class_docstr: Twins Vision Transfomer (Revisiting Spatial Attention)
  
  Adapted from PVT (PyramidVisionTransformer) class at https://github.com/whai362/PVT.git
code: def forward_head(self, x, pre_logits: bool = False):
      if self.global_pool == "avg":
          x = x.mean(dim=1)
      x = self.head_drop(x)
      return x if pre_logits else self.head(x)
  
imports: import math
  from functools import partial
  from typing import Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from timm.data import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
  from timm.layers import Mlp, DropPath, to_2tuple, trunc_normal_, use_fused_attn
  from ._builder import build_model_with_cfg
  from ._features_fx import register_notrace_module
  from ._registry import register_model, generate_default_cfgs
  from .vision_transformer import Attention
label_desc: Use image node_id 9 for calling the Twins obj's underlying member method code with example usage: obj.forward_head(x, pre_logits) and returns: unknown