tensorflow / tensorflow/tensorboard
Plugin design: Do inference to visualize network activations
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Description
Is it conceivable that one could write a plugin that visualizes activations similar to the tool from Yosinski? I wonder, because it seems that one should rather write summaries, that are then processed by the backend, but if one wants to interactively choose inputs, that does not seem appropriate. Would it make sense to just configure the backend with the graph_def and a path to a checkpoint and then serve inferred activations? I am asking, because I currently work on a tool simliar to Yosinski's and integration into Tensorboard would be nice, but I am not sure if this complies with the intended design.
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Research direction
Start with the TensorBoard plugin example and the Yosinski deep-visualization-toolbox linked in the issue, then review the summaries and backend path described here. Establish whether interactive input selection can be supported with a graph_def and checkpoint, and document the resulting plugin integration direction.
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Assessment
- Domain
- backend, data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100