
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow - happy-go-lucky
http://idl.cs.washington.edu/papers/tfgraph
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rawnlq
I wonder if one dominant visual dataflow language will ever emerge. It seems
like a generally useful idea across many different domains but it's something
that's always reimplemented from scratch. Stuff like how to visualize and
layout the nodes seems to be pretty domain agnostic?

Game engines:
[https://docs.unrealengine.com/latest/INT/Engine/Rendering/Ma...](https://docs.unrealengine.com/latest/INT/Engine/Rendering/Materials/Editor/)

Graphics:
[https://developer.apple.com/library/content/documentation/Gr...](https://developer.apple.com/library/content/documentation/GraphicsImaging/Conceptual/QuartzComposerUserGuide/qc_concepts/qc_concepts.html#//apple_ref/doc/uid/TP40005381-CH212-SW9)

Robotics: [https://xod.io/](https://xod.io/)

And many more: [https://stackoverflow.com/questions/461796/dataflow-
programm...](https://stackoverflow.com/questions/461796/dataflow-programming-
languages/2035582)

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kanitw
Note that a dataflow graph is generally a directed graph (which is domain
agnostic). Thus it can always be visualized in some ways.

There are also many generally applicable directed graph drawing techniques in
academic literature. (You can see some in the related work section in the
paper.)

That said, in different domains, people may apply different sets of layout and
visual encoding techniques due to the differences in semantics and
characteristic of the graphs.

For example, in this TensorFlow Graph Vis project, we chose to build a
hierarchical clustered graph to provide high-level overview, bundle edges to
facilitate interactive expansion, and detach unimportant nodes from the main
layout to declutter the graph.

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kanitw
@happy-go-lucky Thanks for posting.

I'm the first author of this paper, so I'm glad our paper attracts your
interest.

I'm also happy to answer questions about the paper too.

