Флукс

What?

Flux is an experimental machine perception / ANN library for Julia. It's designed to make experimenting with novel layer types and architectures really fast, without sacrificing runtime speed.

Why?

Flux has a few key differences from other libraries:

• Flux's graph-based DSL, which provides optimisations and automatic differentiation, is very tightly integrated with the language. This means nice syntax for your equations (σ(W*x+b) anyone?) and no unwieldy compile steps.
• The graph DSL directly is used to represent models (not just computations), so custom architectures – and in particular, recurrent models – are easy to express.
• Those fancy features are completely optional. You can implement functionality in a Torch-like fashion if you wish, since layers are simply objects that satisfy a small interface.
• Flux is written in Julia, which means there's no "dropping down" to C. It's Julia all the way down, and you can prototype both high-level architectures and high-performance GPU kernels from the same language. This also makes the library itself very easy to understand and extend.

Future work will also include:

• Integration with other backends, so that models can be described using Flux and run using (say) TensorFlow.
• Carrying out runtime optimisations of the graph, in particular to handle small matrices efficiently.

How?

See the design docs.

Is it any good?

Yes.