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(
outf,
'filters_{}_{}.png'.format(method, step)),
normalize=True)
