code: def testUint32PassThrough(self):
      model = tf.keras.Sequential(
          [
              tf.keras.layers.InputLayer(
                  input_shape=(4,), dtype=tf.uint32
              ),
              tf.keras.layers.Reshape(target_shape=(2, 2)),
          ]
      )
      converter = tf.lite.TFLiteConverter.from_keras_model(model)
      tflite_model = converter.convert()
      interpreter = tf.lite.Interpreter(model_content=tflite_model)
      interpreter.allocate_tensors()
      input_details = interpreter.get_input_details()[0]
      output_details = interpreter.get_output_details()[0]
  
      self.assertEqual(input_details["dtype"], np.uint32)
      self.assertEqual(output_details["dtype"], np.uint32)
  
      in_array = np.array([[1, 1, 1, 1]], dtype="uint32") * (
          (1 << 32) - 1
      )
      expected_out = np.reshape(in_array, (2, 2))
  
      interpreter.set_tensor(input_details["index"], in_array)
      interpreter.invoke()
  
      output_data = interpreter.get_tensor(output_details["index"])[0]
      self.assertAllEqual(expected_out, output_data)
  
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 the UtilTest obj's underlying member method code with example usage: obj.testUint32PassThrough() without return types