gibbs_revised.cpp

#include <iostream>
#include <mlpack/core.hpp>
#include <mlpack/prereqs.hpp>
#include <mlpack/core/dists/gaussian_distribution.hpp>

using namespace mlpack;
using namespace mlpack::distribution;

/*
 * This class implements Gibbs
 * Sampler. The sampler samples
 * from the conditional distrbution
 * P(y|x).
 * ActivationFnc: Probability Distribution
 */

template<typename ActivationFnc, typename... Args>
class GibbsSampler
{
public:

   /**
	* Create the GibbsSampler object using the specified Probability Distribution.
	* 
	* @param dist probability distribution
	* @param args arguments for the distribution
	*/
	GibbsSampler(Args&... args):
	distribution(new ActivationFnc(args...))
	{/*Nothing to do here*/}

 
   /**
 	* Genereate the samples from the distribution
    * store the sampled value in output variable
    */
	template<typename eT>
	void Sampler(arma::Mat<eT>& output)
	{

		output = distribution.Random();
	}


private:
	/* Distribution class*/
	ActivationFnc distribution;
};


int main()
{
	// combine the incoming mean and variance in some way
	arma::mat visible = {1,0};
	arma::mat hidden = {1,0};
	arma::vec mean = visible;
	arma::vec variance = arma::ones(2);
	GibbsSampler<GaussianDistribution, arma::vec, arma::vec> gibbs(mean, variance);
	// suppose we want to sample hidden layer given the visible layer
	gibbs.Sampler(hidden);
}