TrainingJobState class

Input properties used for looking up and filtering TrainingJob resources.

Constructors

TrainingJobState({Input<TrainingJobAlgorithmSpecification?>? algorithmSpecification, Input<String?>? arn, Input<TrainingJobCheckpointConfig?>? checkpointConfig, Input<TrainingJobDebugHookConfig?>? debugHookConfig, Input<List<TrainingJobDebugRuleConfiguration>?>? debugRuleConfigurations, Input<bool?>? deleteModelPackagesOnDestroy, Input<bool?>? deleteVpcEnisOnDestroy, Input<bool?>? enableInterContainerTrafficEncryption, Input<bool?>? enableManagedSpotTraining, Input<bool?>? enableNetworkIsolation, Input<Map<String, String>?>? environment, Input<TrainingJobExperimentConfig?>? experimentConfig, Input<Map<String, String>?>? hyperParameters, Input<TrainingJobInfraCheckConfig?>? infraCheckConfig, Input<List<TrainingJobInputDataConfig>?>? inputDataConfigs, Input<TrainingJobMlflowConfig?>? mlflowConfig, Input<TrainingJobModelPackageConfig?>? modelPackageConfig, Input<TrainingJobOutputDataConfig?>? outputDataConfig, Input<TrainingJobProfilerConfig?>? profilerConfig, Input<List<TrainingJobProfilerRuleConfiguration>?>? profilerRuleConfigurations, Input<String?>? region, Input<TrainingJobRemoteDebugConfig?>? remoteDebugConfig, Input<TrainingJobResourceConfig?>? resourceConfig, Input<TrainingJobRetryStrategy?>? retryStrategy, Input<String?>? roleArn, Input<TrainingJobServerlessJobConfig?>? serverlessJobConfig, Input<TrainingJobSessionChainingConfig?>? sessionChainingConfig, Input<TrainingJobStoppingCondition?>? stoppingCondition, Input<Map<String, String>?>? tags, Input<Map<String, String>?>? tagsAll, Input<TrainingJobTensorBoardOutputConfig?>? tensorBoardOutputConfig, Input<TrainingJobTimeouts?>? timeouts, Input<String?>? trainingJobName, Input<TrainingJobVpcConfig?>? vpcConfig})
Creates a new TrainingJobState. algorithmSpecification Algorithm-related parameters of the training job. See algorithmSpecification below. Conflicts with serverlessJobConfig. arn ARN of the Training Job. checkpointConfig Location of checkpoints during training. See checkpointConfig below. Conflicts with serverlessJobConfig. debugHookConfig Configuration for debugging rules. See debugHookConfig below. Conflicts with serverlessJobConfig. debugRuleConfigurations List of debug rule configurations. Maximum of 20. See debugRuleConfigurations below. deleteModelPackagesOnDestroy Whether to delete model packages in the configured model package group when the training job is destroyed. Default is false. deleteVpcEnisOnDestroy Whether to delete detached VPC ENIs SageMaker may leave behind when the training job is destroyed. Default is false. enableInterContainerTrafficEncryption Whether to encrypt inter-container traffic. When enabled, communications between containers are encrypted. enableManagedSpotTraining Whether to use managed spot training. Optimizes the cost of training by using Amazon EC2 Spot Instances. Conflicts with serverlessJobConfig. enableNetworkIsolation Whether to isolate the training container from the network. No inbound or outbound network calls can be made. environment Map of environment variables to set in the training container. Maximum of 100 entries. Conflicts with serverlessJobConfig. experimentConfig Associates a SageMaker AI Experiment or Trial to the training job. See experimentConfig below. Conflicts with serverlessJobConfig. hyperParameters Map of hyperparameters for the training algorithm. Maximum of 100 entries. infraCheckConfig Infrastructure health check configuration. See infraCheckConfig below. inputDataConfigs List of input data channel configurations for the training job. Maximum of 20. See inputDataConfig below. mlflowConfig MLflow integration configuration. See mlflowConfig below. modelPackageConfig Model package configuration. Requires serverlessJobConfig. See modelPackageConfig below. outputDataConfig Location of the output data from the training job. See outputDataConfig below. profilerConfig Configuration for the profiler. See profilerConfig below. Conflicts with serverlessJobConfig. profilerRuleConfigurations List of profiler rule configurations. Maximum of 20. See profilerRuleConfigurations below. Conflicts with serverlessJobConfig. region Region where this resource will be managed. Defaults to the Region set in the provider configuration. remoteDebugConfig Configuration for remote debugging. See remoteDebugConfig below. resourceConfig Resources for the training job, including compute instances and storage volumes. See resourceConfig below. retryStrategy Number of times to retry the job if it fails. See retryStrategy below. Conflicts with serverlessJobConfig. roleArn ARN of the IAM role that SageMaker AI assumes to perform tasks on your behalf during training. serverlessJobConfig Configuration for serverless training jobs using foundation models. Conflicts with algorithmSpecification, enableManagedSpotTraining, environment, retryStrategy, checkpointConfig, debugHookConfig, experimentConfig, profilerConfig, profilerRuleConfigurations, and tensorBoardOutputConfig. See serverlessJobConfig below. sessionChainingConfig Configuration for session tag chaining. See sessionChainingConfig below. stoppingCondition Optional. tags Map of tags to assign to the resource. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level. tagsAll Map of tags assigned to the resource, including those inherited from the provider defaultTags configuration block. tensorBoardOutputConfig Configuration for TensorBoard output. See tensorBoardOutputConfig below. Conflicts with serverlessJobConfig. timeouts Optional. trainingJobName Name of the training job. Must be between 1 and 63 characters, start with a letter or number, and contain only letters, numbers, and hyphens. vpcConfig VPC configuration for the training job. See vpcConfig below.
const
TrainingJobState.fromMap(Map<String, dynamic> map)
factory

