gonb
Arraymancer
gonb | Arraymancer | |
---|---|---|
5 | 21 | |
430 | 1,309 | |
- | - | |
9.3 | 8.2 | |
18 days ago | 5 days ago | |
Go | Nim | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gonb
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Go, Python, Rust, and production AI applications
I've had these strong feelings and the OP describes it really well. Despite being a polyglot programmer, I really struggle with Python, both in expression and performance (unless it's just config for GPUs).
Some of this frustration was recently an "Unpopular Opinion" on the Go Time Podcast regarding Python being great for "data exploration" but not for "data engineering": https://changelog.com/gotime/304#t=3196
I've been yearning for better interactive tooling and ML-related libraries bridge this gap and started using some even in just the last week:
* GoNB (Golang-support for Jupyter notebooks, also from a Googler) https://github.com/janpfeifer/gonb
* That uses Go-Plotly for graphs/UI: https://github.com/MetalBlueberry/go-plotly
* GoMLX (GoNB author is also on that project, many thanks Jan!) https://github.com/gomlx/gomlx
* Hidden at the end of OP is LangChainGo for LLMs, which I haven't used yet: https://github.com/tmc/langchaingo
Pick those up and let's make the Go community stronger together!
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The Golang Saga: A Coder’s Journey There and Back Again. Part 2: The Data Expedition
When I created a new Jupyter file in Go, I faced a challenge trying to replicate the development process I usually follow with Python. In Python and Jupyter Notebook I can conveniently run code in separate parts, saving previous values in memory and using cells to organize code. This flexibility was missing in Go, and it took me some time to figure out a solution. However, I came across a helpful tutorial that explained how to use caching with the Go Kernel, making the process smoother with gonb.
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The Golang Saga: A Coder’s Journey There and Back Again. Part 1: Leaving the Shire
I needed one more thing to make myself feel at home, something I usually use with Python. When working with data, I often turned to the Jupyter VSCode extension for its convenience. To my relief, I discovered that a Go kernel existed, tailored perfectly for my needs.
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GoMLX -- Accelerated ML for Go
Training library, with some pretty-printing. Including plots for GoNB Jupyter notebook.
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GoNB, a new Jupyter Notebook Kernel for Go
Tutorial (and demo) here. Source code in github.com/janpfeifer/gonb.
Arraymancer
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Arraymancer – Deep Learning Nim Library
It is a small DSL written using macros at https://github.com/mratsim/Arraymancer/blob/master/src/array....
Nim has pretty great meta-programming capabilities and arraymancer employs some cool features like emitting cuda-kernels on the fly using standard templates depending on backend !
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Go, Python, Rust, and production AI applications
Nim has also a powerful deep learning library called Arraymancer. It's selling point is that you don't have to rewrite your code from research to production. It's used in various machine learning projects, but one recent one that caught my eye was https://github.com/amkrajewski/nimCSO "Composition Space Optimization"
https://github.com/mratsim/Arraymancer
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D Programming Language
- https://github.com/mratsim/Arraymancer/blob/master/src/array...
It's worth noting that nim async/await transformation is fully implemented as a library in macros.
- Prospects of utilising Nim in scientific computation?
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How to write performant Nim?
https://github.com/mratsim/Arraymancer 11. « Premature optimisation is the root of all evil », Donald Knuth, The art of computer Programming It would be quite useful that someone writes one with examples for all these recommendations and more ...
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Deeplearning in Nim?
In particular for deep learning as bobsyourunkl already mentioned there is arraymancer on the one hand and also flambeau on the other. The latter is a Nim wrapper around libtorch (i.e. the PyTorch C++ backend). It is missing things (to be wrapped by adding a few lines) and has some rough edges, but if one needs to get stuff done, it's possible.
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Mastering Nim – now available on Amazon
how are u compiling (optimization, custom compilation flags etc.?) In my case https://github.com/mratsim/Arraymancer big project compile under your 4.2s so or you have like 10k+ lines of codes with macros or you just pass some debug flags to compiler :D
- Nim Version 1.6.6 Released
- The counter-intuitive rise of Python in scientific computing (2020)
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Computer Programming with Nim
We have both raw wrappers for BLAS:
https://github.com/andreaferretti/nimblas
as well as LAPACK:
https://github.com/andreaferretti/nimlapack
For an example, consider calling the least squares routine `dgelsd` in arraymancer:
https://github.com/mratsim/Arraymancer/blob/master/src/array...
wrapped up in a nicer user facing API.
Feel free to hop onto matrix, if you have more questions!
What are some alternatives?
fleet
nimtorch - PyTorch - Python + Nim
Docker - Notary is a project that allows anyone to have trust over arbitrary collections of data
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
myLG - Network Diagnostic Tool
nimble - Package manager for the Nim programming language.
ipe - An open source Pusher server implementation compatible with Pusher client libraries written in GO
awesome-tensor-compilers - A list of awesome compiler projects and papers for tensor computation and deep learning.
Hugo - The world’s fastest framework for building websites.
nvim-treesitter - Nvim Treesitter configurations and abstraction layer
gomlx - GoMLX -- Accelerated ML Libraries for Go
prologue - Powerful and flexible web framework written in Nim