average_loss_dec = 0. average_loss_enc = 0. average_energy_pos = 0. average_energy_neg = 0. average_ent_enc = 0. average_ent_dec = 0. start = time.time() try: # visualization if step % vis_steps == 0: dec_samples = dec.get_v_mean(num_samples) utils.save_images( dec_samples.reshape((num_samples, ) + pixels), os.path.join(outf, 'dec_{}_{}.png'.format(method, step))) samples = rbm.get_independent_means(num_samples) utils.save_images( samples.reshape((num_samples, ) + pixels), os.path.join(outf, 'rbm_{}_{}.png'.format(method, step))) chain_samples = rbm.get_samples_single_chain(num_samples) utils.save_images( chain_samples.reshape((num_samples, ) + pixels), os.path.join(outf, 'rbm_single_chain_{}_{}.png'.format(method, step)), size=(num_samples / adjacent_samples, adjacent_samples)) # plotting filters w = rbm.w.numpy() weights = np.transpose(w).reshape((hid_dim, ) + pixels) utils.save_images(weights[:100], os.path.join(