Copyright | (c) 2013-2023 Brendan Hay |
---|---|
License | Mozilla Public License, v. 2.0. |
Maintainer | Brendan Hay |
Stability | auto-generated |
Portability | non-portable (GHC extensions) |
Safe Haskell | Safe-Inferred |
Language | Haskell2010 |
Synopsis
- data TrainingJob = TrainingJob' {
- algorithmSpecification :: Maybe AlgorithmSpecification
- autoMLJobArn :: Maybe Text
- billableTimeInSeconds :: Maybe Natural
- checkpointConfig :: Maybe CheckpointConfig
- creationTime :: Maybe POSIX
- debugHookConfig :: Maybe DebugHookConfig
- debugRuleConfigurations :: Maybe [DebugRuleConfiguration]
- debugRuleEvaluationStatuses :: Maybe [DebugRuleEvaluationStatus]
- enableInterContainerTrafficEncryption :: Maybe Bool
- enableManagedSpotTraining :: Maybe Bool
- enableNetworkIsolation :: Maybe Bool
- environment :: Maybe (HashMap Text Text)
- experimentConfig :: Maybe ExperimentConfig
- failureReason :: Maybe Text
- finalMetricDataList :: Maybe [MetricData]
- hyperParameters :: Maybe (HashMap Text Text)
- inputDataConfig :: Maybe (NonEmpty Channel)
- labelingJobArn :: Maybe Text
- lastModifiedTime :: Maybe POSIX
- modelArtifacts :: Maybe ModelArtifacts
- outputDataConfig :: Maybe OutputDataConfig
- resourceConfig :: Maybe ResourceConfig
- retryStrategy :: Maybe RetryStrategy
- roleArn :: Maybe Text
- secondaryStatus :: Maybe SecondaryStatus
- secondaryStatusTransitions :: Maybe [SecondaryStatusTransition]
- stoppingCondition :: Maybe StoppingCondition
- tags :: Maybe [Tag]
- tensorBoardOutputConfig :: Maybe TensorBoardOutputConfig
- trainingEndTime :: Maybe POSIX
- trainingJobArn :: Maybe Text
- trainingJobName :: Maybe Text
- trainingJobStatus :: Maybe TrainingJobStatus
- trainingStartTime :: Maybe POSIX
- trainingTimeInSeconds :: Maybe Natural
- tuningJobArn :: Maybe Text
- vpcConfig :: Maybe VpcConfig
- newTrainingJob :: TrainingJob
- trainingJob_algorithmSpecification :: Lens' TrainingJob (Maybe AlgorithmSpecification)
- trainingJob_autoMLJobArn :: Lens' TrainingJob (Maybe Text)
- trainingJob_billableTimeInSeconds :: Lens' TrainingJob (Maybe Natural)
- trainingJob_checkpointConfig :: Lens' TrainingJob (Maybe CheckpointConfig)
- trainingJob_creationTime :: Lens' TrainingJob (Maybe UTCTime)
- trainingJob_debugHookConfig :: Lens' TrainingJob (Maybe DebugHookConfig)
- trainingJob_debugRuleConfigurations :: Lens' TrainingJob (Maybe [DebugRuleConfiguration])
- trainingJob_debugRuleEvaluationStatuses :: Lens' TrainingJob (Maybe [DebugRuleEvaluationStatus])
- trainingJob_enableInterContainerTrafficEncryption :: Lens' TrainingJob (Maybe Bool)
- trainingJob_enableManagedSpotTraining :: Lens' TrainingJob (Maybe Bool)
- trainingJob_enableNetworkIsolation :: Lens' TrainingJob (Maybe Bool)
- trainingJob_environment :: Lens' TrainingJob (Maybe (HashMap Text Text))
- trainingJob_experimentConfig :: Lens' TrainingJob (Maybe ExperimentConfig)
- trainingJob_failureReason :: Lens' TrainingJob (Maybe Text)
- trainingJob_finalMetricDataList :: Lens' TrainingJob (Maybe [MetricData])
- trainingJob_hyperParameters :: Lens' TrainingJob (Maybe (HashMap Text Text))
- trainingJob_inputDataConfig :: Lens' TrainingJob (Maybe (NonEmpty Channel))
- trainingJob_labelingJobArn :: Lens' TrainingJob (Maybe Text)
- trainingJob_lastModifiedTime :: Lens' TrainingJob (Maybe UTCTime)
- trainingJob_modelArtifacts :: Lens' TrainingJob (Maybe ModelArtifacts)
- trainingJob_outputDataConfig :: Lens' TrainingJob (Maybe OutputDataConfig)
- trainingJob_resourceConfig :: Lens' TrainingJob (Maybe ResourceConfig)
- trainingJob_retryStrategy :: Lens' TrainingJob (Maybe RetryStrategy)
- trainingJob_roleArn :: Lens' TrainingJob (Maybe Text)
- trainingJob_secondaryStatus :: Lens' TrainingJob (Maybe SecondaryStatus)
- trainingJob_secondaryStatusTransitions :: Lens' TrainingJob (Maybe [SecondaryStatusTransition])
- trainingJob_stoppingCondition :: Lens' TrainingJob (Maybe StoppingCondition)
- trainingJob_tags :: Lens' TrainingJob (Maybe [Tag])
