code: def execute(
      self,
      input_size: int,
      n_layers: int,
      hidden_size: int,
      optimizer_name: str,
      optimizer_params: dict,
      loss_fn_name: str,
      output_size: int = None,
  ):
      model = LMFFNet(
          token_num=output_size,
          hidden_size=hidden_size,
          n_layers=n_layers,
          seq_len=input_size,
          optimizer_name=optimizer_name,
          optimizer_kwargs=optimizer_params,
          loss_fn_name=loss_fn_name,
          epochs=-1,
          predicted_tokens=-1,
      )
      self.model = model
  
imports: from abc import ABC, abstractmethod
  import torch
  from nebullvm.operations.base import Operation
  from forward_forward.utils.modules import FCNetFFProgressive, RecurrentFCNetFF, LMFFNet
label_desc: Use image node_id 2 for calling the LMFFNetBuildOperation obj's underlying member method code with example usage: obj.execute(input_size, n_layers, hidden_size, optimizer_name, optimizer_params, loss_fn_name, output_size) without return types