docstr: If there is a cache, use it instead of calibrating again. Otherwise, implicitly return None.
  
  Returns
  -------
  cache object
      A cache object which contains calibration parameters for quantization
code: def read_calibration_cache(self):
      """
      If there is a cache, use it instead of calibrating again. Otherwise, implicitly return None.
  
      Returns
      -------
      cache object
          A cache object which contains calibration parameters for quantization
      """
      if os.path.exists(self.cache_file):
          with open(self.cache_file, "rb") as f:
              return f.read()
  
file_path: nni/nni/compression/quantization_speedup/calibrator.py
imports: import os
  import logging
  import tensorrt
  import pycuda.driver
label_desc: Use image node_id 5 for calling the Calibrator obj's underlying member method code with example usage: obj.read_calibration_cache() and returns: f