Exemplo n.º 1
0
# model configurations
config.batch_size = FLAGS.batch_size
config.z_dim = 100  # number inputs to gener
config.c_dim = 1
config.gf_dim = FLAGS.gf_dim  # number of gener conv filters
config.df_dim = FLAGS.df_dim  # number of discim conv filters
config.gfc_dim = 1024  # number of gener fully connecter layer units
config.dfc_dim = 1024  # number of discim fully connected layer units
config.alpha = 0.1  # leaky relu alpha
config.batch_norm = True
config.minibatch_discrim = True

# training hyperparameters
config.epoch = FLAGS.epoch
config.learning_rate = FLAGS.learning_rate  # optim learn rate
config.beta1 = FLAGS.beta1  # momentum
config.repeat_data = True
config.shuffle_data = True
config.buffer_size = 4
config.drop_remainder = True  # currently fails if false!
config.gener_iter = FLAGS.gener_iter  # times to update generator per discriminator update
config.noisy_inputs = False  # add some small noise to the input images
config.flip_inputs = False  # whether to flip the black white pixels

# i/o structures
config.log_dir = 'log'
config.out_dir = 'out'
config.samp_dir = 'samp'
config.chkp_dir = 'chkp'
config.paint_dir = 'paint'
config.post_dir = 'post'