The Experiment.submit() method initiates the pipeline run asynchronously, meaning the script continues execution without waiting for the pipeline to finish. To block the script and wait for the run to complete while streaming its log outputs (including STDOUT) to the console, you must call the waitforcompletion() method on the returned run object. The parameter showoutput=True specifically instructs the SDK to print the run's verbose output, which is essential for testing and debugging purposes.

A. pipelinerun.getmetrics() retrieves only the specific metrics that were explicitly logged during the run; it does not display the general STDOUT output from the compute target.
C. PipelineParameter is used to define dynamic inputs for a pipeline that can be set at submission time, not to control the display of run logs.
D. pipelinerun.getstatus() returns only the current status of the run (e.g., 'Running', 'Completed') as a string. It does not wait for completion or show any detailed output.

1. Microsoft. (2023). azureml.core.run.Run class. Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/python/api/azureml-core/azureml.core.run.run?view=azure-ml-py#azureml-core-run-run-wait-for-completion.

Reference Detail: The documentation for the waitforcompletion method states

"Wait for the run to complete. This function returns the status object after the wait." The showoutput parameter is described as: "Indicates whether to show the run output on sys.stdout." This directly supports option B.

2. Microsoft. (2023). Create and run machine learning pipelines with Azure Machine Learning SDK. Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/azure/machine-learning/how-to-create-machine-learning-pipelines.

Reference Detail: In the "Submit the pipeline" section

the example code demonstrates the pattern of submitting a pipeline and then calling pipelinerun.waitforcompletion(showoutput=True) to monitor the execution.

3. Microsoft. (2023). azureml.pipeline.core.PipelineRun class. Microsoft Learn. Retrieved from https://learn.microsoft.com/en-us/python/api/azureml-pipeline-core/azureml.pipeline.core.pipelinerun?view=azure-ml-py.

Reference Detail: This documentation confirms that PipelineRun inherits from azureml.core.Run

and therefore possesses the waitforcompletion

getmetrics

and getstatus methods.