ROTTA-rs

A Deep Learning Library In Rust 🦀

🛠️ still in development stage 🛠️

⚙️ Create Your AI Model On Rust 🦀

ROTTA-rs was developed as an open-source deep learning library with the primary goal of providing an easy-to-use, lightweight, and flexible tool

fn main() {
    let tensor = Tensor::new([[0.1, 0.2, 0.3]]);
    println!("{}", tensor);
}

📦 Version 0.1.0

see more details about what's new in: 0.1.0

🧑‍💻 see other versions:

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

⚙️ Installation

ROTTA-rs can be installed directly through crates.io. To use it:

Or add the following line to your Cargo.toml 📁:

[dependencies]
rotta_rs = "0.1.0"

or

Run the following Cargo command in your project directory 💻️:

cargo add 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);
    }
}

🏫 Tutorial (currently only available in Indonesian)

Those who want to learn how to create AI can access: 📔 learn.md

📚 GUIDE

📘 Start Exploration: 🧭 GUIDE.md

🤖 Experimental Model

ROTTA-rs also has several AI models intended for testing and not for production.

See more details about: 🤖 Experimental Models

👍️ 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

• rand
• rand_distr
• uuid
• rayon
• matrixmultiply
• rand_chacha
• serde
• serde_json