code: def do_quantize(self, layer, weight_param="bias"):
      ret = super(LayerSelector, self).do_quantize(layer)
      if not ret or layer.name == self.layer_name:
          return False
      return True
  
imports: import os
  import shutil
  import tempfile
  import unittest
  import numpy
  import coremltools.models.datatypes
  from coremltools.models import MLModel
  from coremltools.models.neural_network import AdamParams, NeuralNetworkBuilder, SgdParams, quantization_utils
  from coremltools.models.pipeline import PipelineClassifier, PipelineRegressor
  from coremltools.models.utils import save_spec
label_desc: Use image node_id 2 for calling the LayerSelector obj's underlying member method code with example usage: obj.do_quantize(layer, weight_param) and returns: True, False