fast_neural_network/
lib.rs

1//! # Fast Neural Network Library
2//! 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.
3//! All of the heavy operations are parallelized. Stack-based networks are yet to be implemented.
4//! 
5//! ## Example
6//! 
7//! ```
8//! use fast_neural_network::{activation::*, neural_network::*};
9//! use ndarray::*;
10//! 
11//! fn main() {
12//!     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
13//! 
14//!     network.add_hidden_layer_with_size(2); // Add a hidden layer with 2 neurons
15//! 
16//!     network.compile();  // Compile the network to prepare it for training
17//!                         // (will be done automatically during training)
18//!                         // The API is exposed so that the user can compile
19//!                         // the network on a different thread before training if they want to
20//! 
21//!     // Let's create a dataset to represent the XOR function
22//!     let mut dataset: Vec<(ndarray::Array1<f64>, ndarray::Array1<f64>)> = Vec::new();
23//! 
24//!     dataset.push((array!(0., 0.), array!(0.)));
25//!     dataset.push((array!(1., 0.), array!(1.)));
26//!     dataset.push((array!(0., 1.), array!(1.)));
27//!     dataset.push((array!(1., 1.), array!(0.)));
28//! 
29//!     network.train(&dataset, 20_000, 1_000); // train the network for 20,000 epochs with a decay_time of 1,000 epochs
30//! 
31//!     let mut res;
32//! 
33//!     // Let's check the result
34//!     for i in 0..dataset.len() {
35//!         res = network.forward(&dataset[i].0);
36//!         let d = &dataset[i];
37//!         println!(
38//!             "for [{:.3}, {:.3}], [{:.3}] -> [{:.3}]",
39//!             d.0[0], d.0[1], d.1[0], res
40//!         );
41//!     }
42//! 
43//!     network.save("network.json"); // Save the model as a json to a file
44//! 
45//!     // Load the model from a json file using the below line
46//!     // let mut loaded_network = Network::load("network.json");  
47//! }
48//!  
49//! 
50//! ```
51
52pub mod neural_network;
53pub mod activation;
fast_neural_network/lib.rs

fast_neural_network/
lib.rs
