code: def initialize_parameters(self):
      nn.init.normal_(self.token_embedding.weight, std=0.02)
      nn.init.normal_(self.positional_embedding, std=0.01)
  
      if isinstance(self.visual, ModifiedResNet):
          if self.visual.attnpool is not None:
              std = self.visual.attnpool.c_proj.in_features**-0.5
              nn.init.normal_(
                  self.visual.attnpool.q_proj.weight, std=std
              )
              nn.init.normal_(
                  self.visual.attnpool.k_proj.weight, std=std
              )
              nn.init.normal_(
                  self.visual.attnpool.v_proj.weight, std=std
              )
              nn.init.normal_(
                  self.visual.attnpool.c_proj.weight, std=std
              )
  
          for resnet_block in [
              self.visual.layer1,
              self.visual.layer2,
              self.visual.layer3,
              self.visual.layer4,
          ]:
              for name, param in resnet_block.named_parameters():
                  if name.endswith("bn3.weight"):
                      nn.init.zeros_(param)
  
      proj_std = (self.transformer.width**-0.5) * (
          (2 * self.transformer.layers) ** -0.5
      )
      attn_std = self.transformer.width**-0.5
      fc_std = (2 * self.transformer.width) ** -0.5
      for block in self.transformer.resblocks:
          nn.init.normal_(block.attn.in_proj_weight, std=attn_std)
          nn.init.normal_(block.attn.out_proj.weight, std=proj_std)
          nn.init.normal_(block.mlp.c_fc.weight, std=fc_std)
          nn.init.normal_(block.mlp.c_proj.weight, std=proj_std)
  
      if self.text_projection is not None:
          nn.init.normal_(
              self.text_projection, std=self.transformer.width**-0.5
          )
  
imports: from collections import OrderedDict
  from typing import Tuple, Union
  import numpy
  import torch
  import torch.nn.functional
  from torch import nn
label_desc: Use image node_id 2 for calling the CLIP obj's underlying member method code with example usage: obj.initialize_parameters() without return types