- trainingJob_tensorBoardOutputConfig :: Lens' TrainingJob (Maybe TensorBoardOutputConfig)
- trainingJob_trainingEndTime :: Lens' TrainingJob (Maybe UTCTime)
- trainingJob_trainingJobArn :: Lens' TrainingJob (Maybe Text)
- trainingJob_trainingJobName :: Lens' TrainingJob (Maybe Text)
- trainingJob_trainingJobStatus :: Lens' TrainingJob (Maybe TrainingJobStatus)
- trainingJob_trainingStartTime :: Lens' TrainingJob (Maybe UTCTime)
- trainingJob_trainingTimeInSeconds :: Lens' TrainingJob (Maybe Natural)
- trainingJob_tuningJobArn :: Lens' TrainingJob (Maybe Text)
- trainingJob_vpcConfig :: Lens' TrainingJob (Maybe VpcConfig)
Documentation
data TrainingJob Source #
Contains information about a training job.
See: newTrainingJob
smart constructor.
TrainingJob' | |
|
Instances
newTrainingJob :: TrainingJob Source #
Create a value of TrainingJob
with all optional fields omitted.
Use generic-lens or optics to modify other optional fields.
The following record fields are available, with the corresponding lenses provided for backwards compatibility:
$sel:algorithmSpecification:TrainingJob'
, trainingJob_algorithmSpecification
- Information about the algorithm used for training, and algorithm
metadata.
$sel:autoMLJobArn:TrainingJob'
, trainingJob_autoMLJobArn
- The Amazon Resource Name (ARN) of the job.
$sel:billableTimeInSeconds:TrainingJob'
, trainingJob_billableTimeInSeconds
- The billable time in seconds.
$sel:checkpointConfig:TrainingJob'
, trainingJob_checkpointConfig
- Undocumented member.
$sel:creationTime:TrainingJob'
, trainingJob_creationTime
- A timestamp that indicates when the training job was created.
$sel:debugHookConfig:TrainingJob'
, trainingJob_debugHookConfig
- Undocumented member.
$sel:debugRuleConfigurations:TrainingJob'
, trainingJob_debugRuleConfigurations
- Information about the debug rule configuration.
$sel:debugRuleEvaluationStatuses:TrainingJob'
, trainingJob_debugRuleEvaluationStatuses
- Information about the evaluation status of the rules for the training
job.
$sel:enableInterContainerTrafficEncryption:TrainingJob'
, trainingJob_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.
$sel:enableManagedSpotTraining:TrainingJob'
, trainingJob_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.
$sel:enableNetworkIsolation:TrainingJob'
, trainingJob_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.
$sel:environment:TrainingJob'
, trainingJob_environment
- The environment variables to set in the Docker container.
$sel:experimentConfig:TrainingJob'
, trainingJob_experimentConfig
- Undocumented member.
$sel:failureReason:TrainingJob'
, trainingJob_failureReason
- If the training job failed, the reason it failed.
$sel:finalMetricDataList:TrainingJob'
, trainingJob_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.
$sel:hyperParameters:TrainingJob'
, trainingJob_hyperParameters
- Algorithm-specific parameters.
$sel:inputDataConfig:TrainingJob'
, trainingJob_inputDataConfig
- An array of Channel
objects that describes each data input channel.
$sel:labelingJobArn:TrainingJob'
, trainingJob_labelingJobArn
- The Amazon Resource Name (ARN) of the labeling job.
TrainingJob
, trainingJob_lastModifiedTime
- A timestamp that indicates when the status of the training job was last
modified.
$sel:modelArtifacts:TrainingJob'
, trainingJob_modelArtifacts
- Information about the Amazon S3 location that is configured for storing
model artifacts.
$sel:outputDataConfig:TrainingJob'
, trainingJob_outputDataConfig
- The S3 path where model artifacts that you configured when creating the
job are stored. SageMaker creates subfolders for model artifacts.
$sel:resourceConfig:TrainingJob'
, trainingJob_resourceConfig
- Resources, including ML compute instances and ML storage volumes, that
are configured for model training.
$sel:retryStrategy:TrainingJob'
, trainingJob_retryStrategy
- The number of times to retry the job when the job fails due to an
InternalServerError
.
