code: def forward(self, hidden_states):
      hidden_states = self.dense_h_to_4h(hidden_states)
      hidden_states = self.act(hidden_states)
      hidden_states = self.dense_4h_to_h(hidden_states)
      return hidden_states
  
imports: from typing import Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import CrossEntropyLoss
  from ...activations import ACT2FN
  from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, replace_return_docstrings
  from ...modeling_outputs import BaseModelOutputWithPast, CausalLMOutputWithPast
  from ...modeling_utils import PreTrainedModel
  from ...utils import logging
  from .configuration_gpt_neox import GPTNeoXConfig
label_desc: Use image node_id 2 for calling the GPTNeoXMLP obj's underlying member method code with example usage: obj.forward(hidden_states) and returns: hidden_states