code: def forward(
      self,
      hidden_states,
      attention_mask=None,
      head_mask=None,
      output_attentions=False,
  ):
      self_outputs = self.attention(
          hidden_states,
          attention_mask=attention_mask,
          head_mask=head_mask,
          output_attentions=output_attentions,
      )
      attention_output = self.output(self_outputs[0], hidden_states)
      outputs = (attention_output,) + self_outputs[1:]
      return outputs
  
imports: from collections import namedtuple
  from dataclasses import asdict, dataclass
  import torch
  from mmf.utils.general import retry_n
  from omegaconf import OmegaConf
  from packaging import version
  from torch import nn
label_desc: Use image node_id 2 for calling the ViTAttention obj's underlying member method code with example usage: obj.forward(hidden_states, attention_mask, head_mask, output_attentions) and returns: outputs