pytorch 模型加权

  

   

    

     

    
    

     

      from collections import OrderedDict
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      import torch
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      from LPRNetN.model.STN import STNet
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      STN = STNet()
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      state_dict1 = torch.load('weights/STNNet.pth', map_location=lambda storage, loc: storage)
     
    
   

    

     

    
    

     

      state_dict2 = torch.load('weights/STNNet.pth', map_location=lambda storage, loc: storage)
     
    
   

    

     

    
    

     

      new_state_dict1 = OrderedDict()
     
    
   

    

     

    
    

     

      new_state_dict2 = OrderedDict()
     
    
   

    

     

    
    

     

      for k, v in state_dict2.items():
     
    
   

    

     

    
    

     

          name = k.replace('module.', '')  # remove `module.`
     
    
   

    

     

    
    

     

          new_state_dict2[name] = v
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      for k, v in state_dict1.items():
     
    
   

    

     

    
    

     

          name = k.replace('module.', '')  # remove `module.`
     
    
   

    

     

    
    

     

          new_state_dict1[name] =0.5*new_state_dict2[name]+0.5* v
     
    
   

    

     

    
    

     
 
     
    
   

    

     

    
    

     

      STN.load_state_dict(new_state_dict1)
     
    
  
 

文章来源: blog.csdn.net，作者：AI视觉网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/122708940