code: def testDtype(self):
      dist = make_bernoulli([])
      self.assertEqual(dist.dtype, tf.int32)
      self.assertEqual(
          dist.dtype, dist.sample(5, seed=test_util.test_seed()).dtype
      )
      self.assertEqual(dist.dtype, dist.mode().dtype)
      self.assertEqual(dist.probs.dtype, dist.mean().dtype)
      self.assertEqual(dist.probs.dtype, dist.variance().dtype)
      self.assertEqual(dist.probs.dtype, dist.stddev().dtype)
      self.assertEqual(dist.probs.dtype, dist.entropy().dtype)
      self.assertEqual(dist.probs.dtype, dist.prob(0).dtype)
      self.assertEqual(dist.probs.dtype, dist.prob(1).dtype)
      self.assertEqual(dist.probs.dtype, dist.log_prob(0).dtype)
      self.assertEqual(dist.probs.dtype, dist.log_prob(1).dtype)
  
      dist64 = make_bernoulli([], tf.int64)
      self.assertEqual(dist64.dtype, tf.int64)
      self.assertEqual(
          dist64.dtype,
          dist64.sample(5, seed=test_util.test_seed()).dtype,
      )
      self.assertEqual(dist64.dtype, dist64.mode().dtype)
  
imports: import numpy
  from scipy import special
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import bernoulli
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the BernoulliTest obj's underlying member method code with example usage: obj.testDtype() without return types