$sel:roleArn:TrainingJob'
, trainingJob_roleArn
- The Amazon Web Services Identity and Access Management (IAM) role
configured for the training job.
$sel:secondaryStatus:TrainingJob'
, trainingJob_secondaryStatus
- Provides detailed information about the state of the training job. For
detailed information about the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
- -
Starting
- Starting the training job.Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes.Training
- Training is in progress.Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
- Completed
- -
Completed
- The training job has completed. - Failed
- -
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
. - Stopped
- -
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.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
$sel:secondaryStatusTransitions:TrainingJob'
, trainingJob_secondaryStatusTransitions
- A history of all of the secondary statuses that the training job has
transitioned through.
$sel:stoppingCondition:TrainingJob'
, trainingJob_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.
$sel:tags:TrainingJob'
, trainingJob_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.
$sel:tensorBoardOutputConfig:TrainingJob'
, trainingJob_tensorBoardOutputConfig
- Undocumented member.
$sel:trainingEndTime:TrainingJob'
, trainingJob_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.
$sel:trainingJobArn:TrainingJob'
, trainingJob_trainingJobArn
- The Amazon Resource Name (ARN) of the training job.
$sel:trainingJobName:TrainingJob'
, trainingJob_trainingJobName
- The name of the training job.
$sel:trainingJobStatus:TrainingJob'
, trainingJob_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 theFailureReason
field in the response to aDescribeTrainingJobResponse
call.Stopping
- The training job is stopping.Stopped
- The training job has stopped.
For more detailed information, see SecondaryStatus
.
$sel:trainingStartTime:TrainingJob'
, trainingJob_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.
$sel:trainingTimeInSeconds:TrainingJob'
, trainingJob_trainingTimeInSeconds
- The training time in seconds.
$sel:tuningJobArn:TrainingJob'
, trainingJob_tuningJobArn
- The Amazon Resource Name (ARN) of the associated hyperparameter tuning
job if the training job was launched by a hyperparameter tuning job.
$sel:vpcConfig:TrainingJob'
, trainingJob_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.
trainingJob_algorithmSpecification :: Lens' TrainingJob (Maybe AlgorithmSpecification) Source #
Information about the algorithm used for training, and algorithm metadata.
trainingJob_autoMLJobArn :: Lens' TrainingJob (Maybe Text) Source #
The Amazon Resource Name (ARN) of the job.
trainingJob_billableTimeInSeconds :: Lens' TrainingJob (Maybe Natural) Source #
The billable time in seconds.
trainingJob_checkpointConfig :: Lens' TrainingJob (Maybe CheckpointConfig) Source #
Undocumented member.
trainingJob_creationTime :: Lens' TrainingJob (Maybe UTCTime) Source #
A timestamp that indicates when the training job was created.
trainingJob_debugHookConfig :: Lens' TrainingJob (Maybe DebugHookConfig) Source #
Undocumented member.
trainingJob_debugRuleConfigurations :: Lens' TrainingJob (Maybe [DebugRuleConfiguration]) Source #
Information about the debug rule configuration.
trainingJob_debugRuleEvaluationStatuses :: Lens' TrainingJob (Maybe [DebugRuleEvaluationStatus]) Source #
Information about the evaluation status of the rules for the training job.
trainingJob_enableInterContainerTrafficEncryption :: Lens' TrainingJob (Maybe Bool) Source #
To encrypt all communications between ML compute instances in
distributed training, choose True
. Encryption provides greater
security for distributed training, but training might take longer. How
long it takes depends on the amount of communication between compute
instances, especially if you use a deep learning algorithm in
distributed training.
trainingJob_enableManagedSpotTraining :: Lens' TrainingJob (Maybe Bool) Source #
When true, enables managed spot training using Amazon EC2 Spot instances to run training jobs instead of on-demand instances. For more information, see Managed Spot Training.
trainingJob_enableNetworkIsolation :: Lens' TrainingJob (Maybe Bool) Source #
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_environment :: Lens' TrainingJob (Maybe (HashMap Text Text)) Source #
The environment variables to set in the Docker container.
trainingJob_experimentConfig :: Lens' TrainingJob (Maybe ExperimentConfig) Source #
Undocumented member.
trainingJob_failureReason :: Lens' TrainingJob (Maybe Text) Source #
If the training job failed, the reason it failed.
trainingJob_finalMetricDataList :: Lens' TrainingJob (Maybe [MetricData]) Source #
A list of final metric values that are set when the training job completes. Used only if the training job was configured to use metrics.
trainingJob_hyperParameters :: Lens' TrainingJob (Maybe (HashMap Text Text)) Source #
Algorithm-specific parameters.
