code: def test_integer_dtype(self):
      running_mean = sample_stats.RunningMean.from_shape(
          shape=(), dtype=tf.int32
      )
      for sample in range(6):
          running_mean = running_mean.update(sample)
      mean = running_mean.mean
      self.assertEqual(tf.float32, mean.dtype)
      mean = self.evaluate(mean)
      self.assertEqual(2.5, mean)
  
imports: from absl.testing import parameterized
  import numpy
  import scipy.stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.stats import sample_stats
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc import diagnostic
label_desc: Use image node_id 3 for calling the RunningMeanTest obj's underlying member method code with example usage: obj.test_integer_dtype() without return types