(self, global_step=None)
return var_restore_dict
using vars_average to restotre vars
using vars_average to restotre vars
using vars_average to restotre vars
def make_restore_average_vars_dict(self, global_step=None):
    ''' using vars_average to restotre vars'''
    model_avg_conf = self.config['solver']['model_average']
    var_avg_decay = model_avg_conf['var_avg_decay']

    var_restore_dict = {}
    variable_averages = self.get_var_avg_ema(var_avg_decay, global_step)
    for var in tf.global_variables():
      if var in tf.trainable_variables():
        name = variable_averages.average_name(var)
      else:
        name = var.op.name
      var_restore_dict[name] = var
    return var_restore_dict
def make_restore_average_vars_dict ( self , global_step = None ) : model_avg_conf = self . config [ 'solver' ] [ 'model_average' ] var_avg_decay = model_avg_conf [ 'var_avg_decay' ] var_restore_dict = { } variable_averages = self . get_var_avg_ema ( var_avg_decay , global_step ) for var in tf . global_variables ( ) : if var in tf . trainable_variables ( ) : name = variable_averages . average_name ( var ) else : name = var . op . name var_restore_dict [ name ] = var return var_restore_dict