DescribeTrainingJobResponse (AWS Java SDK :: Services

java.lang.Object
- software.amazon.awssdk.core.SdkResponse
- - software.amazon.awssdk.awscore.AwsResponse
  - - software.amazon.awssdk.services.sagemaker.model.SageMakerResponse
    - - software.amazon.awssdk.services.sagemaker.model.DescribeTrainingJobResponse

All Implemented Interfaces:: SdkPojo, ToCopyableBuilder<DescribeTrainingJobResponse.Builder,DescribeTrainingJobResponse>

@Generated(value="software.amazon.awssdk:codegen")
public final class DescribeTrainingJobResponse
extends SageMakerResponse
implements ToCopyableBuilder<DescribeTrainingJobResponse.Builder,DescribeTrainingJobResponse>

Nested Class Summary

Nested Classes
Modifier and Type Class and Description

static interface DescribeTrainingJobResponse.Builder

Nested Classes
Modifier and Type	Class and Description
`static interface`	`DescribeTrainingJobResponse.Builder`

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`AlgorithmSpecification`	`algorithmSpecification()` Information about the algorithm used for training, and algorithm metadata.
`String`	`autoMLJobArn()` The Amazon Resource Name (ARN) of an AutoML job.
`Integer`	`billableTimeInSeconds()` The billable time in seconds.
`static DescribeTrainingJobResponse.Builder`	`builder()`
`CheckpointConfig`	`checkpointConfig()` Returns the value of the CheckpointConfig property for this object.
`Instant`	`creationTime()` A timestamp that indicates when the training job was created.
`DebugHookConfig`	`debugHookConfig()` Returns the value of the DebugHookConfig property for this object.
`List<DebugRuleConfiguration>`	`debugRuleConfigurations()` Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
`List<DebugRuleEvaluationStatus>`	`debugRuleEvaluationStatuses()` Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
`Boolean`	`enableInterContainerTrafficEncryption()` To encrypt all communications between ML compute instances in distributed training, choose `True`.
`Boolean`	`enableManagedSpotTraining()` A Boolean indicating whether managed spot training is enabled (`True`) or not (`False`).
`Boolean`	`enableNetworkIsolation()` If you want to allow inbound or outbound network calls, except for calls between peers within a training cluster for distributed training, choose `True`.
`Map<String,String>`	`environment()` The environment variables to set in the Docker container.
`boolean`	`equals(Object obj)`
`boolean`	`equalsBySdkFields(Object obj)`
`ExperimentConfig`	`experimentConfig()` Returns the value of the ExperimentConfig property for this object.
`String`	`failureReason()` If the training job failed, the reason it failed.
`List<MetricData>`	`finalMetricDataList()` A collection of `MetricData` objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
`<T> Optional<T>`	`getValueForField(String fieldName, Class<T> clazz)`
`boolean`	`hasDebugRuleConfigurations()` For responses, this returns true if the service returned a value for the DebugRuleConfigurations property.
`boolean`	`hasDebugRuleEvaluationStatuses()` For responses, this returns true if the service returned a value for the DebugRuleEvaluationStatuses property.
`boolean`	`hasEnvironment()` For responses, this returns true if the service returned a value for the Environment property.
`boolean`	`hasFinalMetricDataList()` For responses, this returns true if the service returned a value for the FinalMetricDataList property.
`int`	`hashCode()`
`boolean`	`hasHyperParameters()` For responses, this returns true if the service returned a value for the HyperParameters property.
`boolean`	`hasInputDataConfig()` For responses, this returns true if the service returned a value for the InputDataConfig property.
`boolean`	`hasProfilerRuleConfigurations()` For responses, this returns true if the service returned a value for the ProfilerRuleConfigurations property.
`boolean`	`hasProfilerRuleEvaluationStatuses()` For responses, this returns true if the service returned a value for the ProfilerRuleEvaluationStatuses property.
`boolean`	`hasSecondaryStatusTransitions()` For responses, this returns true if the service returned a value for the SecondaryStatusTransitions property.
`Map<String,String>`	`hyperParameters()` Algorithm-specific parameters.
`List<Channel>`	`inputDataConfig()` An array of `Channel` objects that describes each data input channel.
`String`	`labelingJobArn()` The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
`Instant`	`lastModifiedTime()` A timestamp that indicates when the status of the training job was last modified.
`ModelArtifacts`	`modelArtifacts()` Information about the Amazon S3 location that is configured for storing model artifacts.
`OutputDataConfig`	`outputDataConfig()` The S3 path where model artifacts that you configured when creating the job are stored.
`ProfilerConfig`	`profilerConfig()` Returns the value of the ProfilerConfig property for this object.
`List<ProfilerRuleConfiguration>`	`profilerRuleConfigurations()` Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
`List<ProfilerRuleEvaluationStatus>`	`profilerRuleEvaluationStatuses()` Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
`ProfilingStatus`	`profilingStatus()` Profiling status of a training job.
`String`	`profilingStatusAsString()` Profiling status of a training job.
`ResourceConfig`	`resourceConfig()` Resources, including ML compute instances and ML storage volumes, that are configured for model training.
`RetryStrategy`	`retryStrategy()` The number of times to retry the job when the job fails due to an `InternalServerError`.
`String`	`roleArn()` The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
`List<SdkField<?>>`	`sdkFields()`
`SecondaryStatus`	`secondaryStatus()` Provides detailed information about the state of the training job.
`String`	`secondaryStatusAsString()` Provides detailed information about the state of the training job.
`List<SecondaryStatusTransition>`	`secondaryStatusTransitions()` A history of all of the secondary statuses that the training job has transitioned through.
`static Class<? extends DescribeTrainingJobResponse.Builder>`	`serializableBuilderClass()`
`StoppingCondition`	`stoppingCondition()` Specifies a limit to how long a model training job can run.
`TensorBoardOutputConfig`	`tensorBoardOutputConfig()` Returns the value of the TensorBoardOutputConfig property for this object.
`DescribeTrainingJobResponse.Builder`	`toBuilder()`
`String`	`toString()` Returns a string representation of this object.
`Instant`	`trainingEndTime()` Indicates the time when the training job ends on training instances.
`String`	`trainingJobArn()` The Amazon Resource Name (ARN) of the training job.
`String`	`trainingJobName()` Name of the model training job.
`TrainingJobStatus`	`trainingJobStatus()` The status of the training job.
`String`	`trainingJobStatusAsString()` The status of the training job.
`Instant`	`trainingStartTime()` Indicates the time when the training job starts on training instances.
`Integer`	`trainingTimeInSeconds()` The training time in seconds.
`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`	`vpcConfig()` A VpcConfig object that specifies the VPC that this training job has access to.
`WarmPoolStatus`	`warmPoolStatus()` The status of the warm pool associated with the training job.

