Builder debugHookConfig(Consumer<DebugHookConfig.Builder> debugHookConfig)
DebugHookConfig.Builder avoiding the
need to create one manually via DebugHookConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to debugHookConfig(DebugHookConfig).
debugHookConfig - a consumer that will call methods on DebugHookConfig.BuilderdebugHookConfig(DebugHookConfig)TrainingJob.Builder experimentConfig(ExperimentConfig experimentConfig)
experimentConfig - The new value for the ExperimentConfig property for this object.default TrainingJob.Builder experimentConfig(Consumer<ExperimentConfig.Builder> experimentConfig)
ExperimentConfig.Builder avoiding the
need to create one manually via ExperimentConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to experimentConfig(ExperimentConfig).
experimentConfig - a consumer that will call methods on ExperimentConfig.BuilderexperimentConfig(ExperimentConfig)TrainingJob.Builder debugRuleConfigurations(Collection<DebugRuleConfiguration> debugRuleConfigurations)
Information about the debug rule configuration.
debugRuleConfigurations - Information about the debug rule configuration.TrainingJob.Builder debugRuleConfigurations(DebugRuleConfiguration... debugRuleConfigurations)
Information about the debug rule configuration.
debugRuleConfigurations - Information about the debug rule configuration.TrainingJob.Builder debugRuleConfigurations(Consumer<DebugRuleConfiguration.Builder>... debugRuleConfigurations)
Information about the debug rule configuration.
This is a convenience method that creates an instance of theDebugRuleConfiguration.Builder avoiding the need to
create one manually via
DebugRuleConfiguration.builder().
When the Consumer completes,
SdkBuilder.build() is called
immediately and its result is passed to #debugRuleConfigurations(List.
debugRuleConfigurations - a consumer that will call methods on
DebugRuleConfiguration.Builder#debugRuleConfigurations(java.util.Collection) TrainingJob.Builder tensorBoardOutputConfig(TensorBoardOutputConfig tensorBoardOutputConfig)
tensorBoardOutputConfig - The new value for the TensorBoardOutputConfig property for this object.default TrainingJob.Builder tensorBoardOutputConfig(Consumer<TensorBoardOutputConfig.Builder> tensorBoardOutputConfig)
TensorBoardOutputConfig.Builder avoiding
the need to create one manually via TensorBoardOutputConfig.builder().
When the Consumer completes, SdkBuilder.build() is called immediately
and its result is passed to tensorBoardOutputConfig(TensorBoardOutputConfig).
tensorBoardOutputConfig - a consumer that will call methods on TensorBoardOutputConfig.BuildertensorBoardOutputConfig(TensorBoardOutputConfig)TrainingJob.Builder debugRuleEvaluationStatuses(Collection<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses)
Information about the evaluation status of the rules for the training job.
debugRuleEvaluationStatuses - Information about the evaluation status of the rules for the training job.TrainingJob.Builder debugRuleEvaluationStatuses(DebugRuleEvaluationStatus... debugRuleEvaluationStatuses)
Information about the evaluation status of the rules for the training job.
debugRuleEvaluationStatuses - Information about the evaluation status of the rules for the training job.TrainingJob.Builder debugRuleEvaluationStatuses(Consumer<DebugRuleEvaluationStatus.Builder>... debugRuleEvaluationStatuses)
Information about the evaluation status of the rules for the training job.
This is a convenience method that creates an instance of theDebugRuleEvaluationStatus.Builder avoiding the need
to create one manually via
DebugRuleEvaluationStatus.builder().
When the Consumer completes,
SdkBuilder.build() is called
immediately and its result is passed to #debugRuleEvaluationStatuses(List.
debugRuleEvaluationStatuses - a consumer that will call methods on
DebugRuleEvaluationStatus.Builder#debugRuleEvaluationStatuses(java.util.Collection) TrainingJob.Builder environment(Map<String,String> environment)
The environment variables to set in the Docker container.
environment - The environment variables to set in the Docker container.TrainingJob.Builder retryStrategy(RetryStrategy retryStrategy)
The number of times to retry the job when the job fails due to an InternalServerError.
retryStrategy - The number of times to retry the job when the job fails due to an InternalServerError.default TrainingJob.Builder retryStrategy(Consumer<RetryStrategy.Builder> retryStrategy)
The number of times to retry the job when the job fails due to an InternalServerError.
RetryStrategy.Builder avoiding the need
to create one manually via RetryStrategy.builder().
When the Consumer completes, SdkBuilder.build() is called immediately and its
result is passed to retryStrategy(RetryStrategy).
retryStrategy - a consumer that will call methods on RetryStrategy.BuilderretryStrategy(RetryStrategy)TrainingJob.Builder tags(Collection<Tag> tags)
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
tags - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in
different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
Resources.TrainingJob.Builder tags(Tag... tags)
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
tags - An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in
different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services
Resources.TrainingJob.Builder tags(Consumer<Tag.Builder>... tags)
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
This is a convenience method that creates an instance of theTag.Builder avoiding the need to create one manually
via Tag.builder().
When the Consumer completes,
SdkBuilder.build() is called immediately and its
result is passed to #tags(List.
tags - a consumer that will call methods on
Tag.Builder#tags(java.util.Collection) Copyright © 2022. All rights reserved.