Interface DescribeTrainingJobResponse.Builder
- All Superinterfaces:
AwsResponse.Builder
,Buildable
,CopyableBuilder<DescribeTrainingJobResponse.Builder,
,DescribeTrainingJobResponse> SageMakerResponse.Builder
,SdkBuilder<DescribeTrainingJobResponse.Builder,
,DescribeTrainingJobResponse> SdkPojo
,SdkResponse.Builder
- Enclosing class:
DescribeTrainingJobResponse
-
Method Summary
Modifier and TypeMethodDescriptionalgorithmSpecification
(Consumer<AlgorithmSpecification.Builder> algorithmSpecification) Information about the algorithm used for training, and algorithm metadata.algorithmSpecification
(AlgorithmSpecification algorithmSpecification) Information about the algorithm used for training, and algorithm metadata.autoMLJobArn
(String autoMLJobArn) The Amazon Resource Name (ARN) of an AutoML job.billableTimeInSeconds
(Integer billableTimeInSeconds) The billable time in seconds.checkpointConfig
(Consumer<CheckpointConfig.Builder> checkpointConfig) Sets the value of the CheckpointConfig property for this object.checkpointConfig
(CheckpointConfig checkpointConfig) Sets the value of the CheckpointConfig property for this object.creationTime
(Instant creationTime) A timestamp that indicates when the training job was created.debugHookConfig
(Consumer<DebugHookConfig.Builder> debugHookConfig) Sets the value of the DebugHookConfig property for this object.debugHookConfig
(DebugHookConfig debugHookConfig) Sets the value of the DebugHookConfig property for this object.debugRuleConfigurations
(Collection<DebugRuleConfiguration> debugRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.debugRuleConfigurations
(Consumer<DebugRuleConfiguration.Builder>... debugRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.debugRuleConfigurations
(DebugRuleConfiguration... debugRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.debugRuleEvaluationStatuses
(Collection<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.debugRuleEvaluationStatuses
(Consumer<DebugRuleEvaluationStatus.Builder>... debugRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.debugRuleEvaluationStatuses
(DebugRuleEvaluationStatus... debugRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.enableInterContainerTrafficEncryption
(Boolean enableInterContainerTrafficEncryption) To encrypt all communications between ML compute instances in distributed training, chooseTrue
.enableManagedSpotTraining
(Boolean enableManagedSpotTraining) A Boolean indicating whether managed spot training is enabled (True
) or not (False
).enableNetworkIsolation
(Boolean enableNetworkIsolation) If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, chooseTrue
.environment
(Map<String, String> environment) The environment variables to set in the Docker container.experimentConfig
(Consumer<ExperimentConfig.Builder> experimentConfig) Sets the value of the ExperimentConfig property for this object.experimentConfig
(ExperimentConfig experimentConfig) Sets the value of the ExperimentConfig property for this object.failureReason
(String failureReason) If the training job failed, the reason it failed.finalMetricDataList
(Collection<MetricData> finalMetricDataList) A collection ofMetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.finalMetricDataList
(Consumer<MetricData.Builder>... finalMetricDataList) A collection ofMetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.finalMetricDataList
(MetricData... finalMetricDataList) A collection ofMetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.hyperParameters
(Map<String, String> hyperParameters) Algorithm-specific parameters.infraCheckConfig
(Consumer<InfraCheckConfig.Builder> infraCheckConfig) Contains information about the infrastructure health check configuration for the training job.infraCheckConfig
(InfraCheckConfig infraCheckConfig) Contains information about the infrastructure health check configuration for the training job.inputDataConfig
(Collection<Channel> inputDataConfig) An array ofChannel
objects that describes each data input channel.inputDataConfig
(Consumer<Channel.Builder>... inputDataConfig) An array ofChannel
objects that describes each data input channel.inputDataConfig
(Channel... inputDataConfig) An array ofChannel
objects that describes each data input channel.labelingJobArn
(String labelingJobArn) The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.lastModifiedTime
(Instant lastModifiedTime) A timestamp that indicates when the status of the training job was last modified.modelArtifacts
(Consumer<ModelArtifacts.Builder> modelArtifacts) Information about the Amazon S3 location that is configured for storing model artifacts.modelArtifacts
(ModelArtifacts modelArtifacts) Information about the Amazon S3 location that is configured for storing model artifacts.outputDataConfig
(Consumer<OutputDataConfig.Builder> outputDataConfig) The S3 path where model artifacts that you configured when creating the job are stored.outputDataConfig
(OutputDataConfig outputDataConfig) The S3 path where model artifacts that you configured when creating the job are stored.profilerConfig
