code: def testBrokenShapeUnknownCategories(self):
      with self.assertRaisesWithPredicateMatch(
          ValueError, r"Could not infer"
      ):
          cat_logits = tf.Variable(
              [[13.0, 19.0]], shape=[1, None], dtype=tf.float32
          )
          mixture.Mixture(
              categorical.Categorical(cat_logits),
              [normal.Normal(loc=[1.0], scale=[2.0])],
              validate_args=True,
          )
  
imports: import contextlib
  import warnings
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import categorical
  from tensorflow_probability.python.distributions import dirichlet
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import gamma
  from tensorflow_probability.python.distributions import half_normal
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mixture
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import mvn_tril
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import hypothesis_testlib
  from tensorflow_probability.python.internal import reparameterization
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the MixtureTest obj's underlying member method code with example usage: obj.testBrokenShapeUnknownCategories() without return types