code: def _print_dt(self, timea, timeb, N):
      dt = timeb - timea
      dts = dt.seconds + dt.microseconds * 10**-6
      rate = N / dts
      print(
          f"Classified {N} samples in {dts} seconds ({rate} inferences / s)"
      )
      return dts, rate
  
file_path: hls4ml/hls4ml/templates/vivado_accelerator/pynq-z2/python_drivers/axi_stream_driver.py
imports: from datetime import datetime
  import numpy
  from pynq import Overlay, allocate
label_desc: Use image node_id 2 for calling the NeuralNetworkOverlay obj's underlying member method code with example usage: obj._print_dt(timea, timeb, N) and returns: dts,  rate