If by flow you mean the tensor sizes in different layers, that's a huge help for debugging, or when rewriting the net in a another framework. For debugging, you're otherwise stuck with opaque (for beginners) messages about tensor dimensions not matching. Visualizing makes the mismatches obvious, so it's common to draw the tensor sizes on paper, exactly what that visualization does.
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I'm not a machine learning engineer, so I'll ask the dumb question: why is visualizing this flow important? What's the benefit?
If by flow you mean the tensor sizes in different layers, that's a huge help for debugging, or when rewriting the net in a another framework. For debugging, you're otherwise stuck with opaque (for beginners) messages about tensor dimensions not matching. Visualizing makes the mismatches obvious, so it's common to draw the tensor sizes on paper, exactly what that visualization does.