code: def load_pretrain_params(self, exe, pretrain, prog, place):
      def is_parameter(var):
          return isinstance(var, fluid.framework.Parameter)
  
      params_list = list(filter(is_parameter, prog.list_vars()))
      for param in params_list:
          print(param.name)
  
      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]
              print(
                  "Delete {} from pretrained parameters. Do not load it".format(
                      name
                  )
              )
      fluid.set_program_state(prog, state_dict)
  
imports: import numpy
  import paddle.fluid
  from paddle.fluid import ParamAttr
  from ..model import ModelBase
  from .tsn_res_model import TSN_ResNet
  import logging
label_desc: Use image node_id 13 for calling the TSN obj's underlying member method code with example usage: obj.load_pretrain_params(exe, pretrain, prog, place) and returns: isinstance