newron 0.5.1

A Rust library to train and infer deep learning models.
Documentation 
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use crate::layers::layer::Layer;
use crate::tensor::Tensor;
use crate::layers::layer::LearnableParams;

pub struct ReLU {
    input: Tensor
}

impl Layer for ReLU {
    fn get_info(&self) -> String {
        format!("ReLU Layer")
    }

    fn forward(&mut self, input: Tensor, _training: bool) -> Tensor {
        self.input = input;
        self.input.map(|x| x.max(0.0))
    }

    fn backward(&mut self, gradient: &Tensor) -> Tensor {
        let relu_grad = self.input.map(|x| if x > 0.0 { 1.0 } else { 0.0 });
        gradient.mult_el(&relu_grad)
    }

    fn get_params_list(&self) -> Vec<LearnableParams> {
        vec![]
    }


    fn get_grad(&self, _param: &LearnableParams) -> &Tensor {
        panic!("Layer does not have learnable parameters.")
    }

    fn get_param(&mut self, _param: &LearnableParams) -> &mut Tensor {
        panic!("Layer does not have learnable parameters.")
    }
}

impl ReLU {
    pub(crate) fn new() -> ReLU {
        ReLU {
            input: Tensor::new(vec![], vec![])
        }
    }
}