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 debugging rules.
`List<DebugRuleEvaluationStatus>`	`debugRuleEvaluationStatuses()` Status about the debug rule evaluation.
`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`.
`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()` Returns true if the DebugRuleConfigurations property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
`boolean`	`hasDebugRuleEvaluationStatuses()` Returns true if the DebugRuleEvaluationStatuses property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
`boolean`	`hasFinalMetricDataList()` Returns true if the FinalMetricDataList property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
`int`	`hashCode()`
`boolean`	`hasHyperParameters()` Returns true if the HyperParameters property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
`boolean`	`hasInputDataConfig()` Returns true if the InputDataConfig property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
`boolean`	`hasSecondaryStatusTransitions()` Returns true if the SecondaryStatusTransitions property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty).
`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 Amazon 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.
`ResourceConfig`	`resourceConfig()` Resources, including ML compute instances and ML storage volumes, that are configured for model training.
`String`	`roleArn()` The AWS 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.

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 String trainingJobName()
```
    Name of the model training job.
    
    Returns:
    
    Name of the model training job.
  - trainingJobArn
```
public String trainingJobArn()
```
    The Amazon Resource Name (ARN) of the training job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the training job.
  - tuningJobArn
```
public 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 String labelingJobArn()
```
    The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of the Amazon SageMaker Ground Truth labeling job that created the transform or training job.
  - autoMLJobArn
```
public String autoMLJobArn()
```
    The Amazon Resource Name (ARN) of an AutoML job.
    
    Returns:
    
    The Amazon Resource Name (ARN) of an AutoML job.
  - modelArtifacts
```
public 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 TrainingJobStatus trainingJobStatus()
```
    The status of the training job.
    
    Amazon 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.
    
    Amazon 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 String trainingJobStatusAsString()
```
    The status of the training job.
    
    Amazon 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.
    
    Amazon 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 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.
    
    Amazon 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.
    
    MaxWaitTmeExceeded - 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
    - PreparingTrainingStack
    - 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.
    
    Amazon 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.
    
    MaxWaitTmeExceeded - 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
    
    PreparingTrainingStack
    
    DownloadingTrainingImage
    See Also:
    
    SecondaryStatus
  - secondaryStatusAsString
```
public 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.
    
    Amazon 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.
    
    MaxWaitTmeExceeded - 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
    - PreparingTrainingStack
    - 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.
    
    Amazon 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.
    
    MaxWaitTmeExceeded - 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
    
    PreparingTrainingStack
    
    DownloadingTrainingImage
    See Also:
    
    SecondaryStatus
  - failureReason
```
public String failureReason()
```
    If the training job failed, the reason it failed.
    
    Returns:
    
    If the training job failed, the reason it failed.
  - hasHyperParameters
```
public boolean hasHyperParameters()
```
    Returns true if the HyperParameters property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.
  - hyperParameters
```
public Map<String,String> hyperParameters()
```
    Algorithm-specific parameters.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    You can use hasHyperParameters() to see if a value was sent in this field.
    
    Returns:
    
    Algorithm-specific parameters.
  - algorithmSpecification
```
public 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 String roleArn()
```
    The AWS Identity and Access Management (IAM) role configured for the training job.
    
    Returns:
    
    The AWS Identity and Access Management (IAM) role configured for the training job.
  - hasInputDataConfig
```
public boolean hasInputDataConfig()
```
    Returns true if the InputDataConfig property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.
  - inputDataConfig
```
public 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.
    
    You can use hasInputDataConfig() to see if a value was sent in this field.
    
    Returns:
    
    An array of Channel objects that describes each data input channel.
  - outputDataConfig
```
public OutputDataConfig outputDataConfig()
```
    The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.
    
    Returns:
    
    The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.
  - resourceConfig
```
public 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 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 StoppingCondition stoppingCondition()
```
    Specifies a limit to how long a model training job can run. It also specifies the maximum time to wait for a spot instance. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.
    
    To stop a job, Amazon 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 the maximum time to wait for a spot instance. When the job reaches the time limit, Amazon SageMaker ends the training job. Use this API to cap model training costs.
    
