code: def testDtype(self):
      loc = tf.constant([0.1, 0.4], dtype=tf.float32)
      scale = tf.constant(1.0, dtype=tf.float32)
      dist = logistic.Logistic(loc, scale, validate_args=True)
      self.assertEqual(dist.dtype, tf.float32)
      self.assertEqual(dist.loc.dtype, dist.scale.dtype)
      self.assertEqual(
          dist.dtype, dist.sample(5, seed=test_util.test_seed()).dtype
      )
      self.assertEqual(dist.dtype, dist.mode().dtype)
      self.assertEqual(dist.loc.dtype, dist.mean().dtype)
      self.assertEqual(dist.loc.dtype, dist.variance().dtype)
      self.assertEqual(dist.loc.dtype, dist.stddev().dtype)
      self.assertEqual(dist.loc.dtype, dist.entropy().dtype)
      self.assertEqual(dist.loc.dtype, dist.prob(0.2).dtype)
      self.assertEqual(dist.loc.dtype, dist.log_prob(0.2).dtype)
  
      loc = tf.constant([0.1, 0.4], dtype=tf.float64)
      scale = tf.constant(1.0, dtype=tf.float64)
      dist64 = logistic.Logistic(loc, scale, validate_args=True)
      self.assertEqual(dist64.dtype, tf.float64)
      self.assertEqual(
          dist64.dtype,
          dist64.sample(5, seed=test_util.test_seed()).dtype,
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import logistic
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 12 for calling the LogisticTest obj's underlying member method code with example usage: obj.testDtype() without return types