(Consumer<ProfilerConfig.Builder> profilerConfig) Sets the value of the ProfilerConfig property for this object.profilerConfig
(ProfilerConfig profilerConfig) Sets the value of the ProfilerConfig property for this object.profilerRuleConfigurations
(Collection<ProfilerRuleConfiguration> profilerRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.profilerRuleConfigurations
(Consumer<ProfilerRuleConfiguration.Builder>... profilerRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.profilerRuleConfigurations
(ProfilerRuleConfiguration... profilerRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.profilerRuleEvaluationStatuses
(Collection<ProfilerRuleEvaluationStatus> profilerRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.profilerRuleEvaluationStatuses
(Consumer<ProfilerRuleEvaluationStatus.Builder>... profilerRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.profilerRuleEvaluationStatuses
(ProfilerRuleEvaluationStatus... profilerRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.profilingStatus
(String profilingStatus) Profiling status of a training job.profilingStatus
(ProfilingStatus profilingStatus) Profiling status of a training job.remoteDebugConfig
(Consumer<RemoteDebugConfig.Builder> remoteDebugConfig) Configuration for remote debugging.remoteDebugConfig
(RemoteDebugConfig remoteDebugConfig) Configuration for remote debugging.resourceConfig
(Consumer<ResourceConfig.Builder> resourceConfig) Resources, including ML compute instances and ML storage volumes, that are configured for model training.resourceConfig
(ResourceConfig resourceConfig) Resources, including ML compute instances and ML storage volumes, that are configured for model training.retryStrategy
(Consumer<RetryStrategy.Builder> retryStrategy) The number of times to retry the job when the job fails due to anInternalServerError
.retryStrategy
(RetryStrategy retryStrategy) The number of times to retry the job when the job fails due to anInternalServerError
.The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.secondaryStatus
(String secondaryStatus) Provides detailed information about the state of the training job.secondaryStatus
(SecondaryStatus secondaryStatus) Provides detailed information about the state of the training job.secondaryStatusTransitions
(Collection<SecondaryStatusTransition> secondaryStatusTransitions) A history of all of the secondary statuses that the training job has transitioned through.secondaryStatusTransitions
(Consumer<SecondaryStatusTransition.Builder>... secondaryStatusTransitions) A history of all of the secondary statuses that the training job has transitioned through.secondaryStatusTransitions
(SecondaryStatusTransition... secondaryStatusTransitions) A history of all of the secondary statuses that the training job has transitioned through.stoppingCondition
(Consumer<StoppingCondition.Builder> stoppingCondition) Specifies a limit to how long a model training job can run.stoppingCondition
(StoppingCondition stoppingCondition) Specifies a limit to how long a model training job can run.tensorBoardOutputConfig
(Consumer<TensorBoardOutputConfig.Builder> tensorBoardOutputConfig) Sets the value of the TensorBoardOutputConfig property for this object.tensorBoardOutputConfig
(TensorBoardOutputConfig tensorBoardOutputConfig) Sets the value of the TensorBoardOutputConfig property for this object.trainingEndTime
(Instant trainingEndTime) Indicates the time when the training job ends on training instances.trainingJobArn
(String trainingJobArn) The Amazon Resource Name (ARN) of the training job.trainingJobName
(String trainingJobName) Name of the model training job.trainingJobStatus
(String trainingJobStatus) The status of the training job.trainingJobStatus
(TrainingJobStatus trainingJobStatus) The status of the training job.trainingStartTime
(Instant trainingStartTime) Indicates the time when the training job starts on training instances.trainingTimeInSeconds
(Integer trainingTimeInSeconds) The training time in seconds.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.vpcConfig
(Consumer<VpcConfig.Builder> vpcConfig) A VpcConfig object that specifies the VPC that this training job has access to.A VpcConfig object that specifies the VPC that this training job has access to.warmPoolStatus
(Consumer<WarmPoolStatus.Builder> warmPoolStatus) The status of the warm pool associated with the training job.warmPoolStatus
(WarmPoolStatus warmPoolStatus) The status of the warm pool associated with the training job.Methods inherited from interface software.amazon.awssdk.utils.builder.CopyableBuilder
copy
Methods inherited from interface software.amazon.awssdk.services.sagemaker.model.SageMakerResponse.Builder
build, responseMetadata, responseMetadata
Methods inherited from interface software.amazon.awssdk.utils.builder.SdkBuilder
applyMutation, build
Methods inherited from interface software.amazon.awssdk.core.SdkPojo
equalsBySdkFields, sdkFields
Methods inherited from interface software.amazon.awssdk.core.SdkResponse.Builder
sdkHttpResponse, sdkHttpResponse
-
Method Details
-
trainingJobName
Name of the model training job.
