code: def load_var(executor, main_program=None, var=None, filename=None):
      """
      load_var to certain program
      :param executor: executor
      :param main_program: the program to load
      :param var: the variable name in main_program.
      :file_name: the file name of the file to load.
      :return: None
      """
      load_prog = fluid.Program()
      load_block = load_prog.global_block()
  
      if main_program is None:
          main_program = fluid.default_main_program()
  
      if not isinstance(main_program, fluid.Program):
          raise TypeError("program should be as Program type or None")
  
      vars = list(filter(None, main_program.list_vars()))
      # save origin param shape
      orig_para_shape = {}
      load_var_map = {}
      for each_var in vars:
          if each_var.name != var:
              continue
          assert isinstance(each_var, fluid.Variable)
          if each_var.type == fluid.core.VarDesc.VarType.RAW:
              continue
  
          if isinstance(each_var, fluid.framework.Parameter):
              orig_para_shape[each_var.name] = tuple(
                  each_var.desc.get_shape()
              )
          new_var = _clone_var_in_block_(load_block, each_var)
          if filename is not None:
              load_block.append_op(
                  type="load",
                  inputs={},
                  outputs={"Out": [new_var]},
                  attrs={"file_path": filename},
              )
  
      executor.run(load_prog)
  
imports: import paddle.fluid
  from paddle.fluid.layer_helper import LayerHelper
label_desc: Use image node_id 4 for calling a global function with example usage: load_var(executor, main_program, var, filename) without return types