code: def forward(self, img, return_sampled_token_ids=False):
      x = self.to_patch_embedding(img)
      b, n, _ = x.shape
  
      cls_tokens = repeat(self.cls_token, "() n d -> b n d", b=b)
      x = torch.cat((cls_tokens, x), dim=1)
      x += self.pos_embedding[:, : (n + 1)]
      x = self.dropout(x)
  
      x, token_ids = self.transformer(x)
  
      logits = self.mlp_head(x[:, 0])
  
      if return_sampled_token_ids:
          # remove CLS token and decrement by 1 to make -1 the padding
          token_ids = token_ids[:, 1:] - 1
          return logits, token_ids
  
      return logits
  
imports: import torch
  import torch.nn.functional
  from torch.nn.utils.rnn import pad_sequence
  from torch import nn, einsum
  from einops import rearrange, repeat
  from einops.layers.torch import Rearrange
label_desc: Use image node_id 2 for calling the ViT obj's underlying member method code with example usage: obj.forward(img, return_sampled_token_ids) and returns: logits, logits,  token_ids