code: def get_autocorr(feature):
      feature = torch.from_numpy(feature)
      feature_length = feature.shape[1]
      autocorr_vec = torch.Tensor(feature_length - 2)
      for j in range(1, feature_length - 1):
          autocorr_vec[j - 1] = torch.mean(
              autocorr(feature[:, :-j], feature[:, j:])
          )
      return autocorr_vec
  
file_path: BigDL/python/chronos/example/simulator/dpgansimulator_wwt.py
imports: import sys
  import time
  import torch
  import pickle
  import numpy
  import argparse
  import matplotlib.pyplot
  from bigdl.chronos.simulator import DPGANSimulator
  from bigdl.chronos.simulator.doppelganger.output import Output, OutputType, Normalization
label_desc: Use image node_id 2 for calling a global function with example usage: get_autocorr(feature) and returns: autocorr_vec