28 lines
1.5 KiB
Markdown
28 lines
1.5 KiB
Markdown
# Флукс
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## What?
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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.
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## Why?
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Flux has a few key differences from other libraries:
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* Flux's [graph-based DSL](https://github.com/MikeInnes/Flow.jl), 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.
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* The graph DSL directly is used to represent models (not just computations), so custom architectures – and in particular, recurrent models – are easy to express.
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* 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.
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* Flux is written in [Julia](http://julialang.org), 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.
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Future work will also include:
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* Integration with other backends, so that models can be described using Flux and run using (say) TensorFlow.
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* Carrying out runtime optimisations of the graph, in particular to handle small matrices efficiently.
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## How?
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See [the design docs](design.md).
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## Is it any good?
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Yes.
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