class_docstr: Debugger for Quantized TensorFlow Lite debug mode models.
  
  This can run the TensorFlow Lite converted models equipped with debug ops and
  collect debug information. This debugger calculates statistics from
  user-defined post-processing functions as well as default ones.
docstr: Returns an instrumented quantized model.
  
  Convert the quantized model with the initialized converter and
  return bytes for model. The model will be instrumented with numeric
  verification operations and should only be used for debugging.
  
  Returns:
    Model bytes corresponding to the model.
  Raises:
    ValueError: if converter is not passed to the debugger.
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code: def get_debug_quantized_model(self) -> bytes:
      """Returns an instrumented quantized model.
  
      Convert the quantized model with the initialized converter and
      return bytes for model. The model will be instrumented with numeric
      verification operations and should only be used for debugging.
  
      Returns:
        Model bytes corresponding to the model.
      Raises:
        ValueError: if converter is not passed to the debugger.
      """
      return self._get_quantized_model(is_debug=True)
  
imports: import collections
  import csv
  import re
  from typing import Any, Callable, Dict, IO, Iterable, List, Mapping, Optional, Sequence, Tuple
  import numpy
  from tensorflow.lite.python import convert
  from tensorflow.lite.python import interpreter
  from tensorflow.lite.python.metrics import metrics
  from tensorflow.python.util import tf_export
label_desc: Use image node_id 7 for calling the QuantizationDebugger obj's underlying member method code with example usage: obj.get_debug_quantized_model() and returns: self