code: def _QuantizedOutputToFloat(
      self, quantized, quantized_min, quantized_max
  ):
      number_of_bits = 32
      number_of_steps = 1 << number_of_bits
      range_adjust = number_of_steps / (number_of_steps - 1.0)
      quantized_range = (quantized_max - quantized_min) * range_adjust
      range_scale = quantized_range / number_of_steps
      lowest_quantized = -(1 << (number_of_bits - 1))
      result = np.array(
          [
              (
                  quantized_min
                  + ((float(x) - lowest_quantized) * range_scale)
              )
              for x in quantized.flatten()
          ]
      )
      return result
  
file_path: tensorflow-upstream/tensorflow/python/ops/quantized_conv_ops_test.py
imports: import numpy
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 4 for calling the Conv2DTest obj's underlying member method code with example usage: obj._QuantizedOutputToFloat(quantized, quantized_min, quantized_max) and returns: result