code: def copy_params(self):
      for model_pair in self.model_pairs:
          for param, param_m in zip(
              model_pair[0].parameters(), model_pair[1].parameters()
          ):
              param_m.data.copy_(param.data)  # initialize
              param_m.requires_grad = False
  
file_path: blip/models/blip_pretrain.py
imports: from models.med import BertConfig, BertModel, BertLMHeadModel
  from transformers import BertTokenizer
  import transformers
  import torch
  from torch import nn
  import torch.nn.functional
  from models.blip import create_vit, init_tokenizer, load_checkpoint
  from typing import List
label_desc: Use image node_id 3 for calling the BLIP_Pretrain obj's underlying member method code with example usage: obj.copy_params() without return types