code: def reset_program_state_dict(
      args, model, state_dict, pretrained_state_dict
  ):
      """
      Initialize the parameter from the bert config, and set the parameter by
      reseting the state dict."
      """
      scale = args.init_range
      reset_state_dict = {}
      reset_parameter_names = []
      for n, p in state_dict.items():
          if n in pretrained_state_dict:
              log.info("p_name: %s , pretrained name: %s" % (p.name, n))
              reset_state_dict[p.name] = np.array(
                  pretrained_state_dict[n]
              )
              reset_parameter_names.append(n)
          #  elif p.name in pretrained_state_dict and "bert" in n:
          #      reset_state_dict[p.name] = np.array(pretrained_state_dict[p.name])
          #      reset_parameter_names.append(n)
          else:
              log.info(
                  "[RANDOM] p_name: %s , pretrained name: %s"
                  % (p.name, n)
              )
              dtype_str = "float32"
              if str(p.dtype) == "VarType.FP64":
                  dtype_str = "float64"
              reset_state_dict[p.name] = np.random.normal(
                  loc=0.0, scale=scale, size=p.shape
              ).astype(dtype_str)
      log.info(
          "the following parameter had reset, please check. {}".format(
              reset_parameter_names
          )
      )
      return reset_state_dict
  
imports: import os
  import sys
  import math
  import time
  import numpy
  import pickle
  import paddle
  import paddle.fluid
  import paddle.fluid.layers
  import paddle.static
  from paddle.common_ops_import import LayerHelper, check_type, check_variable_and_dtype
  from paddle.fluid.framework import Variable
  import pgl
  from pgl.utils.logger import log
label_desc: Use image node_id 15 for calling a global function with example usage: reset_program_state_dict(args, model, state_dict, pretrained_state_dict) and returns: reset_state_dict