code: def create_scalar_data(dtype, min_value=-100, max_value=100):
      """Build scalar tensor data range from min_value to max_value exclusively."""
  
      if dtype in MAP_TF_TO_NUMPY_TYPE:
          dtype = MAP_TF_TO_NUMPY_TYPE[dtype]
  
      if dtype in (tf.float32, tf.float16, tf.float64):
          value = (
              max_value - min_value
          ) * np.random.random() + min_value
      elif dtype in (tf.int32, tf.uint8, tf.int64, tf.int16):
          value = np.random.randint(min_value, max_value + 1)
      elif dtype == tf.bool:
          value = np.random.choice([True, False])
      elif dtype == np.string_:
          l = np.random.randint(1, 6)
          value = "".join(
              np.random.choice(list(string.ascii_uppercase), size=l)
          )
      return np.array(value, dtype=dtype)
  
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 4 for calling a global function with example usage: create_scalar_data(dtype, min_value, max_value) and returns: np