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[ aws . sagemaker ]



Update a model training job to request a new Debugger profiling configuration.

See also: AWS API Documentation

See 'aws help' for descriptions of global parameters.


--training-job-name <value>
[--profiler-config <value>]
[--profiler-rule-configurations <value>]
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]


--training-job-name (string)

The name of a training job to update the Debugger profiling configuration.

--profiler-config (structure)

Configuration information for Debugger system monitoring, framework profiling, and storage paths.

S3OutputPath -> (string)

Path to Amazon S3 storage location for system and framework metrics.

ProfilingIntervalInMilliseconds -> (long)

A time interval for capturing system metrics in milliseconds. Available values are 100, 200, 500, 1000 (1 second), 5000 (5 seconds), and 60000 (1 minute) milliseconds. The default value is 500 milliseconds.

ProfilingParameters -> (map)

Configuration information for capturing framework metrics. Available key strings for different profiling options are DetailedProfilingConfig , PythonProfilingConfig , and DataLoaderProfilingConfig . The following codes are configuration structures for the ProfilingParameters parameter. To learn more about how to configure the ProfilingParameters parameter, see Use the SageMaker and Debugger Configuration API Operations to Create, Update, and Debug Your Training Job .

key -> (string)

value -> (string)

DisableProfiler -> (boolean)

To disable Debugger monitoring and profiling, set to True .

Shorthand Syntax:


JSON Syntax:

  "S3OutputPath": "string",
  "ProfilingIntervalInMilliseconds": long,
  "ProfilingParameters": {"string": "string"
  "DisableProfiler": true|false

--profiler-rule-configurations (list)

Configuration information for Debugger rules for profiling system and framework metrics.


Configuration information for profiling rules.

RuleConfigurationName -> (string)

The name of the rule configuration. It must be unique relative to other rule configuration names.

LocalPath -> (string)

Path to local storage location for output of rules. Defaults to /opt/ml/processing/output/rule/ .

S3OutputPath -> (string)

Path to Amazon S3 storage location for rules.

RuleEvaluatorImage -> (string)

The Amazon Elastic Container (ECR) Image for the managed rule evaluation.

InstanceType -> (string)

The instance type to deploy a Debugger custom rule for profiling a training job.

VolumeSizeInGB -> (integer)

The size, in GB, of the ML storage volume attached to the processing instance.

RuleParameters -> (map)

Runtime configuration for rule container.

key -> (string)

value -> (string)

Shorthand Syntax:

RuleConfigurationName=string,LocalPath=string,S3OutputPath=string,RuleEvaluatorImage=string,InstanceType=string,VolumeSizeInGB=integer,RuleParameters={KeyName1=string,KeyName2=string} ...

JSON Syntax:

    "RuleConfigurationName": "string",
    "LocalPath": "string",
    "S3OutputPath": "string",
    "RuleEvaluatorImage": "string",
    "InstanceType": "ml.t3.medium"|"ml.t3.large"|"ml.t3.xlarge"|"ml.t3.2xlarge"|"ml.m4.xlarge"|"ml.m4.2xlarge"|"ml.m4.4xlarge"|"ml.m4.10xlarge"|"ml.m4.16xlarge"|"ml.c4.xlarge"|"ml.c4.2xlarge"|"ml.c4.4xlarge"|"ml.c4.8xlarge"|"ml.p2.xlarge"|"ml.p2.8xlarge"|"ml.p2.16xlarge"|"ml.p3.2xlarge"|"ml.p3.8xlarge"|"ml.p3.16xlarge"|"ml.c5.xlarge"|"ml.c5.2xlarge"|"ml.c5.4xlarge"|"ml.c5.9xlarge"|"ml.c5.18xlarge"|"ml.m5.large"|"ml.m5.xlarge"|"ml.m5.2xlarge"|"ml.m5.4xlarge"|"ml.m5.12xlarge"|"ml.m5.24xlarge"|"ml.r5.large"|"ml.r5.xlarge"|"ml.r5.2xlarge"|"ml.r5.4xlarge"|"ml.r5.8xlarge"|"ml.r5.12xlarge"|"ml.r5.16xlarge"|"ml.r5.24xlarge"|"ml.g4dn.xlarge"|"ml.g4dn.2xlarge"|"ml.g4dn.4xlarge"|"ml.g4dn.8xlarge"|"ml.g4dn.12xlarge"|"ml.g4dn.16xlarge",
    "VolumeSizeInGB": integer,
    "RuleParameters": {"string": "string"

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See 'aws help' for descriptions of global parameters.


TrainingJobArn -> (string)

The Amazon Resource Name (ARN) of the training job.