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You create an Azure Machine Learning pipeline named pipeline1 with two steps that contain Python scripts. Data processed by the first step is passed to the second step.

You must update the content of the downstream data source of pipeline1 and run the pipeline again.

You need to ensure the new run of pipeline1 fully processes the updated content.

Solution: Set the regenerate_outputs parameter of the pipeline1 experiment’s run submit method to True.

Does the solution meet the goal?