code: def load_pretrain_params(self, exe, pretrain, prog, place):
      logger.info(
          "Load pretrain weights from {}, exclude fc layer.".format(
              pretrain
          )
      )
  
      state_dict = fluid.load_program_state(pretrain)
      dict_keys = list(state_dict.keys())
      for name in dict_keys:
          if "fc_0" in name:
              del state_dict[name]
              logger.info(
                  "Delete {} from pretrained parameters. Do not load it".format(
                      name
                  )
              )
      fluid.set_program_state(prog, state_dict)
  
file_path: PaddleHub/modules/video/classification/videotag_tsn_lstm/resource/models/attention_lstm/attention_lstm.py
imports: import logging
  import paddle.fluid
  from paddle.fluid import ParamAttr
  from ..model import ModelBase
  from .lstm_attention import LSTMAttentionModel
label_desc: Use image node_id 11 for calling the AttentionLSTM obj's underlying member method code with example usage: obj.load_pretrain_params(exe, pretrain, prog, place) without return types