code: def _GetMinMaxValues(self, quantize_fn, input_values, **kwds):
      min_var = tf.Variable(0.0)
      max_var = tf.Variable(0.0)
      compat.initialize_variables(self)
  
      for input_elem in input_values:
          y = quantize_fn(
              input_elem, min_var, max_var, is_training=True, **kwds
          )
          self.evaluate(y)
  
      # Now check that the min_max_vars were, in fact, updated.
      min_max_values = self.evaluate([min_var, max_var])
      return min_max_values[0], min_max_values[1]
  
file_path: model-optimization/tensorflow_model_optimization/python/core/quantization/keras/quant_ops_test.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 compat
  from tensorflow_model_optimization.python.core.quantization.keras import quant_ops
label_desc: Use image node_id 12 for calling the QuantOpsTest obj's underlying member method code with example usage: obj._GetMinMaxValues(quantize_fn, input_values) and returns: min_max_values,  min_max_values