code: def forward(
      self, hidden_states: Optional[Tuple[torch.FloatTensor]]
  ) -> torch.FloatTensor:
      hidden_states = self.c_fc(hidden_states)
      hidden_states = self.act(hidden_states)
      hidden_states = self.c_proj(hidden_states)
      return hidden_states
  
imports: from typing import Optional, Tuple, Union
  import torch
  import torch.nn
  from transformers.activations import ACT2FN
  from transformers.models.gpt2.modeling_gpt2 import BaseModelOutputWithPastAndCrossAttentions, GPT2PreTrainedModel
  from transformers.pytorch_utils import Conv1D
label_desc: Use image node_id 2 for calling the GPT2MLP obj's underlying member method code with example usage: obj.forward(hidden_states) and returns: hidden_states