Esempio n. 1
0
 def v_to_h(self, V, do_sampling=True):
     """ Compute the data representation in the hidden space """
     m = V.shape[0]
     if len(V.shape) == 1: V.shape = (1, m)
     # print V.shape, self.W.shape, self.hbias.shape
     H = Activation.sigmoid_function( np.dot(np.c_[np.ones(m), V], np.vstack((self.hbias, self.W)) ) )
     if do_sampling:
         H = self.sample(H)
     return H
Esempio n. 2
0
    def h_to_v(self, H, do_sampling=False, pois_N=None):
        """ Restore visual data using hidden space representation.
            Returns the data representation in the original space.
        """
        m = H.shape[0]
        pre_distr = np.dot( np.c_[np.ones(m), H], np.vstack((self.vbias, self.W.T)) )

        if self.mode == 'gaus-bin':
            return pre_distr

        elif self.mode == 'pois-bin':
            e = np.exp(pre_distr)
            if pois_N is None:
                return ( e.T / np.sum(e, axis=1) ).T
            else:
                return ( e.T / ((1. / pois_N) * np.sum(e, axis=1)) ).T

        V = Activation.sigmoid_function(pre_distr)
        if do_sampling:
            V = self.sample(V)
        return V