Methods inherited from class software.amazon.awssdk.services.sagemaker.model.SageMakerResponse
responseMetadata

Methods inherited from class software.amazon.awssdk.core.SdkResponse
sdkHttpResponse

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

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

- Method Detail
  - trainingJobName
```
public final String trainingJobName()
```
    Name of the model training job.
    
    Returns:
    
    Name of the model training job.
  - trainingJobArn
```
public final String trainingJobArn()
```
    The Amazon Resource Name (ARN) of the training job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the training job.
  - tuningJobArn
```
public final String tuningJobArn()
```
    The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
  - labelingJobArn
```
public final String labelingJobArn()
```
    The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the SageMaker Ground Truth labeling job that created the transform or training job.
  - autoMLJobArn
```
public final String autoMLJobArn()
```
    The Amazon Resource Name (ARN) of an AutoML job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of an AutoML job.
  - modelArtifacts
```
public final ModelArtifacts modelArtifacts()
```
    Information about the Amazon S3 location that is configured for storing model artifacts.
    
    Returns:
    
    Information about the Amazon S3 location that is configured for storing model artifacts.
  - trainingJobStatus
```
public final TrainingJobStatus 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 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.
    
    If the service returns an enum value that is not available in the current SDK version, trainingJobStatus will return TrainingJobStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from trainingJobStatusAsString().
    Returns:
    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 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.
    See Also:
    
    TrainingJobStatus
  - trainingJobStatusAsString
```
public final String trainingJobStatusAsString()
```
    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 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.
    
    If the service returns an enum value that is not available in the current SDK version, trainingJobStatus will return TrainingJobStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from trainingJobStatusAsString().
    Returns:
    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 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.
    See Also:
    
    TrainingJobStatus
  - secondaryStatus
```
public final SecondaryStatus 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 support File 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 the FailureReason field of DescribeTrainingJobResponse.
    
