class_docstr: Vision Transformer with support for patch or hybrid CNN input stage
      
class_docstr_tok: ["Vision","Transformer","with","support","for","patch","or","hybrid","CNN","input","stage"]
code: def forward(self, x):
      x = self.forward_features(x)
      #         x = self.head(x)
      return x
  
imports: import math
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.utils.checkpoint
  from timm.models.layers import drop_path, to_2tuple, trunc_normal_
  from timm.models.registry import register_model
  from lavis.common.dist_utils import download_cached_file
label_desc: Use image node_id 7 for calling the VisionTransformer obj's underlying member method code with example usage: obj.forward(x) and returns: x