Some sample text here, I suppose
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pub trait Layer { /// Propagates input forward through the layer to produce an output Matrix fn forward_prop(&mut self, input: &Matrix, batch_size: usize, training: bool) -> ForwardPropResult; /// Propoagates a given derivative backward through the layer, /// updating the weights and biases within and producing a /// consecutive derivative Matrix to further propogate backwards fn back_prop(&mut self, bp_deriv: &Matrix, learning_rate: f64, batch_size: usize) -> BackPropResult; /// Given a learning rate and a Matrix of gradients for the weights, /// update the weights in the layer fn update_weights(&mut self, learning_rate: f64, gradient: &Matrix, batch_size: usize) -> WeightUpdateResult; /// Given a learning rate and a Matrix of gradients for the biases, /// update the biases in the layer fn update_biases(&mut self, learning_rate: f64, gradient: &Matrix, batch_size: usize) -> BiasUpdateResult; fn get_output_len(&self) -> usize; }