    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
    If the service returns an enum value that is not available in the current SDK version, secondaryStatus will return SecondaryStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from secondaryStatusAsString().
    Returns:
    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 support File 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 the FailureReason field of DescribeTrainingJobResponse.
    
    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
    See Also:
    
    SecondaryStatus
  - secondaryStatusAsString
```
public final String secondaryStatusAsString()
```
    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 support File 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 the FailureReason field of DescribeTrainingJobResponse.
    
    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
    If the service returns an enum value that is not available in the current SDK version, secondaryStatus will return SecondaryStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from secondaryStatusAsString().
    Returns:
    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 support File 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 the FailureReason field of DescribeTrainingJobResponse.
    
    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
    See Also:
    
    SecondaryStatus
  - failureReason
```
public final String failureReason()
```
    If the training job failed, the reason it failed.
    
    Returns:
    
    If the training job failed, the reason it failed.
  - hasHyperParameters
```
public final boolean hasHyperParameters()
```
    For responses, this returns true if the service returned a value for the HyperParameters property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - hyperParameters
```
public final Map<String,String> hyperParameters()
```
    Algorithm-specific parameters.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasHyperParameters() method.
    
    Returns:
    
    Algorithm-specific parameters.
  - algorithmSpecification
```
public final AlgorithmSpecification algorithmSpecification()
```
    Information about the algorithm used for training, and algorithm metadata.
    
    Returns:
    
    Information about the algorithm used for training, and algorithm metadata.
  - roleArn
```
public final String roleArn()
```
    The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
    
    Returns:
    
    The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
  - hasInputDataConfig
```
public final boolean hasInputDataConfig()
```
    For responses, this returns true if the service returned a value for the InputDataConfig property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - inputDataConfig
```
public final List<Channel> inputDataConfig()
```
    An array of Channel objects that describes each data input channel.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasInputDataConfig() method.
    
    Returns:
    
    An array of Channel objects that describes each data input channel.
  - outputDataConfig
```
public final OutputDataConfig outputDataConfig()
```
    The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
    
    Returns:
    
    The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
  - resourceConfig
```
public final ResourceConfig resourceConfig()
```
    Resources, including ML compute instances and ML storage volumes, that are configured for model training.
    
    Returns:
    
    Resources, including ML compute instances and ML storage volumes, that are configured for model training.
  - vpcConfig
```
public final 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.
    
    Returns:
    
    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.
  - stoppingCondition
```
public final 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.
    
    Returns:
    
    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.
  - creationTime
```
public final Instant creationTime()
```
    A timestamp that indicates when the training job was created.
    
    Returns:
    
    A timestamp that indicates when the training job was created.
  - trainingStartTime
```
public final 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.
    
    Returns:
    
    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.
  - trainingEndTime
```
public final 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.
    
    Returns:
    
    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.
  - lastModifiedTime
```
public final Instant lastModifiedTime()
```
    A timestamp that indicates when the status of the training job was last modified.
    
    Returns:
    
    A timestamp that indicates when the status of the training job was last modified.
  - hasSecondaryStatusTransitions
```
public final boolean hasSecondaryStatusTransitions()
```
    For responses, this returns true if the service returned a value for the SecondaryStatusTransitions property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - secondaryStatusTransitions
```
public final List<SecondaryStatusTransition> secondaryStatusTransitions()
```
    A history of all of the secondary statuses that the training job has transitioned through.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasSecondaryStatusTransitions() method.
    
    Returns:
    
    A history of all of the secondary statuses that the training job has transitioned through.
  - hasFinalMetricDataList
```
public final boolean hasFinalMetricDataList()
```
    For responses, this returns true if the service returned a value for the FinalMetricDataList property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - finalMetricDataList
```
public final List<MetricData> finalMetricDataList()
```
    A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasFinalMetricDataList() method.
    
    Returns:
    
    A collection of MetricData objects that specify the names, values, and dates and times that the training algorithm emitted to Amazon CloudWatch.
  - enableNetworkIsolation
```
public final Boolean 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.
    
    Returns:
    
    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.
  - enableInterContainerTrafficEncryption
```
public final 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.
    
