nvis, nhid = w*h, nhid_l0
path_ini_params_l0 = init_w_path + "dae_w_l0_init_" + str(nvis) + '_' +\
str(nhid) + ".pkl"
dae_l0 = DenoisingAutoencoder(input,
nvis=nvis,
nhid=nhid,
L1_reg=0.,
L2_reg=1e-2,
rnd=rnd,
nonlinearity=NonLinearity.SIGMOID,
cost_type=CostType.MeanSquared,
reverse=False,
corruption_level=0.2)
if not os.path.isfile(path_ini_params_l0):
dae_l0.save_params(path_ini_params_l0)
else:
dae_l0.set_params_vals(path_ini_params_l0)
# Create the AE in 2
nvis, nhid = nhid_l0, nhid_l1
path_ini_params_l1 = init_w_path + "dae_w_l1_init_" + str(nvis) + '_' +\
str(nhid) + ".pkl"
dae_l1 = DenoisingAutoencoder(dae_l0.encode((input)),
nvis=nhid_l0,
nhid=nhid_l1,
L1_reg=0.,
L2_reg=1e-2,
rnd=rnd,
nonlinearity=NonLinearity.SIGMOID,
cost_type=CostType.MeanSquared,
nvis, nhid = deep_conv_ae_in.encoder.output_size_flatten, nhid_l0
path_ini_params_l0 = init_w_path + "dae_w_l0_init_" + str(nvis) + '_' +\
str(nhid) + ".pkl"
dae_l0 = DenoisingAutoencoder(deep_conv_ae_in.encoder.output.flatten(2),
nvis=nvis,
nhid=nhid,
L1_reg=0.,
L2_reg=0.,
rnd=rnd,
nonlinearity=NonLinearity.TANH,
cost_type=CostType.MeanSquared,
reverse=False,
corruption_level=0.2)
if not os.path.isfile(path_ini_params_l0):
dae_l0.save_params(path_ini_params_l0)
else:
dae_l0.set_params_vals(path_ini_params_l0)
# Create the AE in 2
# nvis, nhid = nhid_l0, nhid_l1
# path_ini_params_l1 = init_w_path + "dae_w_l1_init_" + str(nvis) + '_' +\
# str(nhid) + ".pkl"
# dae_l1 = DenoisingAutoencoder(dae_l0.encode(),
# nvis=nhid_l0,
# nhid=nhid_l1,
# L1_reg=0.,
# L2_reg=0.,
# rnd=rnd,
# nonlinearity=NonLinearity.TANH,
# cost_type=CostType.MeanSquared,