Clean Up Amazon SageMaker Experiment Resources

To avoid incurring unnecessary charges, delete the Amazon SageMaker Experiment resources you no longer need. You can't delete Experiment resources through the SageMaker Management Console or the Amazon SageMaker Studio UI. This topic shows you how to clean up these resources using the SageMaker Python SDK, Boto3, and the Experiments SDK.

Clean Up Using the SageMaker Python SDK (Recommended)

To clean up using the SageMaker Python SDK

from sagemaker.experiments.experiment import Experiment

exp = Experiment.load(experiment_name=experiment_name, sagemaker_session=sm_session)
exp._delete_all(action="--force")

Clean Up Using the Python SDK (Boto3)

To clean up using Boto 3

import boto3
sm = boto3.Session().client('sagemaker')

Define cleanup_boto3

def cleanup_boto3(experiment_name):
    trials = sm.list_trials(ExperimentName=experiment_name)['TrialSummaries']
    print('TrialNames:')
    for trial in trials:
        trial_name = trial['TrialName']
        print(f"\n{trial_name}")

        components_in_trial = sm.list_trial_components(TrialName=trial_name)
        print('\tTrialComponentNames:')
        for component in components_in_trial['TrialComponentSummaries']:
            component_name = component['TrialComponentName']
            print(f"\t{component_name}")
            sm.disassociate_trial_component(TrialComponentName=component_name, TrialName=trial_name)
            try:
                # comment out to keep trial components
                sm.delete_trial_component(TrialComponentName=component_name)
            except:
                # component is associated with another trial
                continue
            # to prevent throttling
            time.sleep(.5)
        sm.delete_trial(TrialName=trial_name)
    sm.delete_experiment(ExperimentName=experiment_name)
    print(f"\nExperiment {experiment_name} deleted")

Call cleanup_boto3

# Use experiment name not display name
experiment_name = "experiment-name"
cleanup_boto3(experiment_name)

Clean Up Using the Experiments SDK

To clean up using the Experiments SDK

import sys
!{sys.executable} -m pip install sagemaker-experiments

import time

from smexperiments.experiment import Experiment
from smexperiments.trial import Trial
from smexperiments.trial_component import TrialComponent

Define cleanup_sme_sdk

def cleanup_sme_sdk(experiment):
    for trial_summary in experiment.list_trials():
        trial = Trial.load(trial_name=trial_summary.trial_name)
        for trial_component_summary in trial.list_trial_components():
            tc = TrialComponent.load(
                trial_component_name=trial_component_summary.trial_component_name)
            trial.remove_trial_component(tc)
            try:
                # comment out to keep trial components
                tc.delete()
            except:
                # tc is associated with another trial
                continue
            # to prevent throttling
            time.sleep(.5)
        trial.delete()
        experiment_name = experiment.experiment_name
    experiment.delete()
    print(f"\nExperiment {experiment_name} deleted")

Call cleanup_sme_sdk

experiment_to_cleanup = Experiment.load(
    # Use experiment name not display name
    experiment_name="experiment-name")

cleanup_sme_sdk(experiment_to_cleanup)