code: def optimizer_setter(
          net, param, value, optimizer_attr='optimizer_', optimizer_name='optimizer'
      ):
      
      if param == 'lr':
          param_group = 'all'
          param_name = 'lr'
          net.lr = value
      else:
          param_group, param_name = _extract_optimizer_param_name_and_group(
              optimizer_name, param)
  
      _set_optimizer_param(
          optimizer=getattr(net, optimizer_attr),
          param_group=param_group,
          param_name=param_name,
          value=value
      )
docs: Handle setting of optimizer parameters such as learning rate and
      parameter group specific parameters such as momentum.
  
      The parameters ``optimizer_attr`` and ``optimizer_name`` can be specified
      if there exists more than one optimizer (e.g., in seq2seq models).