class_docstr: Max calibrator, tracks the maximum value globally
  
  Args:
      calib_desc: A MaxCalibDescriptor.
      num_bits: An integer. Number of bits of quantization.
      axis: A tuple. see QuantDescriptor.
      unsigned: A boolean. using unsigned quantization.
  
  Readonly Properties:
      amaxs: A list of amax. Numpy array is saved as it is likely to be used for some plot.
class_docstr_tok: ["Max","calibrator",",","tracks","the","maximum","value","globally","Args",":","calib_desc",":","A","MaxCalibDescriptor",".","num_bits",":","An","integer",".","Number","of","bits","of","quantization",".","axis",":","A","tuple",".","see","QuantDescriptor",".","unsigned",":","A","boolean",".","using","unsigned","quantization",".","Readonly","Properties",":","amaxs",":","A","list","of","amax",".","Numpy","array","is","saved","as","it","is","likely","to","be","used","for","some","plot","."]
code: def __repr__(self):
      s = "MaxCalibrator("
      s += super(MaxCalibrator, self).__repr__()
      s += " calib_amax={_calib_amax}"
      s += " track_amax={_track_amax}"
      if self._track_amax:
          s += " amaxs={_amaxs}"
      s += ")"
      return s.format(**self.__dict__)
  
file_path: lightseq/lightseq/csrc/pytorch/pytorch_quantization/calib/max.py
imports: import logging
  import torch
  from csrc.pytorch.pytorch_quantization.calib.calibrator import _Calibrator
  from csrc.pytorch.pytorch_quantization import utils
label_desc: Use image node_id 7 for calling the MaxCalibrator obj's underlying member method code with example usage: obj.__repr__() and returns: s