Using DAG Structure to Trace Errors in a Workflow
When a machine learning system is built as a pipeline, its stages should form a directed acyclic graph. That means each stage can be placed in a fixed linear order, and any stage can use only outputs produced earlier in the graph. If the workflow respects that dependency pattern, you can still use it to locate where errors are likely coming from.
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Using DAG Structure to Trace Errors in a Workflow
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