class_docstr: Emulate quantization of tensors passed through the layer.
code: def from_config(cls, config):
      config = config.copy()
  
      # Deserialization code should ensure Quantizer is in keras scope.
      quantizer = deserialize_keras_object(
          config.pop("quantizer"),
          module_objects=globals(),
          custom_objects=None,
      )
  
      return cls(quantizer=quantizer, **config)
  
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 5 for calling the QuantizeLayer obj's underlying member method code with example usage: obj.from_config(cls, config) and returns: cls