I've been meaning to check Julia out for a while now. Are there any deep learning libraries that are as feature complete and user friendly as PyTorch/ Tensorflow?
Flux but its not even close to PyTorch or TF in terms of features and performance
Julia 1.4
11–20 of 137 posts
Re: Julia 1.4
#12Something about Julia from me. I was big Julia fan using it for last 1.5 year and in my company we are using Julia for data preprocessing and parsing hundred of GB's of data. (We also use Python for ML and start to moving julia code to Nim for data prepro) If u consider Julia as ur next language dont use it to any medium to big project outside pure scientific purposes it just isnt ready yet. We have about 3.5k loc in…
I have to admit that over the past 20 years, java is like the most stable robust, huge project, multiple teams, IDE friendly, type safe, infinite tooling and libraries language of choice!
Re: Julia 1.4
#13Something about Julia from me. I was big Julia fan using it for last 1.5 year and in my company we are using Julia for data preprocessing and parsing hundred of GB's of data. (We also use Python for ML and start to moving julia code to Nim for data prepro) If u consider Julia as ur next language dont use it to any medium to big project outside pure scientific purposes it just isnt ready yet. We have about 3.5k loc in…
I have to admit that over the past 20 years, java is like the most stable robust, huge project, multiple teams, IDE friendly, type safe, infinite tooling and libraries language of choice!
Java is good for big projects but not for Machine Learning purposes (Also im C# fanboy so still will prefer C# over Java :D)
Re: Julia 1.4
#14Something about Julia from me. I was big Julia fan using it for last 1.5 year and in my company we are using Julia for data preprocessing and parsing hundred of GB's of data. (We also use Python for ML and start to moving julia code to Nim for data prepro) If u consider Julia as ur next language dont use it to any medium to big project outside pure scientific purposes it just isnt ready yet. We have about 3.5k loc in…
I have to admit that over the past 20 years, java is like the most stable robust, huge project, multiple teams, IDE friendly, type safe, infinite tooling and libraries language of choice!
Not too surprising. Java was _designed_ by ex Unix engineers at a time that the word "engineer" meant something.
Now we have the cloud/web stack and _Javascript_.
The bar was low enough for Julia to sound good at the start, but it gives the impression of being "designed" "on-the-fly".
Re: Julia 1.4
#15Something about Julia from me. I was big Julia fan using it for last 1.5 year and in my company we are using Julia for data preprocessing and parsing hundred of GB's of data. (We also use Python for ML and start to moving julia code to Nim for data prepro) If u consider Julia as ur next language dont use it to any medium to big project outside pure scientific purposes it just isnt ready yet. We have about 3.5k loc in…
I really like the idea of Julia, and my biggest hope is that it can still replace the use of R in statistics and scientific computing, but I have to agree it is a bit unwieldy in larger projects or as a general programming language and that nim is really promising in this regard.
Re: Julia 1.4
#16Earlier quoted context omitted.
This. I have been trying to learn Julia so I can promote it to replace Matlab in my company. I think everyone will like the performance, and a more modern and extensive library (also the fact that it's free will save the company a lot of money). But the atom Juno IDE looks so unprofessional, I think we will have a really hard time convincing scientists to use something which can't even undock the editor properly (I k…
Seems to be a thing of electron, VS code cannot do this either (and the proper handling of multiple monitors in general).
Yeah, that is my guess too. But at least VS code can save your workspace in atom you have to install a package to do that. To programmers it might look like flexibility but to non programmers it just looks like a chore.
Re: Julia 1.4
#17I've been meaning to check Julia out for a while now. Are there any deep learning libraries that are as feature complete and user friendly as PyTorch/ Tensorflow?
Flux but its not even close to PyTorch or TF in terms of features and performance
It depends what you're doing. If you need to write your own kernels, or have small networks where the framework overhead is significant, then it's way faster than Tensorflow (unless you implement your own Tensorflow OP in C++/Cuda, but that's way more painful than just implementing it directly in Flux/Julia). It's hence quite nice for research on new architectures. Flux's autodiff also handles more language features than TF or PyTorch's.
Re: Julia 1.4
#18Something about Julia from me. I was big Julia fan using it for last 1.5 year and in my company we are using Julia for data preprocessing and parsing hundred of GB's of data. (We also use Python for ML and start to moving julia code to Nim for data prepro) If u consider Julia as ur next language dont use it to any medium to big project outside pure scientific purposes it just isnt ready yet. We have about 3.5k loc in…
We're using it in a soft-realtime setting to monitor industrial chlorine production, and for us it has been a very pleasant experience overall. Yes, we've had some issues, but similar to other ecosystem IMO, and our support contract with Julia computing helped us in the one case we really couldn't solve ourselves.
Julia works really well for power users. There are no huge libraries full of C code like pandas or scipy. Instead there are dozens of small, well-tested packages that fill the same role, all hosted on github. That makes fixing issues so much easier.
Granted: outside of numerical/technical computing, the libraries can be lacking (eg. web development) compared to other languages. We're doing it anyway, but it's a more difficult decision.
Re: Julia 1.4
#19I wish it had more dedicated IDE besides the atom/electron based ones (like GNU Octave has its own). I think Julia's performance deserves an equally performant IDE.
I've had quite a pleasant experience with just Jupyter Notebooks & Emacs for Julia development.
Re: Julia 1.4
#20Something about Julia from me. I was big Julia fan using it for last 1.5 year and in my company we are using Julia for data preprocessing and parsing hundred of GB's of data. (We also use Python for ML and start to moving julia code to Nim for data prepro) If u consider Julia as ur next language dont use it to any medium to big project outside pure scientific purposes it just isnt ready yet. We have about 3.5k loc in…
> near stable and/or fast as any other "new" languages (RUST, Nim, Golang, even Swift)
This is not my experience, at least for numeric code. It generates faster code than Golang, because it uses an LLVM backend (and actually supports macros and parametric polymorphism, so doesn't need to do the work at runtime), faster numeric code than Rust via @inbounds and @simd annotations (way more work to disable bounds checks in Rust), and faster than Swift because it doesn't have pervasive reference counting that can sneak in and destroy performance.