code: def testNotReparameterized(self):
      p = tf.constant([0.3, 0.3, 0.4])
      _, grad_p = gradient.value_and_gradient(
          # pylint: disable=g-long-lambda
          lambda x: categorical.Categorical(
              x, validate_args=True
          ).sample(100, seed=test_util.test_seed()),
          p,
      )
      self.assertIsNone(grad_p)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import identity
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 25 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testNotReparameterized() without return types