code: def write_examples(fp, examples):
      """Given a list `examples`, write a text format representation.
  
      The file format is csv like with a simple repeated pattern. We would ike
      to use proto here, but we can't yet due to interfacing with the Android
      team using this format.
  
      Args:
        fp: File-like object to write to.
        examples: Example dictionary consisting of keys "inputs" and "outputs"
      """
  
      def write_tensor(fp, name, x):
          """Write tensor in file format supported by TFLITE example."""
          fp.write("name,%s\n" % name)
          fp.write("dtype,%s\n" % x.dtype)
          fp.write("shape," + ",".join(map(str, x.shape)) + "\n")
          fp.write("values," + format_result(x) + "\n")
  
      fp.write("test_cases,%d\n" % len(examples))
      for example in examples:
          fp.write("inputs,%d\n" % len(example["inputs"]))
          for name, value in example["inputs"].items():
              if value is not None:
                  write_tensor(fp, name, value)
          fp.write("outputs,%d\n" % len(example["outputs"]))
          for name, value in example["outputs"].items():
              write_tensor(fp, name, value)
  
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 7 for calling a global function with example usage: write_examples(fp, examples) without return types