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darsnack | 4 years ago

I’m not the main dev on FastAI.jl, but I work on the Julia ML community team that supported this project.

> Since FastAI.jl uses Flux, and not PyTorch, functionality has to be reimplemented.

We are looking to offer a high level API for ML in Julia similar to fastai for PyTorch. The goal is to enrich the Flux ecosystem, so just calling into Python fastai wouldn’t be appropriate. FastAI.jl is built on top of several lower level packages that can be used separately from FastAI.jl. These packages help build out the ecosystem not just for FastAI.jl, but any ML framework or workflow in Julia.

> What does this mean for the development of fastai?

FastAI.jl is “unofficial” in that Jeremy and the fastai team did not develop it. But Jeremy knows about the project, and we have kept in touch with the fastai team for feedback. FastAI.jl doesn’t affect the development of Python fastai in any way.

> FastAI.jl has vision support but no text support yet.

> What is the timeline for FastAI.jl to achieve parity?

We’re working to add more out-of-the-box support for other learning tasks. Currently, we have tabular support on the way, but the timeline for text is not decided.

Note that the framework itself could already support a text learning method, but you’d have to implement the high level interface functions for it yourself. We just don’t have built-in defaults like vision. You can check out https://fluxml.ai/FastAI.jl/dev/docs/learning_methods.md.htm... for a bit more on what I mean.

> When should I choose FastAI.jl vs fastai?

It depends on what you need. PyTorch and fastai are more mature, but Julia and Flux tend to be more flexible to non-standard problems in my experience. If you’re interested, then give Julia/Flux/FastAI.jl a try. If we’re missing a mission critical feature for you, then please let us know so we can prioritize it.

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ellisv|4 years ago

Thanks. I use both fastai and Julia already (not together) so this is interesting to me.

I'm unlikely to adopt FastAI.jl at work anytime soon without a clear win over an existing tool.

xvilka|4 years ago

I didn't check the library yet, asking here in case of the quick answer - does it support GNN too via GeometricFlux.jl[1]?

[1] https://github.com/FluxML/GeometricFlux.jl

darsnack|4 years ago

You would have to add a learning method to tell it how to encode/decode graph data, but the framework is agnostic to the model choice. So any Flux model is supported.

WanderPanda|4 years ago

It is not surprising to me that there is no text support yet, given the issues of integrating 3D (batch x sequence x features) RNN support (for CUDNN). This issue has prevailed so long that I came to believe it is impossible to integrate with the current Flux.jl stack.