    Returns:
    
    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.
  - enableManagedSpotTraining
```
public final Boolean enableManagedSpotTraining()
```
    A Boolean indicating whether managed spot training is enabled (True) or not (False).
    
    Returns:
    
    A Boolean indicating whether managed spot training is enabled (True) or not ( False).
  - checkpointConfig
```
public final CheckpointConfig checkpointConfig()
```
    Returns the value of the CheckpointConfig property for this object.
    
    Returns:
    
    The value of the CheckpointConfig property for this object.
  - trainingTimeInSeconds
```
public final Integer trainingTimeInSeconds()
```
    The training time in seconds.
    
    Returns:
    
    The training time in seconds.
  - billableTimeInSeconds
```
public final Integer 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, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.
    
    Returns:
    
    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, if BillableTimeInSeconds is 100 and TrainingTimeInSeconds is 500, the savings is 80%.
  - debugHookConfig
```
public final DebugHookConfig debugHookConfig()
```
    Returns the value of the DebugHookConfig property for this object.
    
    Returns:
    
    The value of the DebugHookConfig property for this object.
  - experimentConfig
```
public final ExperimentConfig experimentConfig()
```
    Returns the value of the ExperimentConfig property for this object.
    
    Returns:
    
    The value of the ExperimentConfig property for this object.
  - hasDebugRuleConfigurations
```
public final boolean hasDebugRuleConfigurations()
```
    For responses, this returns true if the service returned a value for the DebugRuleConfigurations property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - debugRuleConfigurations
```
public final List<DebugRuleConfiguration> debugRuleConfigurations()
```
    Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasDebugRuleConfigurations() method.
    
    Returns:
    
    Configuration information for Amazon SageMaker Debugger rules for debugging output tensors.
  - tensorBoardOutputConfig
```
public final TensorBoardOutputConfig tensorBoardOutputConfig()
```
    Returns the value of the TensorBoardOutputConfig property for this object.
    
    Returns:
    
    The value of the TensorBoardOutputConfig property for this object.
  - hasDebugRuleEvaluationStatuses
```
public final boolean hasDebugRuleEvaluationStatuses()
```
    For responses, this returns true if the service returned a value for the DebugRuleEvaluationStatuses property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - debugRuleEvaluationStatuses
```
public final List<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses()
```
    Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasDebugRuleEvaluationStatuses() method.
    
    Returns:
    
    Evaluation status of Amazon SageMaker Debugger rules for debugging on a training job.
  - profilerConfig
```
public final ProfilerConfig profilerConfig()
```
    Returns the value of the ProfilerConfig property for this object.
    
    Returns:
    
    The value of the ProfilerConfig property for this object.
  - hasProfilerRuleConfigurations
```
public final boolean hasProfilerRuleConfigurations()
```
    For responses, this returns true if the service returned a value for the ProfilerRuleConfigurations property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - profilerRuleConfigurations
```
public final List<ProfilerRuleConfiguration> profilerRuleConfigurations()
```
    Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasProfilerRuleConfigurations() method.
    
    Returns:
    
    Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
  - hasProfilerRuleEvaluationStatuses
```
public final boolean hasProfilerRuleEvaluationStatuses()
```
    For responses, this returns true if the service returned a value for the ProfilerRuleEvaluationStatuses property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - profilerRuleEvaluationStatuses
```
public final List<ProfilerRuleEvaluationStatus> profilerRuleEvaluationStatuses()
```
    Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasProfilerRuleEvaluationStatuses() method.
    
    Returns:
    
    Evaluation status of Amazon SageMaker Debugger rules for profiling on a training job.
  - profilingStatus
```
public final ProfilingStatus profilingStatus()
```
    Profiling status of a training job.
    
    If the service returns an enum value that is not available in the current SDK version, profilingStatus will return ProfilingStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from profilingStatusAsString().
    
    Returns:
    
    Profiling status of a training job.
    
    See Also:
    
    ProfilingStatus
  - profilingStatusAsString
```
public final String profilingStatusAsString()
```
    Profiling status of a training job.
    