trainingJob_inputDataConfig :: Lens' TrainingJob (Maybe (NonEmpty Channel)) Source #
An array of Channel
objects that describes each data input channel.
trainingJob_labelingJobArn :: Lens' TrainingJob (Maybe Text) Source #
The Amazon Resource Name (ARN) of the labeling job.
trainingJob_lastModifiedTime :: Lens' TrainingJob (Maybe UTCTime) Source #
A timestamp that indicates when the status of the training job was last modified.
trainingJob_modelArtifacts :: Lens' TrainingJob (Maybe ModelArtifacts) Source #
Information about the Amazon S3 location that is configured for storing model artifacts.
trainingJob_outputDataConfig :: Lens' TrainingJob (Maybe OutputDataConfig) Source #
The S3 path where model artifacts that you configured when creating the job are stored. SageMaker creates subfolders for model artifacts.
trainingJob_resourceConfig :: Lens' TrainingJob (Maybe ResourceConfig) Source #
Resources, including ML compute instances and ML storage volumes, that are configured for model training.
trainingJob_retryStrategy :: Lens' TrainingJob (Maybe RetryStrategy) Source #
The number of times to retry the job when the job fails due to an
InternalServerError
.
trainingJob_roleArn :: Lens' TrainingJob (Maybe Text) Source #
The Amazon Web Services Identity and Access Management (IAM) role configured for the training job.
trainingJob_secondaryStatus :: Lens' TrainingJob (Maybe SecondaryStatus) Source #
Provides detailed information about the state of the training job. For
detailed information about the secondary status of the training job, see
StatusMessage
under SecondaryStatusTransition.
SageMaker provides primary statuses and secondary statuses that apply to each of them:
- InProgress
- -
Starting
- Starting the training job.Downloading
- An optional stage for algorithms that supportFile
training input mode. It indicates that data is being downloaded to the ML storage volumes.Training
- Training is in progress.Uploading
- Training is complete and the model artifacts are being uploaded to the S3 location.
- Completed
- -
Completed
- The training job has completed. - Failed
- -
Failed
- The training job has failed. The reason for the failure is returned in theFailureReason
field ofDescribeTrainingJobResponse
. - Stopped
- -
MaxRuntimeExceeded
- The job stopped because it exceeded the maximum allowed runtime.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
trainingJob_secondaryStatusTransitions :: Lens' TrainingJob (Maybe [SecondaryStatusTransition]) Source #
A history of all of the secondary statuses that the training job has transitioned through.
trainingJob_stoppingCondition :: Lens' TrainingJob (Maybe StoppingCondition) Source #
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.
trainingJob_tags :: Lens' TrainingJob (Maybe [Tag]) Source #
An array of key-value pairs. You can use tags to categorize your Amazon Web Services resources in different ways, for example, by purpose, owner, or environment. For more information, see Tagging Amazon Web Services Resources.
trainingJob_tensorBoardOutputConfig :: Lens' TrainingJob (Maybe TensorBoardOutputConfig) Source #
Undocumented member.
trainingJob_trainingEndTime :: Lens' TrainingJob (Maybe UTCTime) Source #
Indicates the time when the training job ends on training instances. You
are billed for the time interval between the value of
TrainingStartTime
and this time. For successful jobs and stopped jobs,
this is the time after model artifacts are uploaded. For failed jobs,
this is the time when SageMaker detects a job failure.
trainingJob_trainingJobArn :: Lens' TrainingJob (Maybe Text) Source #
The Amazon Resource Name (ARN) of the training job.
trainingJob_trainingJobName :: Lens' TrainingJob (Maybe Text) Source #
The name of the training job.
trainingJob_trainingJobStatus :: Lens' TrainingJob (Maybe TrainingJobStatus) Source #
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 theFailureReason
field in the response to aDescribeTrainingJobResponse
call.Stopping
- The training job is stopping.Stopped
- The training job has stopped.
For more detailed information, see SecondaryStatus
.
trainingJob_trainingStartTime :: Lens' TrainingJob (Maybe UTCTime) Source #
Indicates the time when the training job starts on training instances.
You are billed for the time interval between this time and the value of
TrainingEndTime
. The start time in CloudWatch Logs might be later than
this time. The difference is due to the time it takes to download the
training data and to the size of the training container.
trainingJob_trainingTimeInSeconds :: Lens' TrainingJob (Maybe Natural) Source #
The training time in seconds.
trainingJob_tuningJobArn :: Lens' TrainingJob (Maybe Text) Source #
The Amazon Resource Name (ARN) of the associated hyperparameter tuning job if the training job was launched by a hyperparameter tuning job.
trainingJob_vpcConfig :: Lens' TrainingJob (Maybe VpcConfig) Source #
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.