code: def forward(self, hidden_states):
      hidden_states = self.c_fc(hidden_states)
      hidden_states = self.act(hidden_states)
      hidden_states = self.c_proj(hidden_states)
      return hidden_states
  
imports: import torch
  import torch.distributed
  from torch import nn
  from transformers.activations import ACT2FN
  from typing import Optional, List, Tuple
  from text_generation_server.utils import paged_attention, flash_attn
  from text_generation_server.utils.layers import TensorParallelRowLinear, TensorParallelColumnLinear, TensorParallelHead, TensorParallelEmbedding, FastLayerNorm, get_linear
label_desc: Use image node_id 2 for calling the MLP obj's underlying member method code with example usage: obj.forward(hidden_states) and returns: hidden_states