SageMakerCreateTrainingJob.Builder (software.amazon.awscdk:aws-cdk-lib 2.0.0-rc.10 API)

java.lang.Object
- software.amazon.awscdk.services.stepfunctions.tasks.SageMakerCreateTrainingJob.Builder

All Implemented Interfaces:

software.amazon.jsii.Builder<SageMakerCreateTrainingJob>

Enclosing class:

SageMakerCreateTrainingJob
```
@Stability(value=Experimental)
public static final class SageMakerCreateTrainingJob.Builder
extends Object
implements software.amazon.jsii.Builder<SageMakerCreateTrainingJob>
```
(experimental) A fluent builder for SageMakerCreateTrainingJob.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`SageMakerCreateTrainingJob.Builder`	`algorithmSpecification(AlgorithmSpecification algorithmSpecification)` (experimental) Identifies the training algorithm to use.
`SageMakerCreateTrainingJob`	`build()`
`SageMakerCreateTrainingJob.Builder`	`comment(String comment)` (experimental) An optional description for this state.
`static SageMakerCreateTrainingJob.Builder`	`create(software.constructs.Construct scope, String id)`
`SageMakerCreateTrainingJob.Builder`	`heartbeat(Duration heartbeat)` (experimental) Timeout for the heartbeat.
`SageMakerCreateTrainingJob.Builder`	`hyperparameters(Map<String,? extends Object> hyperparameters)` (experimental) Algorithm-specific parameters that influence the quality of the model.
`SageMakerCreateTrainingJob.Builder`	`inputDataConfig(List<? extends Channel> inputDataConfig)` (experimental) Describes the various datasets (e.g.
`SageMakerCreateTrainingJob.Builder`	`inputPath(String inputPath)` (experimental) JSONPath expression to select part of the state to be the input to this state.
`SageMakerCreateTrainingJob.Builder`	`integrationPattern(IntegrationPattern integrationPattern)` (experimental) AWS Step Functions integrates with services directly in the Amazon States Language.
`SageMakerCreateTrainingJob.Builder`	`outputDataConfig(OutputDataConfig outputDataConfig)` (experimental) Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training.
`SageMakerCreateTrainingJob.Builder`	`outputPath(String outputPath)` (experimental) JSONPath expression to select select a portion of the state output to pass to the next state.
`SageMakerCreateTrainingJob.Builder`	`resourceConfig(ResourceConfig resourceConfig)` (experimental) Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.
`SageMakerCreateTrainingJob.Builder`	`resultPath(String resultPath)` (experimental) JSONPath expression to indicate where to inject the state's output.
`SageMakerCreateTrainingJob.Builder`	`resultSelector(Map<String,? extends Object> resultSelector)` (experimental) The JSON that will replace the state's raw result and become the effective result before ResultPath is applied.
`SageMakerCreateTrainingJob.Builder`	`role(IRole role)` (experimental) Role for the Training Job.
`SageMakerCreateTrainingJob.Builder`	`stoppingCondition(StoppingCondition stoppingCondition)` (experimental) Sets a time limit for training.
`SageMakerCreateTrainingJob.Builder`	`tags(Map<String,String> tags)` (experimental) Tags to be applied to the train job.
`SageMakerCreateTrainingJob.Builder`	`timeout(Duration timeout)` (experimental) Timeout for the state machine.
`SageMakerCreateTrainingJob.Builder`	`trainingJobName(String trainingJobName)` (experimental) Training Job Name.
`SageMakerCreateTrainingJob.Builder`	`vpcConfig(VpcConfig vpcConfig)` (experimental) Specifies the VPC that you want your training job to connect to.

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

- Method Detail
  - create
```
@Stability(value=Experimental)
public static SageMakerCreateTrainingJob.Builder create(software.constructs.Construct scope,
                                                                                       String id)
```
    Parameters:
    
    scope - This parameter is required.
    
    id - This parameter is required.
    
    Returns:
    
    a new instance of SageMakerCreateTrainingJob.Builder.
  - comment
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder comment(String comment)
```
    (experimental) An optional description for this state.
    Default: - No comment
    
    Parameters:
    
    comment - An optional description for this state. This parameter is required.
    
    Returns:
    
    this
  - heartbeat
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder heartbeat(Duration heartbeat)
```
    (experimental) Timeout for the heartbeat.
    Default: - None
    
    Parameters:
    
    heartbeat - Timeout for the heartbeat. This parameter is required.
    
    Returns:
    
    this
  - inputPath
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder inputPath(String inputPath)
```
    (experimental) 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 {}.
    Default: - The entire task input (JSON path '$')
    
    Parameters:
    
    inputPath - JSONPath expression to select part of the state to be the input to this state. This parameter is required.
    
    Returns:
    
    this
  - integrationPattern
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder integrationPattern(IntegrationPattern integrationPattern)
```
    (experimental) AWS Step Functions integrates with services directly in the Amazon States Language.
    You can control these AWS services using service integration patterns
    Default: IntegrationPattern.REQUEST_RESPONSE
    
    Parameters:
    
    integrationPattern - AWS Step Functions integrates with services directly in the Amazon States Language. This parameter is required.
    