- Parameters:
trainingJobName
- Name of the model training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
trainingJobArn
The Amazon Resource Name (ARN) of the training job.
- Parameters:
trainingJobArn
- The Amazon Resource Name (ARN) of the training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tuningJobArn
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
- Parameters:
tuningJobArn
- The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
labelingJobArn
The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
- Parameters:
labelingJobArn
- The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
autoMLJobArn
The Amazon Resource Name (ARN) of an AutoML job.
- Parameters:
autoMLJobArn
- The Amazon Resource Name (ARN) of an AutoML job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
modelArtifacts
Information about the Amazon S3 location that is configured for storing model artifacts.
- Parameters:
modelArtifacts
- Information about the Amazon S3 location that is configured for storing model artifacts.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
modelArtifacts
default DescribeTrainingJobResponse.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 viaModelArtifacts.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tomodelArtifacts(ModelArtifacts)
.- Parameters:
modelArtifacts
- a consumer that will call methods onModelArtifacts.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
trainingJobStatus
The status of the training job.
SageMaker provides the following training job statuses:
-
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 theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
.- Parameters:
trainingJobStatus
- The status of the training job.SageMaker provides the following training job statuses:
-
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 theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
.-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
-
trainingJobStatus
The status of the training job.
SageMaker provides the following training job statuses:
-
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 theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
.- Parameters:
trainingJobStatus
- The status of the training job.SageMaker provides the following training job statuses:
-
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 theFailureReason
field in the response to aDescribeTrainingJobResponse
call. -
Stopping
- The training job is stopping. -
Stopped
- The training job has stopped.
For more detailed information, see
SecondaryStatus
.-
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
-
secondaryStatus
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Interrupted
- The job stopped because the managed spot training instances were interrupted. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTraining
-
DownloadingTrainingImage
- Parameters:
secondaryStatus
- Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, seeStatusMessage
under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Interrupted
- The job stopped because the managed spot training instances were interrupted. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTraining
-
DownloadingTrainingImage
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
secondaryStatus
Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Interrupted
- The job stopped because the managed spot training instances were interrupted. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTraining
-
DownloadingTrainingImage
- Parameters:
secondaryStatus
- Provides detailed information about the state of the training job. For detailed information on the secondary status of the training job, seeStatusMessage
under SecondaryStatusTransition.SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
-
-
Starting
- Starting the training job. -
Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes. -
Training
- Training is in progress. -
Interrupted
- The job stopped because the managed spot training instances were interrupted. -
Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
-
- Completed
-
-
Completed
- The training job has completed.
-
- Failed
-
-
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
.
-
- Stopped
-
-
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime. -
MaxWaitTimeExceeded
- The job stopped because it exceeded the maximum allowed wait time. -
Stopped
- The training job has stopped.
-
- Stopping
-
-
Stopping
- Stopping the training job.
-
Valid values for
SecondaryStatus
are subject to change.We no longer support the following secondary statuses:
-
LaunchingMLInstances
-
PreparingTraining
-
DownloadingTrainingImage
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
failureReason
If the training job failed, the reason it failed.
- Parameters:
failureReason
- If the training job failed, the reason it failed.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
hyperParameters
Algorithm-specific parameters.
- Parameters:
hyperParameters
- Algorithm-specific parameters.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
algorithmSpecification
DescribeTrainingJobResponse.Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification) Information about the algorithm used for training, and algorithm metadata.
