class_docstr: HistogramMseSymmetric for calculating min and max values of calibration result.
class_docstr_tok: ["HistogramMseSymmetric","for","calculating","min","and","max","values","of","calibration","result","."]
docstr: Finds min and max starting from the center index.
  
  The HistogramMseSymmetric method starts from the center bin and expands the
  range to both sides. This works better when the data is well-centered.
  
  Returns:
    (min_value, max_value): Min and max calculated using the method starting
    from center and expanding.
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code: def get_min_max_value(self) -> tuple[float, float]:
      """Finds min and max starting from the center index.
  
      The HistogramMseSymmetric method starts from the center bin and expands the
      range to both sides. This works better when the data is well-centered.
  
      Returns:
        (min_value, max_value): Min and max calculated using the method starting
        from center and expanding.
      """
  
      # This function is currently only called in this method, but will be used in
      # other methods in the future.
      return self._get_min_max_value_by_expanding_range(
          self._num_bins // 2
      )
  
imports: import abc
  import itertools
  import logging
  import numpy
  from tensorflow.compiler.mlir.quantization.tensorflow import quantization_options_pb2
  from tensorflow.compiler.mlir.quantization.tensorflow.calibrator import calibration_statistics_pb2
label_desc: Use image node_id 1 for calling the _HistogramMseSymmetric obj's underlying member method code with example usage: obj.get_min_max_value() and returns: self