    Returns:
    
    this
    
    See Also:
    
    https://docs.aws.amazon.com/step-functions/latest/dg/connect-to-resource.html#connect-wait-token
  - outputPath
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder outputPath(String outputPath)
```
    (experimental) JSONPath expression to select select a portion of the state output to pass to the next state.
    May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.
    Default: - The entire JSON node determined by the state input, the task result, and resultPath is passed to the next state (JSON path '$')
    
    Parameters:
    
    outputPath - JSONPath expression to select select a portion of the state output to pass to the next state. This parameter is required.
    
    Returns:
    
    this
  - resultPath
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder resultPath(String resultPath)
```
    (experimental) 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.
    Default: - Replaces the entire input with the result (JSON path '$')
    
    Parameters:
    
    resultPath - JSONPath expression to indicate where to inject the state's output. This parameter is required.
    
    Returns:
    
    this
  - resultSelector
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder resultSelector(Map<String,? extends Object> resultSelector)
```
    (experimental) 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.
    Default: - None
    
    Parameters:
    
    resultSelector - The JSON that will replace the state's raw result and become the effective result before ResultPath is applied. This parameter is required.
    
    Returns:
    
    this
    
    See Also:
    
    https://docs.aws.amazon.com/step-functions/latest/dg/input-output-inputpath-params.html#input-output-resultselector
  - timeout
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder timeout(Duration timeout)
```
    (experimental) Timeout for the state machine.
    Default: - None
    
    Parameters:
    
    timeout - Timeout for the state machine. This parameter is required.
    
    Returns:
    
    this
  - algorithmSpecification
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification)
```
    (experimental) Identifies the training algorithm to use.
    
    Parameters:
    
    algorithmSpecification - Identifies the training algorithm to use. This parameter is required.
    
    Returns:
    
    this
  - inputDataConfig
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder inputDataConfig(List<? extends Channel> inputDataConfig)
```
    (experimental) Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored.
    
    Parameters:
    
    inputDataConfig - Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored. This parameter is required.
    
    Returns:
    
    this
  - outputDataConfig
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder outputDataConfig(OutputDataConfig outputDataConfig)
```
    (experimental) Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training.
    
    Parameters:
    
    outputDataConfig - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training. This parameter is required.
    
    Returns:
    
    this
  - trainingJobName
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder trainingJobName(String trainingJobName)
```
    (experimental) Training Job Name.
    
    Parameters:
    
    trainingJobName - Training Job Name. This parameter is required.
    
    Returns:
    
    this
  - hyperparameters
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder hyperparameters(Map<String,? extends Object> hyperparameters)
```
    (experimental) Algorithm-specific parameters that influence the quality of the model.
    Set hyperparameters before you start the learning process. For a list of hyperparameters provided by Amazon SageMaker
    Default: - No hyperparameters
    
    Parameters:
    
    hyperparameters - Algorithm-specific parameters that influence the quality of the model. This parameter is required.
    
    Returns:
    
    this
    
    See Also:
    
    https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
  - resourceConfig
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder resourceConfig(ResourceConfig resourceConfig)
```
    (experimental) 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
    
    Parameters:
    
    resourceConfig - Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training. This parameter is required.
    
    Returns:
    
    this
  - role
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder role(IRole role)
```
    (experimental) Role for the Training Job.
    The role must be granted all necessary permissions for the SageMaker training job to be able to operate.
    See https://docs.aws.amazon.com/fr_fr/sagemaker/latest/dg/sagemaker-roles.html#sagemaker-roles-createtrainingjob-perms
    Default: - a role will be created.
    
    Parameters:
    
    role - Role for the Training Job. This parameter is required.
    
    Returns:
    
    this
  - stoppingCondition
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder stoppingCondition(StoppingCondition stoppingCondition)
```
    (experimental) Sets a time limit for training.
    Default: - max runtime of 1 hour
    
    Parameters:
    
    stoppingCondition - Sets a time limit for training. This parameter is required.
    
    Returns:
    
    this
  - tags
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder tags(Map<String,String> tags)
```
    (experimental) Tags to be applied to the train job.
    Default: - No tags
    
    Parameters:
    
    tags - Tags to be applied to the train job. This parameter is required.
    
    Returns:
    
    this
  - vpcConfig
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob.Builder vpcConfig(VpcConfig vpcConfig)
```
    (experimental) Specifies the VPC that you want your training job to connect to.
    Default: - No VPC
    
    Parameters:
    
    vpcConfig - Specifies the VPC that you want your training job to connect to. This parameter is required.
    
    Returns:
    
    this
  - build
```
@Stability(value=Experimental)
public SageMakerCreateTrainingJob build()
```
    Specified by:
    
    build in interface software.amazon.jsii.Builder<SageMakerCreateTrainingJob>

Class SageMakerCreateTrainingJob.Builder

Method Summary

Methods inherited from class java.lang.Object

Method Detail

create

comment

heartbeat

inputPath

integrationPattern

outputPath

resultPath

resultSelector

timeout

algorithmSpecification

inputDataConfig

outputDataConfig

trainingJobName

hyperparameters

resourceConfig

role

stoppingCondition

tags

vpcConfig

build