- Parameters:
algorithmSpecification
- Information about the algorithm used for training, and algorithm metadata.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
algorithmSpecification
default DescribeTrainingJobResponse.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 viaAlgorithmSpecification.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toalgorithmSpecification(AlgorithmSpecification)
.- Parameters:
algorithmSpecification
- a consumer that will call methods onAlgorithmSpecification.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
roleArn
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
- Parameters:
roleArn
- The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
inputDataConfig
An array of
Channel
objects that describes each data input channel.- Parameters:
inputDataConfig
- An array ofChannel
objects that describes each data input channel.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
inputDataConfig
An array of
Channel
objects that describes each data input channel.- Parameters:
inputDataConfig
- An array ofChannel
objects that describes each data input channel.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
inputDataConfig
An array of
This is a convenience method that creates an instance of theChannel
objects that describes each data input channel.Channel.Builder
avoiding the need to create one manually viaChannel.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toinputDataConfig(List<Channel>)
.- Parameters:
inputDataConfig
- a consumer that will call methods onChannel.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
outputDataConfig
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
- Parameters:
outputDataConfig
- The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
outputDataConfig
default DescribeTrainingJobResponse.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 viaOutputDataConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tooutputDataConfig(OutputDataConfig)
.- Parameters:
outputDataConfig
- a consumer that will call methods onOutputDataConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
resourceConfig
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
- Parameters:
resourceConfig
- Resources, including ML compute instances and ML storage volumes, that are configured for model training.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
resourceConfig
default DescribeTrainingJobResponse.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 viaResourceConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toresourceConfig(ResourceConfig)
.- Parameters:
resourceConfig
- a consumer that will call methods onResourceConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
warmPoolStatus
The status of the warm pool associated with the training job.
- Parameters:
warmPoolStatus
- The status of the warm pool associated with the training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
warmPoolStatus
default DescribeTrainingJobResponse.Builder warmPoolStatus(Consumer<WarmPoolStatus.Builder> warmPoolStatus) The status of the warm pool associated with the training job.
This is a convenience method that creates an instance of theWarmPoolStatus.Builder
avoiding the need to create one manually viaWarmPoolStatus.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed towarmPoolStatus(WarmPoolStatus)
.- Parameters:
warmPoolStatus
- a consumer that will call methods onWarmPoolStatus.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
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.
- Parameters:
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.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
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 viaVpcConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tovpcConfig(VpcConfig)
.- Parameters:
vpcConfig
- a consumer that will call methods onVpcConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
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.- Parameters:
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.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
stoppingCondition
default DescribeTrainingJobResponse.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
This is a convenience method that creates an instance of theSIGTERM
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 viaStoppingCondition.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tostoppingCondition(StoppingCondition)
.- Parameters:
stoppingCondition
- a consumer that will call methods onStoppingCondition.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
creationTime
A timestamp that indicates when the training job was created.
- Parameters:
creationTime
- A timestamp that indicates when the training job was created.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
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.- Parameters:
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 ofTrainingEndTime
. 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.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
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.- Parameters:
trainingEndTime
- Indicates the time when the training job ends on training instances. You are billed for the time interval between the value ofTrainingStartTime
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.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
lastModifiedTime
A timestamp that indicates when the status of the training job was last modified.
- Parameters:
lastModifiedTime
- A timestamp that indicates when the status of the training job was last modified.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
secondaryStatusTransitions
DescribeTrainingJobResponse.Builder secondaryStatusTransitions(Collection<SecondaryStatusTransition> secondaryStatusTransitions) A history of all of the secondary statuses that the training job has transitioned through.
- Parameters:
secondaryStatusTransitions
- A history of all of the secondary statuses that the training job has transitioned through.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
secondaryStatusTransitions
DescribeTrainingJobResponse.Builder secondaryStatusTransitions(SecondaryStatusTransition... secondaryStatusTransitions) A history of all of the secondary statuses that the training job has transitioned through.
