Class SageMakerCreateTrainingJob.Builder
- All Implemented Interfaces:
software.amazon.jsii.Builder<SageMakerCreateTrainingJob>
- Enclosing class:
SageMakerCreateTrainingJob
SageMakerCreateTrainingJob
.-
Method Summary
Modifier and TypeMethodDescriptionalgorithmSpecification
(AlgorithmSpecification algorithmSpecification) Identifies the training algorithm to use.build()
An optional description for this state.credentials
(Credentials credentials) Credentials for an IAM Role that the State Machine assumes for executing the task.enableNetworkIsolation
(Boolean enableNetworkIsolation) Isolates the training container.environment
(Map<String, String> environment) Environment variables to set in the Docker container.Deprecated.heartbeatTimeout
(Timeout heartbeatTimeout) Timeout for the heartbeat.hyperparameters
(Map<String, ? extends Object> hyperparameters) Algorithm-specific parameters that influence the quality of the model.inputDataConfig
(List<? extends Channel> inputDataConfig) Describes the various datasets (e.g.JSONPath expression to select part of the state to be the input to this state.integrationPattern
(IntegrationPattern integrationPattern) AWS Step Functions integrates with services directly in the Amazon States Language.outputDataConfig
(OutputDataConfig outputDataConfig) Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training.outputPath
(String outputPath) JSONPath expression to select select a portion of the state output to pass to the next state.resourceConfig
(ResourceConfig resourceConfig) Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.resultPath
(String resultPath) JSONPath expression to indicate where to inject the state's output.resultSelector
(Map<String, ? extends Object> resultSelector) The JSON that will replace the state's raw result and become the effective result before ResultPath is applied.Role for the Training Job.Optional name for this state.stoppingCondition
(StoppingCondition stoppingCondition) Sets a time limit for training.Tags to be applied to the train job.taskTimeout
(Timeout taskTimeout) Timeout for the task.Deprecated.usetaskTimeout
trainingJobName
(String trainingJobName) Training Job Name.Specifies the VPC that you want your training job to connect to.
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Method Details
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create
@Stability(Stable) public static SageMakerCreateTrainingJob.Builder create(software.constructs.Construct scope, String id) - Parameters:
scope
- This parameter is required.id
- Descriptive identifier for this chainable. This parameter is required.- Returns:
- a new instance of
SageMakerCreateTrainingJob.Builder
.
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comment
An optional description for this state.Default: - No comment
- Parameters:
comment
- An optional description for this state. This parameter is required.- Returns:
this
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credentials
Credentials for an IAM Role that the State Machine assumes for executing the task.This enables cross-account resource invocations.
Default: - None (Task is executed using the State Machine's execution role)
- Parameters:
credentials
- Credentials for an IAM Role that the State Machine assumes for executing the task. This parameter is required.- Returns:
this
- See Also:
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heartbeat
@Stability(Deprecated) @Deprecated public SageMakerCreateTrainingJob.Builder heartbeat(Duration heartbeat) Deprecated.useheartbeatTimeout
(deprecated) Timeout for the heartbeat.Default: - None
- Parameters:
heartbeat
- Timeout for the heartbeat. This parameter is required.- Returns:
this
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heartbeatTimeout
@Stability(Stable) public SageMakerCreateTrainingJob.Builder heartbeatTimeout(Timeout heartbeatTimeout) Timeout for the heartbeat.[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface
Default: - None
- Parameters:
heartbeatTimeout
- Timeout for the heartbeat. This parameter is required.- Returns:
this
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inputPath
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 '$')
- Parameters:
inputPath
- JSONPath expression to select part of the state to be the input to this state. This parameter is required.- Returns:
this
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integrationPattern
@Stability(Stable) public SageMakerCreateTrainingJob.Builder integrationPattern(IntegrationPattern integrationPattern) AWS Step Functions integrates with services directly in the Amazon States Language.You can control these AWS services using service integration patterns.
Depending on the AWS Service, the Service Integration Pattern availability will vary.
