code: def _test_param_modify_integer_model_io_type():
      """Function to generate parameterized inputs for testing."""
      params = []
      str_template = "_{}{}{}{}"
      map_model_type = {
          "PostTraining": True,
          # "DuringTraining": False,
      }
      map_quantize_type_to_io_types = {
          tf.int8: {tf.float32, tf.int8, tf.uint8},
          tf.int16: {tf.float32, tf.int16},
      }
      for k1, v1 in map_model_type.items():
          for qtype, v2 in map_quantize_type_to_io_types.items():
              qstr = "_IntegerQuantize{}".format(
                  qtype.name.capitalize()
              )
              for itype in v2:
                  istr = "_Input{}".format(itype.name.capitalize())
                  for otype in v2:
                      ostr = "_Output{}".format(otype.name.capitalize())
                      params.append(
                          (
                              str_template.format(k1, qstr, istr, ostr),
                              v1,
                              qtype,
                              itype,
                              otype,
                          )
                      )
      return params
  
imports: import os
  from absl.testing import parameterized
  import numpy
  import tensorflow
  from tensorflow.lite.python import util
  from tensorflow.lite.tools.flatbuffer_utils import read_model
  from tensorflow.python.client import session
  from tensorflow.python.framework import convert_to_constants
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import while_loop
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling a global function with example usage: _test_param_modify_integer_model_io_type() and returns: params