class_docstr: Saves layer output min and max values in a dict with layer names as keys.
  The collected min and max values will be directly used as thresholds for quantization.
class_docstr_tok: ["Saves","layer","output","min","and","max","values","in","a","dict","with","layer","names","as","keys",".","The","collected","min","and","max","values","will","be","directly","used","as","thresholds","for","quantization","."]
code: def __init__(self, quantized_dtype, include_layers=None, logger=None):
      super(_LayerOutputMinMaxCollector, self).__init__()
      self.min_max_dict = {}
      self.quantized_dtype = quantized_dtype
      self.include_layers = include_layers
      self.logger = logger
  
imports: import abc
  import ctypes
  import logging
  import os
  import warnings
  import numpy
  import mxnet
  from ..base import _LIB, check_call, py_str
  from ..base import c_array, c_str, mx_uint, mx_real_t, c_str_array
  from ..base import SymbolHandle
  from ..symbol import Symbol
  from ..None import ndarray
  from ..io import DataDesc
  from ..device import cpu, Device
  from ..util import is_np_array, wrap_ctx_to_device_func
label_desc: Use image node_id 1 to create a new _LayerOutputMinMaxCollector object from inherited base classes: CalibrationCollector with example: obj = _LayerOutputMinMaxCollector(quantized_dtype, include_layers, logger)