micrograd_rs/
neuron.rs

1use crate::value::Value;
2
3use rand::{thread_rng, Rng};
4
5#[derive(Clone)]
6pub struct Neuron {
7    weights: Vec<Value>,
8    bias: Value,
9}
10
11impl Neuron {
12    pub fn new(input_count: usize) -> Neuron {
13        let mut rng = thread_rng();
14        let mut rand_value_fn = || {
15            let data = rng.gen_range(-1.0..1.0);
16            Value::from(data)
17        };
18
19        let mut weights = Vec::new();
20        for _ in 0..input_count {
21            weights.push(rand_value_fn());
22        }
23
24        Neuron {
25            weights,
26            bias: rand_value_fn().with_label("b"),
27        }
28    }
29
30    pub fn forward(&self, xs: &Vec<Value>) -> Value {
31        let products = std::iter::zip(&self.weights, xs)
32            .map(|(a, b)| a * b)
33            .collect::<Vec<Value>>();
34
35        let sum = self.bias.clone() + products.into_iter().reduce(|acc, prd| acc + prd).unwrap();
36        sum.tanh()
37    }
38
39    pub fn parameters(&self) -> Vec<Value> {
40        [self.bias.clone()]
41            .into_iter()
42            .chain(self.weights.clone())
43            .collect()
44    }
45}
micrograd_rs/neuron.rs

micrograd_rs/
neuron.rs