Default: - `IntegrationPattern.REQUEST_RESPONSE` for most tasks. `IntegrationPattern.RUN_JOB` for the following exceptions: `BatchSubmitJob`, `EmrAddStep`, `EmrCreateCluster`, `EmrTerminationCluster`, and `EmrContainersStartJobRun`.
- Parameters:
integrationPattern
- AWS Step Functions integrates with services directly in the Amazon States Language. This parameter is required.- Returns:
this
- See Also:
-
outputPath
JSONPath expression to select select a portion of the state output to pass to the next state.May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.
Default: - The entire JSON node determined by the state input, the task result, and resultPath is passed to the next state (JSON path '$')
- 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
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resultPath
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
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resultSelector
@Stability(Stable) public SageMakerCreateTrainingJob.Builder resultSelector(Map<String, ? extends Object> resultSelector) 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:
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stateName
Optional name for this state.Default: - The construct ID will be used as state name
- Parameters:
stateName
- Optional name for this state. This parameter is required.- Returns:
this
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taskTimeout
Timeout for the task.[disable-awslint:duration-prop-type] is needed because all props interface in aws-stepfunctions-tasks extend this interface
Default: - None
- Parameters:
taskTimeout
- Timeout for the task. This parameter is required.- Returns:
this
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timeout
@Stability(Deprecated) @Deprecated public SageMakerCreateTrainingJob.Builder timeout(Duration timeout) Deprecated.usetaskTimeout
(deprecated) Timeout for the task.Default: - None
- Parameters:
timeout
- Timeout for the task. This parameter is required.- Returns:
this
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algorithmSpecification
@Stability(Stable) public SageMakerCreateTrainingJob.Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification) Identifies the training algorithm to use.- Parameters:
algorithmSpecification
- Identifies the training algorithm to use. This parameter is required.- Returns:
this
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outputDataConfig
@Stability(Stable) public SageMakerCreateTrainingJob.Builder outputDataConfig(OutputDataConfig outputDataConfig) 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
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trainingJobName
@Stability(Stable) public SageMakerCreateTrainingJob.Builder trainingJobName(String trainingJobName) Training Job Name.- Parameters:
trainingJobName
- Training Job Name. This parameter is required.- Returns:
this
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enableNetworkIsolation
@Stability(Stable) public SageMakerCreateTrainingJob.Builder enableNetworkIsolation(Boolean enableNetworkIsolation) Isolates the training container.No inbound or outbound network calls can be made to or from the training container.
Default: false
- Parameters:
enableNetworkIsolation
- Isolates the training container. This parameter is required.- Returns:
this
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environment
@Stability(Stable) public SageMakerCreateTrainingJob.Builder environment(Map<String, String> environment) Environment variables to set in the Docker container.Default: - No environment variables
- Parameters:
environment
- Environment variables to set in the Docker container. This parameter is required.- Returns:
this
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hyperparameters
@Stability(Stable) public SageMakerCreateTrainingJob.Builder hyperparameters(Map<String, ? extends Object> hyperparameters) 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:
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inputDataConfig
@Stability(Stable) public SageMakerCreateTrainingJob.Builder inputDataConfig(List<? extends Channel> inputDataConfig) Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored.Default: - No inputDataConfig
- Parameters:
inputDataConfig
- Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored. This parameter is required.- Returns:
this
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resourceConfig
@Stability(Stable) public SageMakerCreateTrainingJob.Builder resourceConfig(ResourceConfig resourceConfig) 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
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role
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
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stoppingCondition
@Stability(Stable) public SageMakerCreateTrainingJob.Builder stoppingCondition(StoppingCondition stoppingCondition) 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
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tags
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
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vpcConfig
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
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build
- Specified by:
build
in interfacesoftware.amazon.jsii.Builder<SageMakerCreateTrainingJob>
- Returns:
- a newly built instance of
SageMakerCreateTrainingJob
.
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heartbeatTimeout