syt123450

I am trying to design RNN layers, however, RNN is not the same as CNN layers. Now we use 3D to visualize CNN layer, as RNN has a time level information, it required 4D to visualize it, but I will try my best to add this attractive feature to TensorSpace!

Thanks!

Thanks!

Augmented reality is really an amazing idea! As Three.js support web vr, I will dig into it. Hoping I can add this feature to TensorSpace soon.

Thanks. Visualize Keras model is easier than other kinds of model, as TensorSpace's API is designed based on Keras, you can easily use keras-like TensorSpace API to build TensorSpace model and visualize it.

Thanks for your feedback, I am planing to visualize weights in next version of TensorSpace. These days, I add a "live loader" for TensorSpace, user can use this API to visualize online training process.

And for others features, we are discussing how to integrate them with TensorSpace, looking forward to your further suggestions.

Thanks so much for your suggestions. As you say, visualizing weights may be really helpful, and I get many feedbacks for adding visualizing weights. I will try to add this feature in later version of TensorSpace. Temporarily, TensorSpace integrate TrackballControl which is an plugin for Three.js to handle "space exploration", and I will try to add more keyboard event for TensorSpace.

I have viewed your blog, and it is really fun. However, it is a pity that the online demo is outdated. Could you tell me what technique you use to construct 3D scene? Thanks.

TensorSpace provides structure information and some basic metric for deep learning, and we use these famous network to show what TensorSpace can do, and how to use TensorSpace API to construct networks. For deep learning experts, these famous network's information is really basic, but we hope TensorSpace can help others to understand existing model, or help to present customized models.

Thanks for your recommendation, I can not wait to add more interesting idea into TensorSpace!

Thanks for your suggestions! TensorSpace is an in developing framework, and I acknowledge that it has some shortcomings, as you mentioned that for a big network, it will be too long in TensorSpace to visualize, and I am trying to figure out a solution to optimize it, for example, add "layer group" concept in TensorSpace in the future, which may make the long network shorter.

Honestly speaking, there are many mature tools for developers to use in model training, and everyone has own "optimum scheme". For me, TensorSpace is not designed to be a "silver bullet" to replace previous solutions or tools, I hope it can help engineers understand existing models and find areas where they can be applied.

Personally, I am interested in data visualization, and I found that neural network visualization is really a cool area. My original intention to make TensorSpace is to share this "beautiful scenery" with hackers!