@Generated(value="software.amazon.awssdk:codegen") public final class TrainingJob extends Object implements SdkPojo, Serializable, ToCopyableBuilder<TrainingJob.Builder,TrainingJob>
Contains information about a training job.
| Modifier and Type | Class and Description |
|---|---|
static interface |
TrainingJob.Builder |
| 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 the job.
|
Integer |
billableTimeInSeconds()
The billable time in seconds.
|
static TrainingJob.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()
Information about the debug rule configuration.
|
List<DebugRuleEvaluationStatus> |
debugRuleEvaluationStatuses()
Information about the evaluation status of the rules for the training job.
|
Boolean |
enableInterContainerTrafficEncryption()
To encrypt all communications between ML compute instances in distributed training, choose
True. |
Boolean |
enableManagedSpotTraining()
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of
on-demand instances.
|
Boolean |
enableNetworkIsolation()
If the
TrainingJob was created with network isolation, the value is set to 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 list of final metric values that are set when the training job completes.
|
<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 |
hasSecondaryStatusTransitions()
For responses, this returns true if the service returned a value for the SecondaryStatusTransitions property.
|
boolean |
hasTags()
For responses, this returns true if the service returned a value for the Tags 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 labeling 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.
|
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 TrainingJob.Builder> |
serializableBuilderClass() |
StoppingCondition |
stoppingCondition()
Specifies a limit to how long a model training job can run.
|
List<Tag> |
tags()
An array of key-value pairs.
|
TensorBoardOutputConfig |
tensorBoardOutputConfig()
Returns the value of the TensorBoardOutputConfig property for this object.
|
TrainingJob.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()
The name of the 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.
|
clone, finalize, getClass, notify, notifyAll, wait, wait, waitcopypublic final String trainingJobName()
The name of the training job.
public final String trainingJobArn()
The Amazon Resource Name (ARN) of the training job.
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.
public final String labelingJobArn()
The Amazon Resource Name (ARN) of the labeling job.
public final String autoMLJobArn()
The Amazon Resource Name (ARN) of the job.
public final ModelArtifacts modelArtifacts()
Information about the Amazon S3 location that is configured for storing model artifacts.
public final TrainingJobStatus trainingJobStatus()
The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
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().
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
TrainingJobStatuspublic final String trainingJobStatusAsString()
The status of the training job.
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
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().
Training job statuses are:
InProgress - The training is in progress.
Completed - The training job has completed.
Failed - The training job has failed. To see the reason for the failure, see the
FailureReason field in the response to a DescribeTrainingJobResponse call.
Stopping - The training job is stopping.
Stopped - The training job has stopped.
For more detailed information, see SecondaryStatus.
TrainingJobStatuspublic final SecondaryStatus secondaryStatus()
Provides detailed information about the state of the training job. For detailed information about the secondary
status of the training job, see StatusMessage under SecondaryStatusTransition.
Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode.
It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
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().
StatusMessage under
SecondaryStatusTransition.
Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input
mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3
location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
SecondaryStatuspublic final String secondaryStatusAsString()
Provides detailed information about the state of the training job. For detailed information about the secondary
status of the training job, see StatusMessage under SecondaryStatusTransition.
Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input mode.
It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3 location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
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().
StatusMessage under
SecondaryStatusTransition.
Amazon SageMaker provides primary statuses and secondary statuses that apply to each of them:
Starting - Starting the training job.
Downloading - An optional stage for algorithms that support File training input
mode. It indicates that data is being downloaded to the ML storage volumes.
Training - Training is in progress.
Uploading - Training is complete and the model artifacts are being uploaded to the S3
location.
Completed - The training job has completed.
Failed - The training job has failed. The reason for the failure is returned in the
FailureReason field of DescribeTrainingJobResponse.
MaxRuntimeExceeded - The job stopped because it exceeded the maximum allowed runtime.
Stopped - The training job has stopped.
Stopping - Stopping the training job.
Valid values for SecondaryStatus are subject to change.
We no longer support the following secondary statuses:
LaunchingMLInstances
PreparingTrainingStack
DownloadingTrainingImage
SecondaryStatuspublic final String failureReason()
If the training job failed, the reason it failed.
public final boolean hasHyperParameters()
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.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.
public final AlgorithmSpecification algorithmSpecification()
Information about the algorithm used for training, and algorithm metadata.
public final String roleArn()
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
public final boolean hasInputDataConfig()
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.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.
Channel objects that describes each data input channel.public final OutputDataConfig outputDataConfig()
The S3 path where model artifacts that you configured when creating the job are stored. Amazon SageMaker creates subfolders for model artifacts.
public final ResourceConfig resourceConfig()
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
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.
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, 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.
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.
public final Instant creationTime()
A timestamp that indicates when the training job was created.
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.
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.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 Amazon SageMaker detects a job
failure.
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.public final Instant lastModifiedTime()
A timestamp that indicates when the status of the training job was last modified.
public final boolean hasSecondaryStatusTransitions()
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.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.
public final boolean hasFinalMetricDataList()
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.public final List<MetricData> finalMetricDataList()
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
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.
public final Boolean enableNetworkIsolation()
If the TrainingJob was created with network isolation, the value is set to true. If
network isolation is enabled, nodes can't communicate beyond the VPC they run in.
TrainingJob was created with network isolation, the value is set to true
. If network isolation is enabled, nodes can't communicate beyond the VPC they run in.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 algorithm
in distributed training.
True. Encryption provides greater security for distributed training, but training might take
longer. How long it takes depends on the amount of communication between compute instances, especially if
you use a deep learning algorithm in distributed training.public final Boolean enableManagedSpotTraining()
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
public final CheckpointConfig checkpointConfig()
public final Integer trainingTimeInSeconds()
The training time in seconds.
public final Integer billableTimeInSeconds()
The billable time in seconds.
public final DebugHookConfig debugHookConfig()
public final ExperimentConfig experimentConfig()
public final boolean hasDebugRuleConfigurations()
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.public final List<DebugRuleConfiguration> debugRuleConfigurations()
Information about the debug rule configuration.
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.
public final TensorBoardOutputConfig tensorBoardOutputConfig()
public final boolean hasDebugRuleEvaluationStatuses()
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.public final List<DebugRuleEvaluationStatus> debugRuleEvaluationStatuses()
Information about the evaluation status of the rules for the 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.
public final boolean hasEnvironment()
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.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.
public final RetryStrategy retryStrategy()
The number of times to retry the job when the job fails due to an InternalServerError.
InternalServerError.public final boolean hasTags()
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.public final List<Tag> tags()
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
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 hasTags() method.
public TrainingJob.Builder toBuilder()
toBuilder in interface ToCopyableBuilder<TrainingJob.Builder,TrainingJob>public static TrainingJob.Builder builder()
public static Class<? extends TrainingJob.Builder> serializableBuilderClass()
public final boolean equalsBySdkFields(Object obj)
equalsBySdkFields in interface SdkPojopublic final String toString()
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