code: def named_apply(
      fn: Callable,
      module: nn.Module,
      name="",
      depth_first=True,
      include_root=False,
  ) -> nn.Module:
      if not depth_first and include_root:
          fn(module=module, name=name)
      for child_name, child_module in module.named_children():
          child_name = (
              ".".join((name, child_name)) if name else child_name
          )
          named_apply(
              fn=fn,
              module=child_module,
              name=child_name,
              depth_first=depth_first,
              include_root=True,
          )
      if depth_first and include_root:
          fn(module=module, name=name)
      return module
  
imports: from functools import partial
  import math
  import logging
  from typing import Sequence, Tuple, Union, Callable
  import torch
  import torch.nn
  import torch.utils.checkpoint
  from torch.nn.init import trunc_normal_
  from dinov2.layers import Mlp, PatchEmbed, SwiGLUFFNFused, MemEffAttention, NestedTensorBlock
label_desc: Use image node_id 1 for calling a global function with example usage: named_apply(fn, module, name, depth_first, include_root) and returns: module