Starbeamrainbowlabs
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tfsummaryvis
Visualise textual Tensorflow summaries as a directed graph.
Tensorflow summaries are invaluable to understand how a model is put together. They usually look like this:
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
bidirectional (Bidirectiona (None, 100, 256) 336896
l)
bidirectional_1 (Bidirectio (None, 256) 394240
nal)
dense (Dense) (None, 2) 514
=================================================================
Total params: 731,650
Trainable params: 731,650
Non-trainable params: 0
_________________________________________________________________
Pretty easy to understand, right? But what about this monster? Or this one (this one doesn't actually work, do not implement at home)?
Larger models (and those aren't just a simple stack of layers) can be a nightmare to understand - even with a summary - hence this project was born :-)
It converts the above textual tensorflow summary into a directed graph with nomnoml.
Demo
Try the demo here: https://starbeamrainbowlabs.com/labs/tfsummaryvis/
Getting started locally
System Requirements
- git
- Node + npm
Instructions
If you want to run this project locally, first start by cloning the repository:
git clone https://git.starbeamrainbowlabs.com/sbrl/tfsummaryvis.git
cd tfsummaryvis;
Then, install dependencies:
npm install
Next, build the client-side app:
npm run build
Finally, serve with your favourite static web server:
npx serve dist/
Contributing
Contributions are very welcome - both issues and pull requests! Please mention in your pull request that you release your work under the MPL-2.0 (see below).
If you're feeling that way inclined, the sponsor button at the top of the page (if you're on GitHub) will take you to my Liberapay profile if you'd like to donate to say an extra thank you :-)
License
tfsummaryvis is released under the Mozilla Public License 2.0. The full license text is included in the LICENSE
file in this repository. Tldr legal have a great summary of the license if you're interested.