code: def _generate_int8_f32io_concat_residual_tflite(
      self, number_of_inputs=3
  ):
      dtype = float
  
      class ConcatNResidual(tf.keras.layers.Layer):
          """A simple concat and residual Keras Model."""
  
          def __init__(self, number_of_inputs=3, **kwargs):
              super().__init__(**kwargs)
              self.number_of_inputs = number_of_inputs
              self.conv = tf.keras.layers.Conv2D(
                  2, (2, 2), padding="same"
              )
              self.mins = [
                  -0.01 * (i + 1) for i in range(self.number_of_inputs)
              ]
              self.maxs = [
                  0.01 * (i + 1) for i in range(self.number_of_inputs)
              ]
  
          def call(self, inputs):
              xs = [
                  tf.quantization.fake_quant_with_min_max_args(
                      inputs[i], self.mins[i], self.maxs[i]
                  )
                  for i in range(self.number_of_inputs)
              ]
              x = tf.keras.backend.concatenate(xs, 1)
              x = x[:, : inputs[-1].shape[1]]
              x = x + xs[-1]
              x = tf.quantization.fake_quant_with_min_max_args(
                  x, -2.242, 2.242
              )
              return x
  
      inputs = [
          tf.keras.layers.Input(
              shape=(2, 2, 2), batch_size=1, dtype=dtype
          )
          for _ in range(number_of_inputs)
      ]
      outputs = ConcatNResidual(number_of_inputs)(inputs)
      model = tf.keras.Model(inputs, outputs)
  
      converter = tf.lite.TFLiteConverter.from_keras_model(model)
      converter.optimizations = [tf.lite.Optimize.DEFAULT]
      tflite_model = converter.convert()
      return tflite_model
  
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 1 for calling the UtilModifyIntegerQuantizedConcatResidualModelIOTypeTest obj's underlying member method code with example usage: obj._generate_int8_f32io_concat_residual_tflite(number_of_inputs) and returns: tflite_model, x