burn-nn 0.20.1

Neural network building blocks for the Burn deep learning framework
Documentation 
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use burn_core as burn;

use burn::module::Module;
use burn::tensor::Tensor;
use burn::tensor::backend::Backend;

/// Applies the sigmoid function element-wise
/// See also [sigmoid](burn::tensor::activation::sigmoid)
#[derive(Module, Clone, Debug, Default)]
pub struct Sigmoid;

impl Sigmoid {
    /// Create the module.
    pub fn new() -> Self {
        Self {}
    }
    /// Applies the forward pass on the input tensor.
    ///
    /// # Shapes
    ///
    /// - input: `[..., any]`
    /// - output: `[..., any]`
    pub fn forward<B: Backend, const D: usize>(&self, input: Tensor<B, D>) -> Tensor<B, D> {
        burn::tensor::activation::sigmoid(input)
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn display() {
        let layer = Sigmoid::new();

        assert_eq!(alloc::format!("{layer}"), "Sigmoid");
    }
}