Answer-first summary for fast verification
Answer: the register_on_complete method of the OutputDatasetConfig class
The question requires registering pipeline output as a new version of a named dataset after the run completes. The register_on_complete method of the OutputDatasetConfig class is specifically designed for this purpose - it registers the output dataset as a new version after the pipeline run finishes. Option A (as_input) is for consuming datasets as input in subsequent pipeline steps, not for registering outputs. Options C and D (as_mount and as_download) are methods of DatasetConsumptionConfig class used for configuring how datasets are accessed during pipeline execution, not for registering outputs after completion. The community discussion shows 100% consensus on option B with multiple references to Microsoft documentation confirming this is the correct method.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
You are developing a two-step Azure Machine Learning pipeline with the Azure Machine Learning SDK for Python.
You must register the pipeline's output as a new version of a named dataset after the pipeline run completes.
What should you implement?
A
the as_input method of the OutputDatasetConfig class
B
the register_on_complete method of the OutputDatasetConfig class
C
the as_mount method of the DatasetConsumptionConfig class
D
the as_download method of the DatasetConsumptionConfig class
No comments yet.