You use the Azure Machine Learning SDK in a notebook to run an experiment using a script file in an experiment folder.
The experiment fails.
You need to troubleshoot the failed experiment.
What are two possible ways to achieve this goal? Each correct answer presents a complete solution.
Correct Answer: B,D
Use get_details_with_logs() to fetch the run details and logs created by the run.
You can monitor Azure Machine Learning runs and view their logs with the Azure Machine Learning studio.
Incorrect Answers:
A: You can view the metrics of a trained model using run.get_metrics().
E: get_output() gets the output of the step as PipelineData.
Reference:
https://docs.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.steprun
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-monitor-view-training-logs