Properties

algorithmSpecification → Input<TrainingJobAlgorithmSpecification?>?
Algorithm-related parameters of the training job. See algorithmSpecification below. Conflicts with serverlessJobConfig.
final
arn → Input<String?>?
ARN of the Training Job.
final
checkpointConfig → Input<TrainingJobCheckpointConfig?>?
Location of checkpoints during training. See checkpointConfig below. Conflicts with serverlessJobConfig.
final
debugHookConfig → Input<TrainingJobDebugHookConfig?>?
Configuration for debugging rules. See debugHookConfig below. Conflicts with serverlessJobConfig.
final
debugRuleConfigurations → Input<List<TrainingJobDebugRuleConfiguration>?>?
List of debug rule configurations. Maximum of 20. See debugRuleConfigurations below.
final
deleteModelPackagesOnDestroy → Input<bool?>?
Whether to delete model packages in the configured model package group when the training job is destroyed. Default is false.
final
deleteVpcEnisOnDestroy → Input<bool?>?
Whether to delete detached VPC ENIs SageMaker may leave behind when the training job is destroyed. Default is false.
final
enableInterContainerTrafficEncryption → Input<bool?>?
Whether to encrypt inter-container traffic. When enabled, communications between containers are encrypted.
final
enableManagedSpotTraining → Input<bool?>?
Whether to use managed spot training. Optimizes the cost of training by using Amazon EC2 Spot Instances. Conflicts with serverlessJobConfig.
final
enableNetworkIsolation → Input<bool?>?
Whether to isolate the training container from the network. No inbound or outbound network calls can be made.
final
environment → Input<Map<String, String>?>?
Map of environment variables to set in the training container. Maximum of 100 entries. Conflicts with serverlessJobConfig.
final
experimentConfig → Input<TrainingJobExperimentConfig?>?
Associates a SageMaker AI Experiment or Trial to the training job. See experimentConfig below. Conflicts with serverlessJobConfig.
final
hashCode → int
The hash code for this object.
no setterinherited
hyperParameters → Input<Map<String, String>?>?
Map of hyperparameters for the training algorithm. Maximum of 100 entries.
final
infraCheckConfig → Input<TrainingJobInfraCheckConfig?>?
Infrastructure health check configuration. See infraCheckConfig below.
final
inputDataConfigs → Input<List<TrainingJobInputDataConfig>?>?
List of input data channel configurations for the training job. Maximum of 20. See inputDataConfig below.
final
mlflowConfig → Input<TrainingJobMlflowConfig?>?
MLflow integration configuration. See mlflowConfig below.
final
modelPackageConfig → Input<TrainingJobModelPackageConfig?>?
Model package configuration. Requires serverlessJobConfig. See modelPackageConfig below.
final
outputDataConfig → Input<TrainingJobOutputDataConfig?>?
Location of the output data from the training job. See outputDataConfig below.
final
profilerConfig → Input<TrainingJobProfilerConfig?>?
Configuration for the profiler. See profilerConfig below. Conflicts with serverlessJobConfig.
final
profilerRuleConfigurations → Input<List<TrainingJobProfilerRuleConfiguration>?>?
List of profiler rule configurations. Maximum of 20. See profilerRuleConfigurations below. Conflicts with serverlessJobConfig.
final
region → Input<String?>?
Region where this resource will be managed. Defaults to the Region set in the provider configuration.
final
remoteDebugConfig → Input<TrainingJobRemoteDebugConfig?>?
Configuration for remote debugging. See remoteDebugConfig below.
final
resourceConfig → Input<TrainingJobResourceConfig?>?
Resources for the training job, including compute instances and storage volumes. See resourceConfig below.
final
retryStrategy → Input<TrainingJobRetryStrategy?>?
Number of times to retry the job if it fails. See retryStrategy below. Conflicts with serverlessJobConfig.
final
roleArn → Input<String?>?
ARN of the IAM role that SageMaker AI assumes to perform tasks on your behalf during training.
final
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
serverlessJobConfig → Input<TrainingJobServerlessJobConfig?>?
Configuration for serverless training jobs using foundation models. Conflicts with algorithmSpecification, enableManagedSpotTraining, environment, retryStrategy, checkpointConfig, debugHookConfig, experimentConfig, profilerConfig, profilerRuleConfigurations, and tensorBoardOutputConfig. See serverlessJobConfig below.
final
sessionChainingConfig → Input<TrainingJobSessionChainingConfig?>?
Configuration for session tag chaining. See sessionChainingConfig below.
final
stoppingCondition → Input<TrainingJobStoppingCondition?>?
final
tags → Input<Map<String, String>?>?
Map of tags to assign to the resource. If configured with a provider defaultTags configuration block present, tags with matching keys will overwrite those defined at the provider-level.
final
tagsAll → Input<Map<String, String>?>?
Map of tags assigned to the resource, including those inherited from the provider defaultTags configuration block.
final
tensorBoardOutputConfig → Input<TrainingJobTensorBoardOutputConfig?>?
Configuration for TensorBoard output. See tensorBoardOutputConfig below. Conflicts with serverlessJobConfig.
final
timeouts → Input<TrainingJobTimeouts?>?
final
trainingJobName → Input<String?>?
Name of the training job. Must be between 1 and 63 characters, start with a letter or number, and contain only letters, numbers, and hyphens.
final
vpcConfig → Input<TrainingJobVpcConfig?>?
VPC configuration for the training job. See vpcConfig below.
final

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toMap() → Map<String, dynamic>
toString() → String
A string representation of this object.
inherited

Operators

operator ==(Object other) → bool
The equality operator.
inherited