code: def test_layer_direct_compare_metrics(self, quantized_io):
      def _corr(float_values, quant_values, scale, zero_point):
          dequant_values = (
              quant_values.astype(np.int32) - zero_point
          ) * scale
          return np.corrcoef(
              float_values.flatten(), dequant_values.flatten()
          )[0, 1]
  
      if quantized_io:
          debug_model = QuantizationDebuggerTest.debug_model_int8
      else:
          debug_model = QuantizationDebuggerTest.debug_model_float
  
      options = debugger.QuantizationDebugOptions(
          layer_direct_compare_metrics={"corr": _corr}
      )
      quant_debugger = debugger.QuantizationDebugger(
          quant_debug_model_content=debug_model,
          debug_dataset=_calibration_gen,
          debug_options=options,
      )
      quant_debugger.run()
  
      expected_metrics = {
          "corr": 0.99999,
      }
      self.assertLen(quant_debugger.layer_statistics, 1)
      actual_metrics = next(
          iter(quant_debugger.layer_statistics.values())
      )
  
      for key, value in expected_metrics.items():
          self.assertAlmostEqual(value, actual_metrics[key], places=4)
  
imports: import csv
  import io
  import re
  from unittest import mock
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.lite.python import convert
  from tensorflow.lite.python import lite
  from tensorflow.lite.python.metrics import metrics
  from tensorflow.lite.tools.optimize.debugging.python import debugger
  from tensorflow.python.framework import test_util
  from tensorflow.python.platform import test
  from tensorflow.python.trackable import autotrackable
label_desc: Use image node_id 4 for calling the QuantizationDebuggerTest obj's underlying member method code with example usage: obj.test_layer_direct_compare_metrics(quantized_io) and returns: np