text: import torch 
  from collections import OrderedDict
  
  # from_path = '/HOME/scz0088/run/datasets/weights/model_seresnet50.pth.tar'
  # save_path = './work_dirs/seresnet50/model_seresnet5.pth.tar'
  # para_dict = torch.load(from_path)['state_dict']
  # new_dict = OrderedDict()
  # print(para_dict.keys())
  # for key, value in para_dict.items():
  #     # print(key, key.replace('attention', 'receptive_field_attention'))
  #     new_dict[key.replace('se', 'attention')] = value 
  # torch.save(new_dict, save_path)
  
  ###########################################################################
  
  # from_path = '/HOME/scz0088/run/datasets/weights/model_r50_cbam.pth'
  # save_path = './work_dirs/resnet50_cbam/model_r50_cbam.pth'
  # para_dict = torch.load(from_path)['state_dict']
  # new_dict = OrderedDict()
  # print(para_dict.keys())
  # for key, value in para_dict.items():
  #     # print(key, key.replace('attention', 'receptive_field_attention'))
  #     new_dict[key.replace('cbam', 'attention')] = value 
  # torch.save(new_dict, save_path)
  
  ########################################################################## 
  
  from_path = '/HOME/scz0088/run/datasets/weights/model_r50_rf.pth.tar'
  save_path = './work_dirs/resnet50_rf/model_r50_rf.pth.tar'
  para_dict = torch.load(from_path)#['state_dict']
  new_dict = OrderedDict()
  print(para_dict.keys())
  for key, value in para_dict.items():
      # print(key, key.replace('attention', 'receptive_field_attention'))
      new_dict[key.replace('receptive_field_attention', 'attention')] = value
  torch.save(new_dict, save_path)