#pragma once

#include "core/omp_config.h"

#include "utils/vector.h"
#include "utils/matrix.h"
#include "modules/neural_networks/layers/Layer.h"

#include "random/random.h"


namespace neural_networks{

	template <typename T>
	struct Dropout_Layer : Layer<T>{

		// Store rate, we invert it as for example for dropout
		// of 0.1 we need a success rate of 0.9
		T rate = T{0};
		utils::Matrix<T> binary_mask;
		
		utils::Matrix<T> _inputs;
		utils::Matrix<T> outputs;

		utils::Matrix<T> dinputs;

		
		
		// Default Constructor
		Dropout_Layer() = default;

		// Constructor
    	Dropout_Layer(const T rate){
    		this->rate = T{1} - rate;
        	
        }

        void forward(const utils::Matrix<T>& inputs){
        	// Save input values
        	_inputs = inputs;

        	// Generate binary_mask
        	binary_mask = rng::binomial<T>(inputs.rows(), inputs.cols(), 1, rate);
        	// Scale binary_mask
        	binary_mask = numerics::div(binary_mask, rate);

        	// Apply binary mask to output values
        	outputs = numerics::mul(binary_mask, inputs);

        }

        void backward(const utils::Matrix<T>& dvalues){
        	dinputs = numerics::mul(dvalues, binary_mask);
        }

	};



} // end namespace neural_networks