- Parameters:
secondaryStatusTransitions
- A history of all of the secondary statuses that the training job has transitioned through.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
secondaryStatusTransitions
DescribeTrainingJobResponse.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 viaSecondaryStatusTransition.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tosecondaryStatusTransitions(List<SecondaryStatusTransition>)
.- Parameters:
secondaryStatusTransitions
- a consumer that will call methods onSecondaryStatusTransition.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
finalMetricDataList
A collection of
MetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.- Parameters:
finalMetricDataList
- A collection ofMetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
finalMetricDataList
A collection of
MetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.- Parameters:
finalMetricDataList
- A collection ofMetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
finalMetricDataList
DescribeTrainingJobResponse.Builder finalMetricDataList(Consumer<MetricData.Builder>... finalMetricDataList) A collection of
This is a convenience method that creates an instance of theMetricData
objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.MetricData.Builder
avoiding the need to create one manually viaMetricData.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tofinalMetricDataList(List<MetricData>)
.- Parameters:
finalMetricDataList
- a consumer that will call methods onMetricData.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
enableNetworkIsolation
If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose
True
. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.- Parameters:
enableNetworkIsolation
- If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, chooseTrue
. If you enable network isolation for training jobs that are configured to use a VPC, SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
enableInterContainerTrafficEncryption
DescribeTrainingJobResponse.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 algorithms in distributed training.- Parameters:
enableInterContainerTrafficEncryption
- To encrypt all communications between ML compute instances in distributed training, chooseTrue
. 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 algorithms in distributed training.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
enableManagedSpotTraining
A Boolean indicating whether managed spot training is enabled (
True
) or not (False
).- Parameters:
enableManagedSpotTraining
- A Boolean indicating whether managed spot training is enabled (True
) or not (False
).- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
checkpointConfig
Sets the value of the CheckpointConfig property for this object.- Parameters:
checkpointConfig
- The new value for the CheckpointConfig property for this object.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
checkpointConfig
default DescribeTrainingJobResponse.Builder checkpointConfig(Consumer<CheckpointConfig.Builder> checkpointConfig) Sets the value of the CheckpointConfig property for this object. This is a convenience method that creates an instance of theCheckpointConfig.Builder
avoiding the need to create one manually viaCheckpointConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed tocheckpointConfig(CheckpointConfig)
.- Parameters:
checkpointConfig
- a consumer that will call methods onCheckpointConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
trainingTimeInSeconds
The training time in seconds.
- Parameters:
trainingTimeInSeconds
- The training time in seconds.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
billableTimeInSeconds
The billable time in seconds. Billable time refers to the absolute wall-clock time.
Multiply
BillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows:BillableTimeInSeconds * InstanceCount
.You can calculate the savings from using managed spot training using the formula
(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100
. For example, ifBillableTimeInSeconds
is 100 andTrainingTimeInSeconds
is 500, the savings is 80%.- Parameters:
billableTimeInSeconds
- The billable time in seconds. Billable time refers to the absolute wall-clock time.Multiply
BillableTimeInSeconds
by the number of instances (InstanceCount
) in your training cluster to get the total compute time SageMaker bills you if you run distributed training. The formula is as follows:BillableTimeInSeconds * InstanceCount
.You can calculate the savings from using managed spot training using the formula
(1 - BillableTimeInSeconds / TrainingTimeInSeconds) * 100
. For example, ifBillableTimeInSeconds
is 100 andTrainingTimeInSeconds
is 500, the savings is 80%.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
debugHookConfig
Sets the value of the DebugHookConfig property for this object.- Parameters:
debugHookConfig
- The new value for the DebugHookConfig property for this object.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
debugHookConfig
default DescribeTrainingJobResponse.Builder debugHookConfig(Consumer<DebugHookConfig.Builder> debugHookConfig) Sets the value of the DebugHookConfig property for this object. This is a convenience method that creates an instance of theDebugHookConfig.Builder
avoiding the need to create one manually viaDebugHookConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed todebugHookConfig(DebugHookConfig)
