rotta_rs 0.0.4

an AI library with rust language
Documentation

ROTTA Logo

ROTTA-rs

An AI Library In Rust 🦀

🛠️ still in development stage 🛠️

📦 Version: 0.0.4

✨ New Features

  • Dropout
  • SGD + Momentum
  • AdaGrad
  • powf
  • train and val method for module
  • New method for creating tensors

🚀 Optimizations

  • Optimized Basic Operations add, sub, mul, div, matmul

🛠️ Bug Fixes

  • Fixed bug on Sum Square Residual
  • Fixed a bug where tensors accumulated their gradients

📌 Check all releases: Tags
📜 Full changelog: version.md

⚙️ Installation

Currently, ROTTA-rs is not yet available on crates.io.
To use it:

[dependencies]
rotta_rs = {git = "https://github.com/araxnoid-code/ROTTA-rs"}

🧠 Simple AI Model

use rotta_rs::*;

fn main() {
    let mut model = Module::init();
    let optimazer = Sgd::init(model.parameters(), 0.00001);
    let loss_fn = SSResidual::init();

    let linear = model.liniar_init(1, 1);
    let linear_2 = model.liniar_init(1, 1);

    let input = Tensor::new([[1.0], [2.0]]);
    let actual = Tensor::new([[1.0], [4.0]]);

    for epoch in 0..100 {
        let x = linear.forward(&input);
        let x = relu(&x);
        let output = linear_2.forward(&x);

        let loss = loss_fn.forward(&output, &actual);
        println!("epoch:{epoch} | loss => {loss}");

        optimazer.zero_grad();

        let backward = loss.backward();

        optimazer.optim(backward);
    }
}

📚 GUIDE

📘 Start learning: 🧭 GUIDE.md

👍️ Support the Developer

If you find this project useful, you can support further development via:

🔗 saweria

🌐 Connect with Me

  • youtube

araxnoid

click here to go directly to youtube

  • tiktok

araxnoid

click here to go directly to tiktok

contact

  • Gmail

araxnoid0@gmail.com

📥 Dependencies