    If the service returns an enum value that is not available in the current SDK version, profilingStatus will return ProfilingStatus.UNKNOWN_TO_SDK_VERSION. The raw value returned by the service is available from profilingStatusAsString().
    
    Returns:
    
    Profiling status of a training job.
    
    See Also:
    
    ProfilingStatus
  - retryStrategy
```
public final RetryStrategy retryStrategy()
```
    The number of times to retry the job when the job fails due to an InternalServerError.
    
    Returns:
    
    The number of times to retry the job when the job fails due to an InternalServerError.
  - hasEnvironment
```
public final boolean hasEnvironment()
```
    For responses, this returns true if the service returned a value for the Environment property. This DOES NOT check that the value is non-empty (for which, you should check the isEmpty() method on the property). This is useful because the SDK will never return a null collection or map, but you may need to differentiate between the service returning nothing (or null) and the service returning an empty collection or map. For requests, this returns true if a value for the property was specified in the request builder, and false if a value was not specified.
  - environment
```
public final Map<String,String> environment()
```
    The environment variables to set in the Docker container.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    This method will never return null. If you would like to know whether the service returned this field (so that you can differentiate between null and empty), you can use the hasEnvironment() method.
    
    Returns:
    
    The environment variables to set in the Docker container.
  - warmPoolStatus
```
public final WarmPoolStatus warmPoolStatus()
```
    The status of the warm pool associated with the training job.
    
    Returns:
    
    The status of the warm pool associated with the training job.
  - toBuilder
```
public DescribeTrainingJobResponse.Builder toBuilder()
```
    Specified by:
    
    toBuilder in interface ToCopyableBuilder<DescribeTrainingJobResponse.Builder,DescribeTrainingJobResponse>
    
    Overrides:
    
    toBuilder in class AwsResponse
  - builder
```
public static DescribeTrainingJobResponse.Builder builder()
```
  - serializableBuilderClass
```
public static Class<? extends DescribeTrainingJobResponse.Builder> serializableBuilderClass()
```
  - hashCode
```
public final int hashCode()
```
    Overrides:
    
    hashCode in class AwsResponse
  - equals
```
public final boolean equals(Object obj)
```
    Overrides:
    
    equals in class AwsResponse
  - equalsBySdkFields
```
public final boolean equalsBySdkFields(Object obj)
```
    Specified by:
    
    equalsBySdkFields in interface SdkPojo
  - toString
```
public final String toString()
```
    Returns a string representation of this object. This is useful for testing and debugging. Sensitive data will be redacted from this string using a placeholder value.
    
    Overrides:
    
    toString in class Object
  - getValueForField
```
public final <T> Optional<T> getValueForField(String fieldName,
                                              Class<T> clazz)
```
    Overrides:
    
    getValueForField in class SdkResponse
  - sdkFields
```
public final List<SdkField<?>> sdkFields()
```
    Specified by:
    
    sdkFields in interface SdkPojo

Class DescribeTrainingJobResponse

Nested Class Summary

Method Summary

Methods inherited from class software.amazon.awssdk.services.sagemaker.model.SageMakerResponse

Methods inherited from class software.amazon.awssdk.core.SdkResponse

Methods inherited from class java.lang.Object

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

Method Detail

trainingJobName

trainingJobArn

tuningJobArn

labelingJobArn

autoMLJobArn

modelArtifacts

trainingJobStatus

trainingJobStatusAsString

secondaryStatus

secondaryStatusAsString

failureReason

hasHyperParameters

hyperParameters

algorithmSpecification

roleArn

hasInputDataConfig

inputDataConfig

outputDataConfig

resourceConfig

vpcConfig

stoppingCondition

creationTime

trainingStartTime

trainingEndTime

lastModifiedTime

hasSecondaryStatusTransitions

secondaryStatusTransitions

hasFinalMetricDataList

finalMetricDataList

enableNetworkIsolation

enableInterContainerTrafficEncryption

enableManagedSpotTraining

checkpointConfig

trainingTimeInSeconds

billableTimeInSeconds

debugHookConfig

experimentConfig

hasDebugRuleConfigurations

debugRuleConfigurations

tensorBoardOutputConfig

hasDebugRuleEvaluationStatuses

debugRuleEvaluationStatuses

profilerConfig

hasProfilerRuleConfigurations

profilerRuleConfigurations

hasProfilerRuleEvaluationStatuses

profilerRuleEvaluationStatuses

profilingStatus

profilingStatusAsString

retryStrategy

hasEnvironment

environment

warmPoolStatus

toBuilder

builder

serializableBuilderClass

hashCode

equals

equalsBySdkFields

toString

getValueForField

sdkFields