code: def autocorrelate(signal, lag=1):
      """Gives the correlation coefficient for the signal's correlation with itself.
  
      Args:
        signal: The signal on which to compute the autocorrelation. Can be a list.
        lag: The offset at which to correlate the signal with itself. E.g. if lag
          is 1, will compute the correlation between the signal and itself 1 beat
          later.
      Returns:
        Correlation coefficient.
      """
      n = len(signal)
      x = np.asarray(signal) - np.mean(signal)
      c0 = np.var(signal)
  
      return (x[lag:] * x[: n - lag]).sum() / float(n) / c0
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import random
  from magenta.contrib import training
  import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 4 for calling a global function with example usage: autocorrelate(signal, lag) and returns: unknown