rust-ndarray
manim
rust-ndarray | manim | |
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20 | 144 | |
3,319 | 57,952 | |
2.0% | - | |
8.2 | 8.6 | |
18 days ago | 19 days ago | |
Rust | Python | |
Apache License 2.0 | MIT License |
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rust-ndarray
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Some Reasons to Avoid Cython
I would love some examples of how to do non-trivial data interop between Rust and Python. My experience is that PyO3/Maturin is excellent when converting between simple datatypes but conversions get difficult when there are non-standard types, e.g. Python Numpy arrays or Rust ndarrays or whatever other custom thing.
Polars seems to have a good model where it uses the Arrow in memory format, which has implementations in Python and Rust, and makes a lot of the ndarray stuff easier. However, if the Rust libraries are not written with Arrow first, they become quite hard to work with. For example, there are many libraries written with https://github.com/rust-ndarray/ndarray, which is challenging to interop with Numpy.
(I am not an expert at all, please correct me if my characterizations are wrong!)
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Helper crate for working with image data of varying type?
Thanks for sharing. I read this issue on why ndarray does not have a dynamically typed array: https://github.com/rust-ndarray/ndarray/issues/651
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What is the most efficient way to study Rust for scientific computing applications?
You can get involved with the ndarray project
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faer 0.8.0 release
Sadly Ndarray does look a little abandoned to me: https://github.com/rust-ndarray/ndarray
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Status and Future of ndarray?
The date of the last commit of [ndarray](https://github.com/rust-ndarray/ndarray) lies 6 month in the past while many recent issues are open and untouched.
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How does explicit unrolling differ from iterating through elements one-by-one? (ndarray example)
While looking through ndarrays src, I came across a set of functions that explicitly unroll 8 variables on each iteration of a loop, with the comment eightfold unrolled so that floating point can be vectorized (even with strict floating point accuracy semantics). I don't understand why floats would be affected by unrolling, and in general I'm confused as to how explicit unrolling differs from iterating through each element one by one. I assumed this would be a scenario where the compiler would optimize best anyway, which seems to be confirmed (at least in the context of using iter() rather than for) here. Could anyone give a little context into what this, or any explicit unrolling achieves?
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Announcing Burn: New Deep Learning framework with CPU & GPU support using the newly stabilized GAT feature
Burn is different: it is built around the Backend trait which encapsulates tensor primitives. Even the reverse mode automatic differentiation is just a backend that wraps another one using the decorator pattern. The goal is to make it very easy to create optimized backends and support different devices and use cases. For now, there are only 3 backends: NdArray (https://github.com/rust-ndarray/ndarray) for a pure rust solution, Tch (https://github.com/LaurentMazare/tch-rs) for an easy access to CUDA and cuDNN optimized operations and the ADBackendDecorator making any backend differentiable. I am now refactoring the internal backend API to make it as easy as possible to plug in new ones.
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Pure rust implementation for deep learning models
Looks like it's an open request
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The Illustrated Stable Diffusion
https://github.com/rust-ndarray/ndarray/issues/281
Answer: you can’t with this crate. I implemented a dynamic n-dim solution myself but it uses views of integer indices that get copied to a new array, which have indexes to another flattened array in order to avoid duplication of possibly massive amounts of n-dimensional data; using the crate alone, copying all the array data would be unavoidable.
Ultimately I’ve had to make my own axis shifting and windowing mechanisms. But the crate is still a useful lib and continuing effort.
While I don’t mind getting into the weeds, these kinds of side efforts can really impact context focus so it’s just something to be aware of.
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Any efficient way of splitting vector?
In principle you're trying to convert between columnar and row-based data layouts, something that happens fairly often in data science. I bet there's some hyper-efficient SIMD magic that could be invoked for these slicing operations (and maybe the iterator solution does exactly that). Might be worth taking a look at how the relevant Rust libraries like ndarray do it.
manim
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3Blue1Brown: Visualizing Attention, a Transformer's Heart
That is definitely one of the things he does better than most. He actually wrote a custom library for math animations: https://github.com/3b1b/manim
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Where Is Noether's Principle in Machine Learning?
Not quite what you're looking for, but worth pointing out that Grant Sanderson of 3Blue1Brown has published the "framework" he uses for his math videos on GitHub.
https://github.com/3b1b/manim
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3Blue1Brown Calculus Blog Series
3b1b uses a python library for creating those videos.
https://github.com/3b1b/manim
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Animating High School Maths Curriculum
Manim, 3b1b's animation library is open source: https://github.com/3b1b/manim
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Why do people think animation involves a ton of coding?
Coming to motion design, this rumour takes of due to the fact that there are programming libraries like Manim and Motion-Canvas which are actually used to generate animations from code. You can search 3Blue1Brown channel on youtube.
- Connaissez-vous des petits youtubeurs dans le style de Micode?
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Stickman fucks around with math and finds out
It kinda looks like this: https://github.com/3b1b/manim, but that would be a crazy usage of it. Wondering if they’re compositing Manim with a more traditional animation suite.
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Online classes in china 🔥
Probably used this for the animation: https://github.com/3b1b/manim
- Material python
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What language for creating mathematical modeling program?
3blue1brown has had success with (their tool) manim, which uses Python.
What are some alternatives?
nalgebra - Linear algebra library for Rust.
geogebra - GeoGebra apps (mirror)
Rust-CUDA - Ecosystem of libraries and tools for writing and executing fast GPU code fully in Rust.
reanimate - Haskell library for building declarative animations based on SVG graphics
image - Encoding and decoding images in Rust
Tools-to-Design-or-Visualize-Architecture-of-Neural-Network - Tools to Design or Visualize Architecture of Neural Network
neuronika - Tensors and dynamic neural networks in pure Rust.
matplotplusplus - Matplot++: A C++ Graphics Library for Data Visualization 📊🗾
utah - Dataframe structure and operations in Rust
NumPy - The fundamental package for scientific computing with Python.
linfa - A Rust machine learning framework.
jupyter-manim - manim cell magic for IPython/Jupyter to show the output video