class_docstr: Test cases for random-number generating operators.
code: def testCategoricalIsNotConstant(self):
      def rng(dtype, output_dtype):
          return random_ops.multinomial(
              np.array([[1.0, 1.0, 1.0]], dtype=dtype),
              10,
              output_dtype=output_dtype,
          )
  
      dtype = np.float32
      for output_dtype in self.output_dtypes():
          self._testRngIsNotConstant(rng, dtype, output_dtype)
  
imports: import collections
  import numpy
  from tensorflow.compiler.tests import xla_test
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import random_seed
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import stateless_random_ops
  from tensorflow.python.platform import googletest
  from tensorflow.python.platform import test
label_desc: Use image node_id 5 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testCategoricalIsNotConstant() and returns: random_ops