code: def __init__(self, functions_ranks, config=None):
      super(QuantizeRecordingToTrainingModifier, self).__init__()
      self._fct_bin_set = {
          "Add2": F.add2,
          "Sub2": F.sub2,
          "Mul2": F.mul2,
          "Div2": F.div2,
          "Pow2": F.pow2,
      }
  
      from nnabla.utils.qnn import PrecisionMode
  
      self._mode = self._precision_mode_set = {
          PrecisionMode.QNN: None,
          PrecisionMode.SIM_QNN: self.SimulatedQNN,
          PrecisionMode.MIXED_QNN: None,
      }[config.precision_mode](functions_ranks, self, config)
  
imports: import nnabla
  import nnabla.functions
  import numpy
  from collections import defaultdict
  from .graph_converter import FunctionModifier
  from .batch_normalization_folding import BatchNormalizationFoldingModifier
  from .batch_normalization_self_folding import BatchNormalizationSelfFoldingModifier
  from .remove_function import RemoveFunctionModifier
label_desc: Use image node_id 1 to create a new QuantizeRecordingToTrainingModifier object from inherited base classes: FunctionModifier with example: obj = QuantizeRecordingToTrainingModifier(functions_ranks, config)