import tensorflow as tf

tf.app.flags.DEFINE_integer('ws_nb_iters_ft', 400, 'WS: # of iterations for global fine-tuning')
tf.app.flags.DEFINE_integer('ws_nb_iters_feval', 25, 'WS: # of iterations for fast evaluation')
tf.app.flags.DEFINE_float('ws_prune_ratio_exp', 3.0, 'WS: pruning ratio\'s exponent term')
tf.app.flags.DEFINE_float('ws_iter_ratio_beg', 0.1, 'WS: iteration ratio (at starting time)')
tf.app.flags.DEFINE_float('ws_iter_ratio_end', 0.5, 'WS: iteration ratio (at ending time)')
tf.app.flags.DEFINE_float('ws_mask_update_step', 500, 'WS: step size for updating the pruning mask')
