code: def format_result(t):
      """Convert a tensor to a format that can be used in test specs."""
      if t.dtype.kind not in [
          np.dtype(np.string_).kind,
          np.dtype(np.object_).kind,
      ]:
          # Output 9 digits after the point to ensure the precision is good enough.
          values = [
              "{:.9f}".format(value) for value in list(t.flatten())
          ]
          return ",".join(values)
      else:
          # SerializeAsHexString returns bytes in PY3, so decode if appropriate.
          return _pywrap_string_util.SerializeAsHexString(
              t.flatten()
          ).decode("utf-8")
  
imports: import functools
  import io
  import itertools
  import operator
  import os
  import re
  import string
  import sys
  import tempfile
  import traceback
  import zipfile
  import numpy
  import tensorflow
  from google.protobuf import text_format
  from tensorflow.lite.testing import _pywrap_string_util
  from tensorflow.lite.testing import generate_examples_report
  from tensorflow.lite.tools import flatbuffer_utils
  from tensorflow.python.framework import convert_to_constants
  from tensorflow.python.saved_model import signature_constants
label_desc: Use image node_id 6 for calling a global function with example usage: format_result(t) and returns: str, _pywrap_string_util