code: def testDtype(self):
      dist = make_onehot_categorical([], 5, dtype=tf.int32)
      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)
      dist = make_onehot_categorical([], 5, dtype=tf.int64)
      self.assertEqual(dist.dtype, tf.int64)
      self.assertEqual(
          dist.dtype, dist.sample(5, seed=test_util.test_seed()).dtype
      )
      self.assertEqual(dist.dtype, dist.mode().dtype)
      self.assertEqual(dist.probs_parameter().dtype, tf.float32)
      self.assertEqual(dist.logits.dtype, tf.float32)
      self.assertEqual(dist.logits.dtype, dist.entropy().dtype)
      self.assertEqual(
          dist.logits.dtype,
          dist.prob(np.array([1] + [0] * 4, dtype=np.int64)).dtype,
      )
      self.assertEqual(
          dist.logits.dtype,
          dist.log_prob(np.array([1] + [0] * 4, dtype=np.int64)).dtype,
      )
  
imports: import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import onehot_categorical
  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.util import deferred_tensor
label_desc: Use image node_id 6 for calling the OneHotCategoricalTest obj's underlying member method code with example usage: obj.testDtype() without return types