    To stop a job, Amazon 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 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 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 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 Amazon 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 Amazon SageMaker detects a job failure.
  - lastModifiedTime
```
public 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 boolean hasSecondaryStatusTransitions()
```
    Returns true if the SecondaryStatusTransitions property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.
  - secondaryStatusTransitions
```
public 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.
    
    You can use hasSecondaryStatusTransitions() to see if a value was sent in this field.
    
    Returns:
    
    A history of all of the secondary statuses that the training job has transitioned through.
  - hasFinalMetricDataList
```
public boolean hasFinalMetricDataList()
```
    Returns true if the FinalMetricDataList property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.
  - finalMetricDataList
```
public 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.
    
    You can use hasFinalMetricDataList() to see if a value was sent in this field.
    
    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 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, Amazon 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, Amazon SageMaker downloads and uploads customer data and model artifacts through the specified VPC, but the training container does not have network access.
  - enableInterContainerTrafficEncryption
```
public Boolean enableInterContainerTrafficEncryption()
```
    To encrypt all communications between ML compute instances in distributed training, choose True. Encryption provides greater security for distributed training, but training might take longer. How long it takes depends on the amount of communication between compute instances, especially if you use a deep learning 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 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 CheckpointConfig checkpointConfig()
```
    Returns the value of the CheckpointConfig property for this object.
    
    Returns:
    
    The value of the CheckpointConfig property for this object.
  - trainingTimeInSeconds
```
public Integer trainingTimeInSeconds()
```
    The training time in seconds.
    
    Returns:
    
    The training time in seconds.
  - billableTimeInSeconds
```
public Integer billableTimeInSeconds()
```
    The billable time in seconds.
    
    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.
    
    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 DebugHookConfig debugHookConfig()
```
    Returns the value of the DebugHookConfig property for this object.
    
    Returns:
    
    The value of the DebugHookConfig property for this object.
  - experimentConfig
```
public ExperimentConfig experimentConfig()
```
    Returns the value of the ExperimentConfig property for this object.
    
    Returns:
    
    The value of the ExperimentConfig property for this object.
  - hasDebugRuleConfigurations
```
public boolean hasDebugRuleConfigurations()
```
    Returns true if the DebugRuleConfigurations property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.
  - debugRuleConfigurations
```
public List<DebugRuleConfiguration> debugRuleConfigurations()
```
    Configuration information for debugging rules.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    You can use hasDebugRuleConfigurations() to see if a value was sent in this field.
    
    Returns:
    
    Configuration information for debugging rules.
  - tensorBoardOutputConfig
```
public TensorBoardOutputConfig tensorBoardOutputConfig()
```
    Returns the value of the TensorBoardOutputConfig property for this object.
    
    Returns:
    
    The value of the TensorBoardOutputConfig property for this object.
  - hasDebugRuleEvaluationStatuses
```
public boolean hasDebugRuleEvaluationStatuses()
```
    Returns true if the DebugRuleEvaluationStatuses property was specified by the sender (it may be empty), or false if the sender did not specify the value (it will be empty). For responses returned by the SDK, the sender is the AWS service.
  - debugRuleEvaluationStatuses
```
public List<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses()
```
    Status about the debug rule evaluation.
    
    Attempts to modify the collection returned by this method will result in an UnsupportedOperationException.
    
    You can use hasDebugRuleEvaluationStatuses() to see if a value was sent in this field.
    
    Returns:
    
    Status about the debug rule evaluation.
  - 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 int hashCode()
```
    Overrides:
    
    hashCode in class AwsResponse
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class AwsResponse
  - equalsBySdkFields
```
public boolean equalsBySdkFields(Object obj)
```
    Specified by:
    
    equalsBySdkFields in interface SdkPojo
  - toString
```
public 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 <T> Optional<T> getValueForField(String fieldName,
                                        Class<T> clazz)
```
    Overrides:
    
    getValueForField in class SdkResponse
  - sdkFields
```
public 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

toBuilder

builder

serializableBuilderClass

hashCode

equals

equalsBySdkFields

toString

getValueForField

sdkFields