SageMakerCreateTrainingJobJsonPathProps Struct
Properties for creating an Amazon SageMaker training job using JSONPath.
Example
ts
// The code below shows an example of how to instantiate this type.
// The values are placeholders you should change.
import * as cdk from 'aws-cdk-lib';
import { aws_ec2 as ec2 } from 'aws-cdk-lib';
import { aws_iam as iam } from 'aws-cdk-lib';
import { aws_kms as kms } from 'aws-cdk-lib';
import { aws_stepfunctions as stepfunctions } from 'aws-cdk-lib';
import { aws_stepfunctions_tasks as stepfunctions_tasks } from 'aws-cdk-lib';
declare const assign: any;
declare const dockerImage: stepfunctions_tasks.DockerImage;
declare const hyperparameters: any;
declare const instanceType: ec2.InstanceType;
declare const key: kms.Key;
declare const resultSelector: any;
declare const role: iam.Role;
declare const s3Location: stepfunctions_tasks.S3Location;
declare const size: cdk.Size;
declare const subnet: ec2.Subnet;
declare const subnetFilter: ec2.SubnetFilter;
declare const taskRole: stepfunctions.TaskRole;
declare const timeout: stepfunctions.Timeout;
declare const vpc: ec2.Vpc;
const sageMakerCreateTrainingJobJsonPathProps: stepfunctions_tasks.SageMakerCreateTrainingJobJsonPathProps = {
algorithmSpecification: {
algorithmName: 'algorithmName',
metricDefinitions: [{
name: 'name',
regex: 'regex',
}],
trainingImage: dockerImage,
trainingInputMode: stepfunctions_tasks.InputMode.PIPE,
},
outputDataConfig: {
s3OutputLocation: s3Location,
// the properties below are optional
encryptionKey: key,
},
trainingJobName: 'trainingJobName',
// the properties below are optional
assign: {
assignKey: assign,
},
comment: 'comment',
credentials: {
role: taskRole,
},
enableNetworkIsolation: false,
environment: {
environmentKey: 'environment',
},
heartbeat: cdk.Duration.minutes(30),
heartbeatTimeout: timeout,
hyperparameters: {
hyperparametersKey: hyperparameters,
},
inputDataConfig: [{
channelName: 'channelName',
dataSource: {
s3DataSource: {
s3Location: s3Location,
// the properties below are optional
attributeNames: ['attributeNames'],
s3DataDistributionType: stepfunctions_tasks.S3DataDistributionType.FULLY_REPLICATED,
s3DataType: stepfunctions_tasks.S3DataType.MANIFEST_FILE,
},
},
// the properties below are optional
compressionType: stepfunctions_tasks.CompressionType.NONE,
contentType: 'contentType',
inputMode: stepfunctions_tasks.InputMode.PIPE,
recordWrapperType: stepfunctions_tasks.RecordWrapperType.NONE,
shuffleConfig: {
seed: 123,
},
}],
inputPath: 'inputPath',
integrationPattern: stepfunctions.IntegrationPattern.REQUEST_RESPONSE,
outputPath: 'outputPath',
queryLanguage: stepfunctions.QueryLanguage.JSON_PATH,
resourceConfig: {
instanceCount: 123,
instanceType: instanceType,
volumeSize: size,
// the properties below are optional
volumeEncryptionKey: key,
},
resultPath: 'resultPath',
resultSelector: {
resultSelectorKey: resultSelector,
},
role: role,
stateName: 'stateName',
stoppingCondition: {
maxRuntime: cdk.Duration.minutes(30),
},
tags: {
tagsKey: 'tags',
},
taskTimeout: timeout,
timeout: cdk.Duration.minutes(30),
vpcConfig: {
vpc: vpc,
// the properties below are optional
subnets: {
availabilityZones: ['availabilityZones'],
onePerAz: false,
subnetFilters: [subnetFilter],
subnetGroupName: 'subnetGroupName',
subnets: [subnet],
subnetType: ec2.SubnetType.PRIVATE_ISOLATED,
},
},
};
Properties
algorithmSpecificationAlgorithmSpecificationalgorithm_specificationAlgorithmSpecificationalgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationAlgorithmSpecificationrequired#Identifies the training algorithm to use.
assignoptional{ [key: string]: any }assignoptionaltyping.Mapping[str, Any]assignoptionalMap<String, Object>AssignoptionalIDictionary<string, object>Assignoptional*map[string]interface{}#Workflow variables to store in this step.
