Answer-first summary for fast verification
Answer: Use the get_details_with_logs() method of the run object to display the experiment run logs., View the logs for the experiment run in Azure Machine Learning studio.
The question asks for two complete solutions to troubleshoot a failed Azure ML experiment run from a notebook. Option B (get_details_with_logs()) is correct because it retrieves both run details and execution logs directly through the SDK, which is optimal for programmatic troubleshooting in a notebook environment. Option D is correct because Azure ML Studio provides a comprehensive UI for viewing run logs, metrics, and diagnostics, offering an alternative visual approach. Option A (get_metrics()) is incorrect as it only retrieves metrics, not detailed execution logs needed for troubleshooting failures. Option C is incorrect because log files are not stored in the experiment folder but in dedicated log directories (e.g., azureml-logs), making direct file access unreliable. Option E (get_output()) is incorrect as it retrieves pipeline outputs, not logs.
Author: LeetQuiz Editorial Team
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You are using the Azure Machine Learning SDK in a notebook to run an experiment that references a script file in an experiment folder. The experiment fails. What are two different ways to troubleshoot the failed run? Each answer must present a complete solution.
A
Use the get_metrics() method of the run object to retrieve the experiment run logs.
B
Use the get_details_with_logs() method of the run object to display the experiment run logs.
C
View the log files for the experiment run in the experiment folder.
D
View the logs for the experiment run in Azure Machine Learning studio.
E
Use the get_output() method of the run object to retrieve the experiment run logs.
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