code: def init_weights_vit_timm(module: nn.Module, name: str = ""):
      """ViT weight initialization, original timm impl (for reproducibility)"""
      if isinstance(module, nn.Linear):
          trunc_normal_(module.weight, std=0.02)
          if module.bias is not None:
              nn.init.zeros_(module.bias)
      elif hasattr(module, "init_weights"):
          module.init_weights()
  
imports: import math
  from functools import partial
  from copy import deepcopy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch.nn.init import trunc_normal_
  from timm.models.helpers import named_apply
  from timm.models.layers import PatchEmbed
  from src.models.modules.mha import MHA
  from src.models.modules.mlp import Mlp, FusedDenseGeluDense
  from src.models.modules.block import Block
label_desc: Use image node_id 4 for calling a global function with example usage: init_weights_vit_timm(module, name) without return types