class_docstr: Emulate quantization of tensors passed through the layer.
code: def build(self, input_shape):
      if self.quantizer:
          self.quantizer_vars = self.quantizer.build(
              input_shape, self.name, self
          )
  
      self.optimizer_step = self.add_weight(
          "optimizer_step",
          initializer=tf.keras.initializers.Constant(-1),
          dtype=tf.dtypes.int32,
          trainable=False,
      )
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/quantize_layer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
  from tensorflow_model_optimization.python.core.keras import utils
  from tensorflow_model_optimization.python.core.quantization.keras import quantizers
  from tensorflow_model_optimization.python.core.quantization.keras import utils
label_desc: Use image node_id 2 for calling the QuantizeLayer obj's underlying member method code with example usage: obj.build(input_shape) without return types