parameters: (cells, prefix, epoch, symbol, arg_params, aux_params)
docstring: Save checkpoint for model using RNN cells.
      Unpacks weight before saving.
  
      Parameters
      ----------
      cells : mxnet.rnn.RNNCell or list of RNNCells
          The RNN cells used by this symbol.
      prefix : str
          Prefix of model name.
      epoch : int
          The epoch number of the model.
      symbol : Symbol
          The input symbol
      arg_params : dict of str to NDArray
          Model parameter, dict of name to NDArray of net's weights.
      aux_params : dict of str to NDArray
          Model parameter, dict of name to NDArray of net's auxiliary states.
  
      Notes
      -----
      - ``prefix-symbol.json`` will be saved for symbol.
      - ``prefix-epoch.params`` will be saved for parameters.
docstring_summary: Save checkpoint for model using RNN cells.
      Unpacks weight before saving.
docstring_tokens: Save checkpoint for model using RNN cells . Unpacks weight before saving .
function: def save_rnn_checkpoint(cells, prefix, epoch, symbol, arg_params, aux_params):
      """Save checkpoint for model using RNN cells.
      Unpacks weight before saving.
  
      Parameters
      ----------
      cells : mxnet.rnn.RNNCell or list of RNNCells
          The RNN cells used by this symbol.
      prefix : str
          Prefix of model name.
      epoch : int
          The epoch number of the model.
      symbol : Symbol
          The input symbol
      arg_params : dict of str to NDArray
          Model parameter, dict of name to NDArray of net's weights.
      aux_params : dict of str to NDArray
          Model parameter, dict of name to NDArray of net's auxiliary states.
  
      Notes
      -----
      - ``prefix-symbol.json`` will be saved for symbol.
      - ``prefix-epoch.params`` will be saved for parameters.
      """
      if isinstance(cells, BaseRNNCell):
          cells = [cells]
      for cell in cells:
          arg_params = cell.unpack_weights(arg_params)
      save_checkpoint(prefix, epoch, symbol, arg_params, aux_params)
function_tokens: def save_rnn_checkpoint ( cells , prefix , epoch , symbol , arg_params , aux_params ) : if isinstance ( cells , BaseRNNCell ) : cells = [ cells ] for cell in cells : arg_params = cell . unpack_weights ( arg_params ) save_checkpoint ( prefix , epoch , symbol , arg_params , aux_params )