class_docstr: Transformer in Transformer - https://arxiv.org/abs/2103.00112
      
code: def forward_head(self, x, pre_logits: bool = False):
      if self.global_pool:
          x = (
              x[:, 1:].mean(dim=1)
              if self.global_pool == "avg"
              else x[:, 0]
          )
      x = self.head_drop(x)
      return x if pre_logits else self.head(x)
  
imports: import math
  import torch
  import torch.nn
  from torch.utils.checkpoint import checkpoint
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import Mlp, DropPath, trunc_normal_, _assert, to_2tuple
  from ._builder import build_model_with_cfg
  from ._registry import register_model
  from .vision_transformer import resize_pos_embed
label_desc: Use image node_id 9 for calling the TNT obj's underlying member method code with example usage: obj.forward_head(x, pre_logits) and returns: unknown