code: def get_jit_fused_vit_output_forward():
      from transformers.models.vit.modeling_vit import ViTOutput
  
      def forward(
          self: ViTOutput,
          hidden_states: torch.Tensor,
          input_tensor: torch.Tensor,
      ) -> torch.Tensor:
          hidden_states = self.dense(hidden_states)
          hidden_states = self.dropout_add(
              hidden_states,
              input_tensor,
              self.dropout.p,
              self.dropout.training,
          )
          return hidden_states
  
      return forward
  
file_path: ColossalAI/colossalai/shardformer/modeling/vit.py
imports: import math
  from typing import List, Optional, Tuple, Union
  import torch
  from transformers.models.vit.modeling_vit import BaseModelOutput, ViTEncoder
  from transformers.utils import logging
  from colossalai.pipeline.stage_manager import PipelineStageManager
label_desc: Use image node_id 6 for calling a global function with example usage: get_jit_fused_vit_output_forward() and returns: forward, hidden_states