Nice work! I've also tried my hands at use WebGL to do deep learning in the browser (e.g. https://github.com/scienceai/neocortex/blob/master/src/lib/w...). The conclusion I came to was that there are just way too many limitations for it to really pay off. The need to encode everything in textures etc limits the data shape and dimensionality, not to mention the complexity cost. If you can get more complex networks working I'll be really impressed!
MXnet.js [1] is an emscripten port of the base C++ framework. It runs entirely in the browser and works fairly well. The actual code produced by emscripten isn't that large, but the model weights can become an issue. I've tried to get emscripten working on tensorflow, even just for forward prediction, but have been pretty much gotten nowhere. Of course this doesn't let you harness GPU power.
Lots of cool potential applications of doing deep learning over the web are just waiting to be discovered and built.
MXnet.js [1] is an emscripten port of the base C++ framework. It runs entirely in the browser and works fairly well. The actual code produced by emscripten isn't that large, but the model weights can become an issue. I've tried to get emscripten working on tensorflow, even just for forward prediction, but have been pretty much gotten nowhere. Of course this doesn't let you harness GPU power.
Lots of cool potential applications of doing deep learning over the web are just waiting to be discovered and built.
[1] https://github.com/dmlc/mxnet.js