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 _pos_embed(self, x):
      if self.no_embed_class:
          # deit-3, updated JAX (big vision)
          # position embedding does not overlap with class token, add then concat
          x = x + self.pos_embed
          if self.cls_token is not None:
              x = torch.cat(
                  (self.cls_token.expand(x.shape[0], -1, -1), x), dim=1
              )
      else:
          # original timm, JAX, and deit vit impl
          # pos_embed has entry for class token, concat then add
          if self.cls_token is not None:
              x = torch.cat(
                  (self.cls_token.expand(x.shape[0], -1, -1), x), dim=1
              )
          x = x + self.pos_embed
      return x
  
imports: import math
  import re
  from collections import OrderedDict
  from copy import deepcopy
  from functools import partial
  import torch
  import torch.nn
  import torch.nn.functional
  from einops import rearrange
  from timm.models.helpers import named_apply
  from torch.nn.init import trunc_normal_
  from torchvision.ops import StochasticDepth
  from flash_attn.layers.patch_embed import PatchEmbed
  from flash_attn.modules.block import Block
  from flash_attn.modules.mha import MHA
  from flash_attn.modules.mlp import FusedMLP, Mlp
label_desc: Use image node_id 5 for calling the VisionTransformer obj's underlying member method code with example usage: obj._pos_embed(x) and returns: x