class_docstr: Vision Transformer
  A PyTorch impl of : `An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale`  -
      https://arxiv.org/abs/2010.11929
code: def forward(self, x, register_blk=-1):
      B = x.shape[0]
      x = self.patch_embed(x)
  
      cls_tokens = self.cls_token.expand(
          B, -1, -1
      )  # stole cls_tokens impl from Phil Wang, thanks
      x = torch.cat((cls_tokens, x), dim=1)
  
      x = x + self.pos_embed[:, : x.size(1), :]
      x = self.pos_drop(x)
  
      for i, blk in enumerate(self.blocks):
          x = blk(x, register_blk == i)
      x = self.norm(x)
  
      return x
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from functools import partial
  from timm.models.vision_transformer import _cfg, PatchEmbed
  from timm.models.registry import register_model
  from timm.models.layers import trunc_normal_, DropPath
  from timm.models.helpers import named_apply, adapt_input_conv
  from fairscale.nn.checkpoint.checkpoint_activations import checkpoint_wrapper
  from lavis.models.base_model import BaseEncoder
label_desc: Use image node_id 4 for calling the VisionTransformer obj's underlying member method code with example usage: obj.forward(x, register_blk) and returns: x