code: def forward(self, x):
      x = self.forward_features(x)
      if self.head_dist is not None:
          x, x_dist = self.head(x[0]), self.head_dist(x[1])
          if self.training and not torch.jit.is_scripting():
              # during inference, return the average of both classifier predictions
              return x, x_dist
          else:
              return (x + x_dist) / 2
      else:
          x = self.head(x)
      return x
  
imports: from functools import partial
  from collections import OrderedDict
  import torch
  import torch.nn
label_desc: Use image node_id 3 for calling the VisionTransformer obj's underlying member method code with example usage: obj.forward(x) and returns: x, x,  x_dist, unknown