code: def normal_init(module, mean=0, std=1, bias=0):
      if hasattr(module, "weight") and module.weight is not None:
          nn.init.normal_(module.weight, mean, std)
      if hasattr(module, "bias") and module.bias is not None:
          nn.init.constant_(module.bias, bias)
  
imports: from abc import ABC, abstractmethod
  import torch
  import torch.nn
  import torch.nn.functional
  import math
  from .multimodal_encoder.builder import build_vision_tower
  import pdb
  from ferret.constants import IGNORE_INDEX, IMAGE_TOKEN_INDEX, DEFAULT_IMAGE_PATCH_TOKEN, DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN
label_desc: Use image node_id 8 for calling a global function with example usage: normal_init(module, mean, std, bias) without return types