sagemaker_update_training_job: Update a model training job to request a new Debugger...

In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length

Description

Update a model training job to request a new Debugger profiling configuration or to change warm pool retention length.

See https://www.paws-r-sdk.com/docs/sagemaker_update_training_job/ for full documentation.

Usage

sagemaker_update_training_job(
  TrainingJobName,
  ProfilerConfig = NULL,
  ProfilerRuleConfigurations = NULL,
  ResourceConfig = NULL,
  RemoteDebugConfig = NULL
)

Arguments

TrainingJobName	[required] The name of a training job to update the Debugger profiling configuration.
ProfilerConfig	Configuration information for Amazon SageMaker Debugger system monitoring, framework profiling, and storage paths.
ProfilerRuleConfigurations	Configuration information for Amazon SageMaker Debugger rules for profiling system and framework metrics.
ResourceConfig	The training job ResourceConfig to update warm pool retention length.
RemoteDebugConfig	Configuration for remote debugging while the training job is running. You can update the remote debugging configuration when the SecondaryStatus of the job is Downloading or Training.To learn more about the remote debugging functionality of SageMaker, see Access a training container through Amazon Web Services Systems Manager (SSM) for remote debugging.

paws.machine.learning documentation built on Sept. 12, 2024, 6:23 a.m.