fengari VS Pytorch

it should be possible, the article mentions https://fengari.io/ (a Lua VM written in JavaScript)

Check out Fengari or Lapis. Fun fact: itch.io is written primarily in Lua, and started by the same person who made Lapis and MoonScript.

I was real excited to see these recently... have you tried any? https://fengari.io/ is the one I was most intrigued by.

Hello, there is also fengari: https://fengari.io/

Other languages have done that :)

Lua in the browser: https://fengari.io/

And then you can use that to run Fennel, a Lisp that compiles to Lua https://fennel-lang.org/

I think TypeScript also has a script you can include that lets you put your TS code in a special script tag, and it gets compiled in-browser.

just use lua, it’s what should have been used for web scripting anyways

Please stop this stuck in the mud nonsense. Anyone stumbling upon lua.org might think the project is dead already. The material is great, close to the best, but its presentation is pure shite. Not mobile friendly (what kinds of device do you think the majority of people in the Global South use?). We live in a world of code highlighting, none of that in PiL. We live in a world where Fengari allows Lua to run in the browser, does that make an appearance on lua.org, allowing users to immediately play with the language? Of course not! It's almost as if the Lua team is trying to push away potential users.

why not use lua

Just use lua https://fengari.io/

Definitely the most surprising use-case for Lua that I've seen is http://lua.space/webdev/why-we-rewrote-lua-in-js which discusses https://fengari.io/.

PyTorch (https://pytorch.org/)

torch is a package to manage tensors and dynamic neural networks in python (GitHub)

PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832

TensorFlow

TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.

> does PyTorch have a similar concept

of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...

fyi should work on most 40xx[1]

[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...

Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...

Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....

> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].

*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.

In PyTorch with @, dot() or matmul():