Crate fast_neural_network

source ·
Expand description

Fast Neural Network Library

This library is a simple neural network library written in Rust. It is designed to be fast and easy to use. It supports saving and loading networks to and from JSON files. All of the heavy operations are parallelized. Stack-based networks are yet to be implemented.

Example

use fast_neural_network::{activation::*, neural_network::*};
use ndarray::*;
 
fn main() {
    let mut network = Network::new(2, 1, ActivationType::LeakyRelu, 0.01); // Create a new network with 2 inputs, 1 output, a LeakyRelu activation function, and a learning rate of 0.01
 
    network.add_hidden_layer_with_size(2); // Add a hidden layer with 2 neurons
 
    network.compile();  // Compile the network to prepare it for training
                        // (will be done automatically during training)
                        // The API is exposed so that the user can compile
                        // the network on a different thread before training if they want to
 
    // Let's create a dataset to represent the XOR function
    let mut dataset: Vec<(ndarray::Array1<f64>, ndarray::Array1<f64>)> = Vec::new();
 
    dataset.push((array!(0., 0.), array!(0.)));
    dataset.push((array!(1., 0.), array!(1.)));
    dataset.push((array!(0., 1.), array!(1.)));
    dataset.push((array!(1., 1.), array!(0.)));
 
    network.train(&dataset, 20_000, 1_000); // train the network for 20,000 epochs with a decay_time of 1,000 epochs
 
    let mut res;
 
    // Let's check the result
    for i in 0..dataset.len() {
        res = network.forward(&dataset[i].0);
        let d = &dataset[i];
        println!(
            "for [{:.3}, {:.3}], [{:.3}] -> [{:.3}]",
            d.0[0], d.0[1], d.1[0], res
        );
    }
 
    network.save("network.json"); // Save the model as a json to a file
 
    // Load the model from a json file using the below line
    // let mut loaded_network = Network::load("network.json");  
}

Modules