.- Parameters:
debugHookConfig
- a consumer that will call methods onDebugHookConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
experimentConfig
Sets the value of the ExperimentConfig property for this object.- Parameters:
experimentConfig
- The new value for the ExperimentConfig property for this object.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
experimentConfig
default DescribeTrainingJobResponse.Builder experimentConfig(Consumer<ExperimentConfig.Builder> experimentConfig) Sets the value of the ExperimentConfig property for this object. This is a convenience method that creates an instance of theExperimentConfig.Builder
avoiding the need to create one manually viaExperimentConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toexperimentConfig(ExperimentConfig)
.- Parameters:
experimentConfig
- a consumer that will call methods onExperimentConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
debugRuleConfigurations
DescribeTrainingJobResponse.Builder debugRuleConfigurations(Collection<DebugRuleConfiguration> debugRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
- Parameters:
debugRuleConfigurations
- Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
debugRuleConfigurations
DescribeTrainingJobResponse.Builder debugRuleConfigurations(DebugRuleConfiguration... debugRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
- Parameters:
debugRuleConfigurations
- Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
debugRuleConfigurations
DescribeTrainingJobResponse.Builder debugRuleConfigurations(Consumer<DebugRuleConfiguration.Builder>... debugRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
This is a convenience method that creates an instance of theDebugRuleConfiguration.Builder
avoiding the need to create one manually viaDebugRuleConfiguration.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed todebugRuleConfigurations(List<DebugRuleConfiguration>)
.- Parameters:
debugRuleConfigurations
- a consumer that will call methods onDebugRuleConfiguration.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
tensorBoardOutputConfig
DescribeTrainingJobResponse.Builder tensorBoardOutputConfig(TensorBoardOutputConfig tensorBoardOutputConfig) Sets the value of the TensorBoardOutputConfig property for this object.- Parameters:
tensorBoardOutputConfig
- The new value for the TensorBoardOutputConfig property for this object.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
tensorBoardOutputConfig
default DescribeTrainingJobResponse.Builder tensorBoardOutputConfig(Consumer<TensorBoardOutputConfig.Builder> tensorBoardOutputConfig) Sets the value of the TensorBoardOutputConfig property for this object. This is a convenience method that creates an instance of theTensorBoardOutputConfig.Builder
avoiding the need to create one manually viaTensorBoardOutputConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed totensorBoardOutputConfig(TensorBoardOutputConfig)
.- Parameters:
tensorBoardOutputConfig
- a consumer that will call methods onTensorBoardOutputConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
debugRuleEvaluationStatuses
DescribeTrainingJobResponse.Builder debugRuleEvaluationStatuses(Collection<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
- Parameters:
debugRuleEvaluationStatuses
- Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
debugRuleEvaluationStatuses
DescribeTrainingJobResponse.Builder debugRuleEvaluationStatuses(DebugRuleEvaluationStatus... debugRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
- Parameters:
debugRuleEvaluationStatuses
- Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
debugRuleEvaluationStatuses
DescribeTrainingJobResponse.Builder debugRuleEvaluationStatuses(Consumer<DebugRuleEvaluationStatus.Builder>... debugRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
This is a convenience method that creates an instance of theDebugRuleEvaluationStatus.Builder
avoiding the need to create one manually viaDebugRuleEvaluationStatus.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed todebugRuleEvaluationStatuses(List<DebugRuleEvaluationStatus>)
.- Parameters:
debugRuleEvaluationStatuses
- a consumer that will call methods onDebugRuleEvaluationStatus.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
profilerConfig
Sets the value of the ProfilerConfig property for this object.- Parameters:
profilerConfig
- The new value for the ProfilerConfig property for this object.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
profilerConfig
default DescribeTrainingJobResponse.Builder profilerConfig(Consumer<ProfilerConfig.Builder> profilerConfig) Sets the value of the ProfilerConfig property for this object. This is a convenience method that creates an instance of theProfilerConfig.Builder
avoiding the need to create one manually viaProfilerConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toprofilerConfig(ProfilerConfig)
.- Parameters:
profilerConfig
- a consumer that will call methods onProfilerConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
profilerRuleConfigurations
DescribeTrainingJobResponse.Builder profilerRuleConfigurations(Collection<ProfilerRuleConfiguration> profilerRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
- Parameters:
profilerRuleConfigurations
- Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
profilerRuleConfigurations
