Explanation:
The solution does NOT meet the goal because run.log_table() is designed to log tabular data (dictionaries with column names and lists of values), not simple lists of unique label values. The community discussion clearly indicates that for logging a list of values like label_vals (which is a numpy.ndarray containing unique labels), the appropriate method is run.log_list('Label Values', label_vals). The highly upvoted comment (7 upvotes) provides specific examples showing that run.log_list() is for lists while run.log_table() is for tabular data. Another comment with 5 upvotes explicitly states that B (No) is correct and confirms that run.log_table() is used for dictionary objects, not simple lists of label values.
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You are using a Python script for an Azure Machine Learning experiment. The script references the experiment run context, loads data, identifies the unique values for the label column, and completes the run. You need to record these unique label values as run metrics.
You implement the following solution: Replace the comment in the script with the code run.log_table('Label Values', label_vals).
Does this solution meet the goal of recording the unique label values as metrics for the run?
A
Yes
B
No
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