brainstorm how to get objects into brain.js recurrent neural network

The standard network uses:

[
  {input: { r: 0.03, g: 0.7, b: 0.5 }, output: { black: 1 }},
  {input: { r: 0.16, g: 0.09, b: 0.2 }, output: { white: 1 }},
  {input: { r: 0.5, g: 0.5, b: 1.0 }, output: { white: 1 }}
]

for training. Would it be possible to get something like that into the recurrent neural network? If so, how?

[robertleeplummerjr]

Really, why there is different RNN and DenseNet APIs? They should be same, it’s just an abstraction.

The idea of brain.js is simplicity first. By not abstracting the base neural nets, we can optimize towards speed, and keep the learning curve low for understanding what is actually happening in the neural net, keeping things composable and understandable. However, I’d be open to abstracting if it meant meeting that goal. Also, the LSTM and GRU are abstractions. In the end, I think we wanted to just get it working 😋. Like Addy Osmani said: “First do it. Then do it right. Then do it better.” Also, I’m unaware of the “DenseNet” (a Densely Connected Convolutional Networks?) in our codebase that you speak of.

Also, I really think you are over-bloating the code, really, guys, review the codebase, we at synaptic2 have a RNN in around 7 times smaller amount of lines.

I applaud your hard work towards less is more, and the synaptic project is fantastic. The code we started with was https://github.com/karpathy/recurrentjs so it is just a reflection of that code aimed toward the brain.js api. We also have es6 src, which is compiled into es5 and a special browser (and browser min) file. This is all done automatically, but does add to the code base. I’m also interested where the figure “7 times smaller” comes from, would be helpful for comparing other projects in the future. We are also in the middle of removing things like tests that bring in dependencies. Does synpatic2 use matrix operations?

And the last thing, why for gods sake you do have an internal matrices lib? We have scijs, sylvester, vectorious, or you’re trying to build your own ecosystem?

The actual matrix library was brought in from recurrentjs, just simplified it and cut down on matrix instantiation, and split it apart so that when we do .toFunction() we could get the inner value of the objects and reuse as a non-function operation, an example that I sent to my mother which outputs “hi mom!”. Also, the actual matrix code fits in about 8 lines:

class Matrix {
  constructor(rows, columns) {
    this.rows = rows;
    this.columns = columns;
    this.weights = Float64Array(rows * columns);
    this.recurrence = Float64Array(rows * columns);
  }
}

The rest of it are some left over (not used, and thank you for bringing that to my attention) methods from recurrentjs, and utility functions for going to and from json, and math. The math was again brought in by recurrentjs and is there doing very simple operations that will eventually be made to run on the gpu where available. If there is a library that would give us what we have (reused matrices, relu, tanh, rowPluck, sampleI, maxI), I’m all for using it.

Thank you for your time in looking at our codebase!

[robertleeplummerjr]

This is now completed with https://gist.github.com/robertleeplummerjr/713a47d5fd63e8e189f8cf5cbc0649cd in brain.js 1.6.0+ for recurrent time step neural networks.