code: def testAssertionsLogits(self):
      x = deferred_tensor.TransformedVariable(
          0.0, identity.Identity(), shape=None
      )
      with self.assertRaisesRegexp(
          ValueError, "Argument `logits` must have rank at least 1."
      ):
          d = categorical.Categorical(logits=x, validate_args=True)
          self.evaluate([v.initializer for v in d.variables])
          self.evaluate(d.entropy())
  
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 4 for calling the CategoricalFromVariableTest obj's underlying member method code with example usage: obj.testAssertionsLogits() without return types