if self.use_vq:
            z_sampled, loss, info = self.vqvae(z, is_voxel=False)
            #print("lnn-z_sampled",z_sampled.shape)
            #print("lnn-loss",loss.shape)
            output_dict.update({'embed_loss': loss})
        else:
            z_sampled, z_mu, z_sigma = self.sample_z(z)
            output_dict.update({
                'z_mu': z_mu,
                'z_sigma': z_sigma})
        
        middd = z_sampled
        
        
        ##
        samples_array = np.load('/samples_array.npy') # 8 128 3 25 25

        samples_array = samples_array * 10  # sc