@Stability(value=Stable) public static final class SageMakerCreateTrainingJob.Builder extends Object implements software.amazon.jsii.Builder<SageMakerCreateTrainingJob>
SageMakerCreateTrainingJob.| Modifier and Type | Method and Description |
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SageMakerCreateTrainingJob.Builder |
algorithmSpecification(AlgorithmSpecification algorithmSpecification)
Identifies the training algorithm to use.
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SageMakerCreateTrainingJob |
build() |
SageMakerCreateTrainingJob.Builder |
comment(String comment)
An optional description for this state.
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static SageMakerCreateTrainingJob.Builder |
create(software.constructs.Construct scope,
String id) |
SageMakerCreateTrainingJob.Builder |
enableNetworkIsolation(Boolean enableNetworkIsolation)
Isolates the training container.
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SageMakerCreateTrainingJob.Builder |
environment(Map<String,String> environment)
Environment variables to set in the Docker container.
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SageMakerCreateTrainingJob.Builder |
heartbeat(Duration heartbeat)
Timeout for the heartbeat.
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SageMakerCreateTrainingJob.Builder |
hyperparameters(Map<String,? extends Object> hyperparameters)
Algorithm-specific parameters that influence the quality of the model.
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SageMakerCreateTrainingJob.Builder |
inputDataConfig(List<? extends Channel> inputDataConfig)
Describes the various datasets (e.g.
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SageMakerCreateTrainingJob.Builder |
inputPath(String inputPath)
JSONPath expression to select part of the state to be the input to this state.
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SageMakerCreateTrainingJob.Builder |
integrationPattern(IntegrationPattern integrationPattern)
AWS Step Functions integrates with services directly in the Amazon States Language.
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SageMakerCreateTrainingJob.Builder |
outputDataConfig(OutputDataConfig outputDataConfig)
Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training.
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SageMakerCreateTrainingJob.Builder |
outputPath(String outputPath)
JSONPath expression to select select a portion of the state output to pass to the next state.
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SageMakerCreateTrainingJob.Builder |
resourceConfig(ResourceConfig resourceConfig)
Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training.
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SageMakerCreateTrainingJob.Builder |
resultPath(String resultPath)
JSONPath expression to indicate where to inject the state's output.
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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.
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SageMakerCreateTrainingJob.Builder |
role(IRole role)
Role for the Training Job.
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SageMakerCreateTrainingJob.Builder |
stoppingCondition(StoppingCondition stoppingCondition)
Sets a time limit for training.
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SageMakerCreateTrainingJob.Builder |
tags(Map<String,String> tags)
Tags to be applied to the train job.
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SageMakerCreateTrainingJob.Builder |
timeout(Duration timeout)
Timeout for the state machine.
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SageMakerCreateTrainingJob.Builder |
trainingJobName(String trainingJobName)
Training Job Name.
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SageMakerCreateTrainingJob.Builder |
vpcConfig(VpcConfig vpcConfig)
Specifies the VPC that you want your training job to connect to.
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@Stability(value=Stable) public static SageMakerCreateTrainingJob.Builder create(software.constructs.Construct scope, String id)
scope - This parameter is required.id - This parameter is required.SageMakerCreateTrainingJob.Builder.@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder comment(String comment)
Default: - No comment
comment - An optional description for this state. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder heartbeat(Duration heartbeat)
Default: - None
heartbeat - Timeout for the heartbeat. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder inputPath(String inputPath)
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 '$')
inputPath - JSONPath expression to select part of the state to be the input to this state. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder integrationPattern(IntegrationPattern integrationPattern)
You can control these AWS services using service integration patterns
Default: - `IntegrationPattern.REQUEST_RESPONSE` for most tasks. `IntegrationPattern.RUN_JOB` for the following exceptions: `BatchSubmitJob`, `EmrAddStep`, `EmrCreateCluster`, `EmrTerminationCluster`, and `EmrContainersStartJobRun`.
integrationPattern - AWS Step Functions integrates with services directly in the Amazon States Language. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder outputPath(String outputPath)
May also be the special value JsonPath.DISCARD, which will cause the effective output to be the empty object {}.
Default: - The entire JSON node determined by the state input, the task result, and resultPath is passed to the next state (JSON path '$')
outputPath - JSONPath expression to select select a portion of the state output to pass to the next state. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder resultPath(String resultPath)
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 '$')
resultPath - JSONPath expression to indicate where to inject the state's output. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder resultSelector(Map<String,? extends Object> resultSelector)
You can use ResultSelector to create a payload with values that are static or selected from the state's raw result.
Default: - None
resultSelector - The JSON that will replace the state's raw result and become the effective result before ResultPath is applied. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder timeout(Duration timeout)
Default: - None
timeout - Timeout for the state machine. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder algorithmSpecification(AlgorithmSpecification algorithmSpecification)
algorithmSpecification - Identifies the training algorithm to use. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder inputDataConfig(List<? extends Channel> inputDataConfig)
inputDataConfig - Describes the various datasets (e.g. train, validation, test) and the Amazon S3 location where stored. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder outputDataConfig(OutputDataConfig outputDataConfig)
outputDataConfig - Identifies the Amazon S3 location where you want Amazon SageMaker to save the results of model training. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder trainingJobName(String trainingJobName)
trainingJobName - Training Job Name. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder enableNetworkIsolation(Boolean enableNetworkIsolation)
No inbound or outbound network calls can be made to or from the training container.
Default: false
enableNetworkIsolation - Isolates the training container. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder environment(Map<String,String> environment)
Default: - No environment variables
environment - Environment variables to set in the Docker container. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder hyperparameters(Map<String,? extends Object> hyperparameters)
Set hyperparameters before you start the learning process. For a list of hyperparameters provided by Amazon SageMaker
Default: - No hyperparameters
hyperparameters - Algorithm-specific parameters that influence the quality of the model. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder resourceConfig(ResourceConfig resourceConfig)
Default: - 1 instance of EC2 `M4.XLarge` with `10GB` volume
resourceConfig - Specifies the resources, ML compute instances, and ML storage volumes to deploy for model training. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder role(IRole role)
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.
role - Role for the Training Job. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder stoppingCondition(StoppingCondition stoppingCondition)
Default: - max runtime of 1 hour
stoppingCondition - Sets a time limit for training. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder tags(Map<String,String> tags)
Default: - No tags
tags - Tags to be applied to the train job. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob.Builder vpcConfig(VpcConfig vpcConfig)
Default: - No VPC
vpcConfig - Specifies the VPC that you want your training job to connect to. This parameter is required.this@Stability(value=Stable) public SageMakerCreateTrainingJob build()
build in interface software.amazon.jsii.Builder<SageMakerCreateTrainingJob>Copyright © 2022. All rights reserved.