RusTorch

A PyTorch-compatible deep learning library in Rust, providing tensor computation with strong GPU acceleration and deep neural networks built on a tape-based autograd system.

Features

• Tensor Computation: N-dimensional tensors with GPU support (coming soon)
• Automatic Differentiation: Build computational graphs for automatic differentiation
• Neural Network Building Blocks: Pre-defined layers, loss functions, and optimization algorithms
• PyTorch-like API: Familiar interface for PyTorch users
• Safe and Fast: Leveraging Rust's safety guarantees and performance

Installation

Add this to your Cargo.toml:

[dependencies]
rustorch = "0.1.0"

Quick Start

Here's a simple example of training a linear regression model:

use rustorch::prelude::*;
use rustorch::nn::{Module, Linear};

fn main() {
    // Create a simple linear model
    let model = Linear::new(1, 1, true);
    
    // Example input and target
    let x = Tensor::from_vec(vec![1.0, 2.0, 3.0, 4.0], vec![4, 1]);
    let y = Tensor::from_vec(vec![2.0, 4.0, 6.0, 8.0], vec![4, 1]);
    
    // Convert to variables
    let x_var = Variable::new(x, true);
    let y_var = Variable::new(y, false);
    
    // Forward pass
    let output = model.forward(&x_var);
    
    // Compute loss
    let loss = (output - y_var).pow(2.0).mean();
    
    println!("Loss: {}", loss.data());
}

Examples

See the examples directory for more complete examples:

• Linear Regression: Simple linear regression example
• MNIST Classifier: Handwritten digit classification (coming soon)

Documentation

For detailed documentation, please refer to the API documentation.

License

Licensed under either of:

• Apache License, Version 2.0 (LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
• MIT license (LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.