SageMakerCreateTrainingJobProps Struct
Properties for creating an Amazon SageMaker training job.
Example
new tasks.SageMakerCreateTrainingJob(this, 'TrainSagemaker', {
trainingJobName: sfn.JsonPath.stringAt('$.JobName'),
algorithmSpecification: {
algorithmName: 'BlazingText',
trainingInputMode: tasks.InputMode.FILE,
},
inputDataConfig: [{
channelName: 'train',
dataSource: {
s3DataSource: {
s3DataType: tasks.S3DataType.S3_PREFIX,
s3Location: tasks.S3Location.fromJsonExpression('$.S3Bucket'),
},
},
}],
outputDataConfig: {
s3OutputLocation: tasks.S3Location.fromBucket(s3.Bucket.fromBucketName(this, 'Bucket', 'amzn-s3-demo-bucket'), 'myoutputpath'),
},
resourceConfig: {
instanceCount: 1,
instanceType: new ec2.InstanceType(sfn.JsonPath.stringAt('$.InstanceType')),
volumeSize: Size.gibibytes(50),
}, // optional: default is 1 instance of EC2 `M4.XLarge` with `10GB` volume
stoppingCondition: {
maxRuntime: Duration.hours(2),
}, // optional: default is 1 hour
});
Properties
algorithmSpecificationAlgorithmSpecificationalgorithm_specificationAlgorithmSpecificationalgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationrequired#assignoptional{ [key: string]: any }assignoptionaltyping.Mapping[str, Any]assignoptionalMap<String, Object>AssignoptionalIDictionary<string, object>Assignoptional*map[string]interface{}#Default: Not assign variables
Using workflow variables, you can store data in a step and retrieve that data in future steps.
commentoptionalstringcommentoptionalstrcommentoptionalStringCommentoptionalstringCommentoptional*string#Default: No comment
credentialsoptionalCredentialscredentialsoptionalCredentialscredentialsoptionalCredentialsCredentialsoptionalCredentialsCredentialsoptionalCredentials#Default: None (Task is executed using the State Machine's execution role)
This enables cross-account resource invocations.
enableNetworkIsolationoptionalbooleanenable_network_isolationoptionalboolenableNetworkIsolationoptionalBooleanEnableNetworkIsolationoptionalboolEnableNetworkIsolationoptional*bool= false#No inbound or outbound network calls can be made to or from the training container.
environmentoptional{ [key: string]: string }environmentoptionaltyping.Mapping[str, str]environmentoptionalMap<String, String>EnvironmentoptionalIDictionary<string, string>Environmentoptional*map[string]*string#Default: No environment variables
heartbeatoptionalDurationheartbeatoptionalDurationheartbeatoptionalDurationHeartbeatoptionalDurationHeartbeatoptionalDuration= Nonedeprecated#heartbeatTimeoutoptionalTimeoutheartbeat_timeoutoptionalTimeoutheartbeatTimeoutoptionalTimeoutHeartbeatTimeoutoptionalTimeoutHeartbeatTimeoutoptionalTimeout= None#[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface
hyperparametersoptional{ [key: string]: any }hyperparametersoptionaltyping.Mapping[str, Any]hyperparametersoptionalMap<String, Object>HyperparametersoptionalIDictionary<string, object>Hyperparametersoptional*map[string]interface{}#Default: No hyperparameters
Set hyperparameters before you start the learning process. For a list of hyperparameters provided by Amazon SageMaker
inputDataConfigoptionalChannel[]input_data_configoptionaltyping.List[Channel]inputDataConfigoptionalList<Channel>InputDataConfigoptionalChannel[]InputDataConfigoptional*[]Channel#Default: No inputDataConfig
inputPathoptionalstringinput_pathoptionalstrinputPathoptionalStringInputPathoptionalstringInputPathoptional*string= $#May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}.
integrationPatternoptionalIntegrationPatternintegration_patternoptionalIntegrationPatternintegrationPatternoptionalIntegrationPatternIntegrationPatternoptionalIntegrationPatternIntegrationPatternoptionalIntegrationPattern#Default: IntegrationPattern.REQUEST_RESPONSE for most tasks. IntegrationPattern.RUN_JOB for the following exceptions: BatchSubmitJob, EmrAddStep, EmrCreateCluster, EmrTerminationCluster, and EmrContainersStartJobRun.
You can control these AWS services using service integration patterns.
Depending on the AWS Service, the Service Integration Pattern availability will vary.
outputDataConfigOutputDataConfigoutput_data_configOutputDataConfigoutputDataConfigOutputDataConfigOutputDataConfigOutputDataConfigOutputDataConfigOutputDataConfigrequired#outputPathoptionalstringoutput_pathoptionalstroutputPathoptionalStringOutputPathoptionalstringOutputPathoptional*string= $#May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.
outputsoptionalanyoutputsoptionalAnyoutputsoptionalObjectOutputsoptionalobjectOutputsoptionalinterface{}#Default: $states.result or $states.errorOutput
notes
When specified, the value overrides the state output default. The output field accepts any JSON value (object, array, string, number, boolean, null). Any string value, including those inside objects or arrays, will be evaluated as JSONata if surrounded by {% %} characters. Output also accepts a JSONata expression directly.
queryLanguageoptionalQueryLanguagequery_languageoptionalQueryLanguagequeryLanguageoptionalQueryLanguageQueryLanguageoptionalQueryLanguageQueryLanguageoptionalQueryLanguage= JSONPath#If the state does not contain a queryLanguage field, then it will use the query language specified in the top-level queryLanguage field.
resourceConfigoptionalResourceConfigresource_configoptionalResourceConfigresourceConfigoptionalResourceConfigResourceConfigoptionalResourceConfigResourceConfigoptionalResourceConfig#Default: 1 instance of EC2 M4.XLarge with 10GB volume
resultPathoptionalstringresult_pathoptionalstrresultPathoptionalStringResultPathoptionalstringResultPathoptional*string= $#May also be the special value JsonPath.DISCARD, which will cause the state's input to become its output.
resultSelectoroptional{ [key: string]: any }result_selectoroptionaltyping.Mapping[str, Any]resultSelectoroptionalMap<String, Object>ResultSelectoroptionalIDictionary<string, object>ResultSelectoroptional*map[string]interface{}= None#You can use ResultSelector to create a payload with values that are static or selected from the state's raw result.
Default: a role will be created.
The role must be granted all necessary permissions for the SageMaker training job to be able to operate.
stateNameoptionalstringstate_nameoptionalstrstateNameoptionalStringStateNameoptionalstringStateNameoptional*string#Default: The construct ID will be used as state name
stoppingConditionoptionalStoppingConditionstopping_conditionoptionalStoppingConditionstoppingConditionoptionalStoppingConditionStoppingConditionoptionalStoppingConditionStoppingConditionoptionalStoppingCondition#Default: max runtime of 1 hour
tagsoptional{ [key: string]: string }tagsoptionaltyping.Mapping[str, str]tagsoptionalMap<String, String>TagsoptionalIDictionary<string, string>Tagsoptional*map[string]*string#Default: No tags
taskTimeoutoptionalTimeouttask_timeoutoptionalTimeouttaskTimeoutoptionalTimeoutTaskTimeoutoptionalTimeoutTaskTimeoutoptionalTimeout= None#[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface
timeoutoptionalDurationtimeoutoptionalDurationtimeoutoptionalDurationTimeoutoptionalDurationTimeoutoptionalDuration= Nonedeprecated#trainingJobNamestringtraining_job_namestrtrainingJobNameStringTrainingJobNamestringTrainingJobName*stringrequired#