code: def forward(
      self,
      pixel_values: Optional[torch.FloatTensor],
      output_hidden_states: Optional[bool] = None,
      return_dict: Optional[bool] = None,
  ) -> Union[Tuple, BaseModelOutputWithPoolingAndNoAttention]:
      output_hidden_states = (
          output_hidden_states
          if output_hidden_states is not None
          else self.config.output_hidden_states
      )
      return_dict = (
          return_dict
          if return_dict is not None
          else self.config.use_return_dict
      )
  
      encoder_outputs = self.encoder(
          pixel_values,
          output_hidden_states=output_hidden_states,
          return_dict=return_dict,
      )
      last_hidden_state = encoder_outputs[0]
      # global average pooling, n c w h -> n c
      pooled_output = last_hidden_state.mean(dim=[-2, -1])
  
      if not return_dict:
          return (last_hidden_state, pooled_output) + encoder_outputs[
              1:
          ]
  
      return BaseModelOutputWithPoolingAndNoAttention(
          last_hidden_state=last_hidden_state,
          pooler_output=pooled_output,
          hidden_states=encoder_outputs.hidden_states,
      )
  
imports: import math
  from collections import OrderedDict
  from typing import Optional, Tuple, Union
  import torch
  import torch.utils.checkpoint
  from torch import nn
  from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
  from ....activations import ACT2FN
  from ....modeling_outputs import BaseModelOutputWithNoAttention, BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
  from ....modeling_utils import PreTrainedModel
  from ....utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward, logging
  from .configuration_van import VanConfig
label_desc: Use image node_id 2 for calling the VanModel obj's underlying member method code with example usage: obj.forward(pixel_values, output_hidden_states, return_dict) and returns: BaseModelOutputWithPoolingAndNoAttention, unknown