DescribeTrainingJobResponse.Builder profilerRuleConfigurations(ProfilerRuleConfiguration... profilerRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
- Parameters:
profilerRuleConfigurations
- Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
profilerRuleConfigurations
DescribeTrainingJobResponse.Builder profilerRuleConfigurations(Consumer<ProfilerRuleConfiguration.Builder>... profilerRuleConfigurations) Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
This is a convenience method that creates an instance of theProfilerRuleConfiguration.Builder
avoiding the need to create one manually viaProfilerRuleConfiguration.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toprofilerRuleConfigurations(List<ProfilerRuleConfiguration>)
.- Parameters:
profilerRuleConfigurations
- a consumer that will call methods onProfilerRuleConfiguration.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
profilerRuleEvaluationStatuses
DescribeTrainingJobResponse.Builder profilerRuleEvaluationStatuses(Collection<ProfilerRuleEvaluationStatus> profilerRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
- Parameters:
profilerRuleEvaluationStatuses
- Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
profilerRuleEvaluationStatuses
DescribeTrainingJobResponse.Builder profilerRuleEvaluationStatuses(ProfilerRuleEvaluationStatus... profilerRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
- Parameters:
profilerRuleEvaluationStatuses
- Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
profilerRuleEvaluationStatuses
DescribeTrainingJobResponse.Builder profilerRuleEvaluationStatuses(Consumer<ProfilerRuleEvaluationStatus.Builder>... profilerRuleEvaluationStatuses) Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
This is a convenience method that creates an instance of theProfilerRuleEvaluationStatus.Builder
avoiding the need to create one manually viaProfilerRuleEvaluationStatus.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toprofilerRuleEvaluationStatuses(List<ProfilerRuleEvaluationStatus>)
.- Parameters:
profilerRuleEvaluationStatuses
- a consumer that will call methods onProfilerRuleEvaluationStatus.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
profilingStatus
Profiling status of a training job.
- Parameters:
profilingStatus
- Profiling status of a training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
profilingStatus
Profiling status of a training job.
- Parameters:
profilingStatus
- Profiling status of a training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
environment
The environment variables to set in the Docker container.
- Parameters:
environment
- The environment variables to set in the Docker container.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
retryStrategy
The number of times to retry the job when the job fails due to an
InternalServerError
.- Parameters:
retryStrategy
- The number of times to retry the job when the job fails due to anInternalServerError
.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
retryStrategy
default DescribeTrainingJobResponse.Builder retryStrategy(Consumer<RetryStrategy.Builder> retryStrategy) The number of times to retry the job when the job fails due to an
This is a convenience method that creates an instance of theInternalServerError
.RetryStrategy.Builder
avoiding the need to create one manually viaRetryStrategy.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toretryStrategy(RetryStrategy)
.- Parameters:
retryStrategy
- a consumer that will call methods onRetryStrategy.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
remoteDebugConfig
Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
- Parameters:
remoteDebugConfig
- Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
remoteDebugConfig
default DescribeTrainingJobResponse.Builder remoteDebugConfig(Consumer<RemoteDebugConfig.Builder> remoteDebugConfig) Configuration for remote debugging. To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.
This is a convenience method that creates an instance of theRemoteDebugConfig.Builder
avoiding the need to create one manually viaRemoteDebugConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toremoteDebugConfig(RemoteDebugConfig)
.- Parameters:
remoteDebugConfig
- a consumer that will call methods onRemoteDebugConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-
infraCheckConfig
Contains information about the infrastructure health check configuration for the training job.
- Parameters:
infraCheckConfig
- Contains information about the infrastructure health check configuration for the training job.- Returns:
- Returns a reference to this object so that method calls can be chained together.
-
infraCheckConfig
default DescribeTrainingJobResponse.Builder infraCheckConfig(Consumer<InfraCheckConfig.Builder> infraCheckConfig) Contains information about the infrastructure health check configuration for the training job.
This is a convenience method that creates an instance of theInfraCheckConfig.Builder
avoiding the need to create one manually viaInfraCheckConfig.builder()
.When the
Consumer
completes,SdkBuilder.build()
is called immediately and its result is passed toinfraCheckConfig(InfraCheckConfig)
.- Parameters:
infraCheckConfig
- a consumer that will call methods onInfraCheckConfig.Builder
- Returns:
- Returns a reference to this object so that method calls can be chained together.
- See Also:
-