use std::marker::PhantomData;
use crate::neural_network::layer_trait::Layer;
use crate::tensor_library::matrix::Matrix;
pub struct TestLayer<T> {
input_shape : Vec<usize>,
output_shape : Vec<usize>,
phantom: PhantomData<T>,
}
impl<T> Layer for TestLayer<T> {
type CType = T;
fn forward(&mut self, input : Matrix<T>) -> Matrix<Self::CType> where <Self as Layer>::CType: Clone + Default {
todo!()
}
fn get_input_shape(&self) -> &Vec<usize> {
&self.input_shape
}
fn get_output_shape(&self) -> &Vec<usize> {
&self.output_shape
}
}