code: def forward(self, x):
      return self.down_proj(
          self.act_fn(self.gate_proj(x)) * self.up_proj(x)
      )
  
imports: from .configuration_baichuan import BaiChuanConfig
  from transformers import PreTrainedModel, add_start_docstrings
  from transformers.activations import ACT2FN
  from transformers.modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast, SequenceClassifierOutputWithPast
  from transformers.utils import logging, add_start_docstrings_to_model_forward, replace_return_docstrings
  import math
  from typing import List, Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.forward(x) and returns: self