code: def _get_quant_params(
      tensor_detail: Mapping[str, Any]
  ) -> Optional[Tuple[float, int]]:
      """Returns first scale and zero point from tensor detail, if present."""
      quant_params = tensor_detail["quantization_parameters"]
      if not quant_params:
          return None
      if quant_params["scales"] and quant_params["zero_points"]:
          return (
              quant_params["scales"][0],
              quant_params["zero_points"][0],
          )
      return None
  
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 1 for calling a global function with example usage: _get_quant_params(tensor_detail) and returns: None, None, quant_params,  quant_params