Default: Not assign variables
Using workflow variables, you can store data in a step and retrieve that data in future steps.
commentoptionalstringcommentoptionalstrcommentoptionalStringCommentoptionalstringCommentoptional*string#A comment describing this state.
Default: No comment
credentialsoptionalCredentialscredentialsoptionalCredentialscredentialsoptionalCredentialsCredentialsoptionalCredentialsCredentialsoptionalCredentials#Credentials for an IAM Role that the State Machine assumes for executing the task.
Default: None (Task is executed using the State Machine's execution role)
This enables cross-account resource invocations.
enableNetworkIsolationoptionalbooleanenable_network_isolationoptionalboolenableNetworkIsolationoptionalBooleanEnableNetworkIsolationoptionalboolEnableNetworkIsolationoptional*bool= false#Isolates the training container.
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#Environment variables to set in the Docker container.
Default: No environment variables
heartbeatoptionalDurationheartbeatoptionalDurationheartbeatoptionalDurationHeartbeatoptionalDurationHeartbeatoptionalDuration= Nonedeprecated#use `heartbeatTimeout`
heartbeatTimeoutoptionalTimeoutheartbeat_timeoutoptionalTimeoutheartbeatTimeoutoptionalTimeoutHeartbeatTimeoutoptionalTimeoutHeartbeatTimeoutoptionalTimeout= None#Timeout for the heartbeat.
[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{}#Algorithm-specific parameters that influence the quality of the model.
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#Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored.
Default: No inputDataConfig
inputPathoptionalstringinput_pathoptionalstrinputPathoptionalStringInputPathoptionalstringInputPathoptional*string= $#JSONPath expression to select part of the state to be the input to this state.
May also be the special value JsonPath.DISCARD, which will cause the effective input to be the empty object {}.
integrationPatternoptionalIntegrationPatternintegration_patternoptionalIntegrationPatternintegrationPatternoptionalIntegrationPatternIntegrationPatternoptionalIntegrationPatternIntegrationPatternoptionalIntegrationPattern#AWS Step Functions integrates with services directly in the Amazon States Language.
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#Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training.
outputPathoptionalstringoutput_pathoptionalstroutputPathoptionalStringOutputPathoptionalstringOutputPathoptional*string= $#JSONPath expression to select part of the state to be the output to this state.
May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.
queryLanguageoptionalQueryLanguagequery_languageoptionalQueryLanguagequeryLanguageoptionalQueryLanguageQueryLanguageoptionalQueryLanguageQueryLanguageoptionalQueryLanguage= JSONPath#The name of the query language used by the state.
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#Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.
Default: 1 instance of EC2 M4.XLarge with 10GB volume
resultPathoptionalstringresult_pathoptionalstrresultPathoptionalStringResultPathoptionalstringResultPathoptional*string= $#JSONPath expression to indicate where to inject the state's output.
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#The JSON that will replace the state's raw result and become the effective result before ResultPath is applied.
You can use ResultSelector to create a payload with values that are static or selected from the state's raw result.
Role for the Training Job.
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#Optional name for this state.
Default: The construct ID will be used as state name
stoppingConditionoptionalStoppingConditionstopping_conditionoptionalStoppingConditionstoppingConditionoptionalStoppingConditionStoppingConditionoptionalStoppingConditionStoppingConditionoptionalStoppingCondition#Sets a time limit for training.
Default: max runtime of 1 hour
tagsoptional{ [key: string]: string }tagsoptionaltyping.Mapping[str, str]tagsoptionalMap<String, String>TagsoptionalIDictionary<string, string>Tagsoptional*map[string]*string#Tags to be applied to the train job.
Default: No tags
taskTimeoutoptionalTimeouttask_timeoutoptionalTimeouttaskTimeoutoptionalTimeoutTaskTimeoutoptionalTimeoutTaskTimeoutoptionalTimeout= None#Timeout for the task.
[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface
timeoutoptionalDurationtimeoutoptionalDurationtimeoutoptionalDurationTimeoutoptionalDurationTimeoutoptionalDuration= Nonedeprecated#use `taskTimeout`
trainingJobNamestringtraining_job_namestrtrainingJobNameStringTrainingJobNamestringTrainingJobName*stringrequired#Training Job Name.