class_docstr: Test cases for random-number generating operators.
code: def testCategoricalIsInRange(self):
      for dtype in self.float_types:
          for output_dtype in self.output_dtypes():
              with self.session():
                  with self.test_scope():
                      x = random_ops.multinomial(
                          array_ops.ones(shape=[1, 20], dtype=dtype),
                          1000,
                          output_dtype=output_dtype,
                      )
                  y = self.evaluate(x)
                  self.assertTrue((y >= 0).sum() == 1000)
                  self.assertTrue((y < 20).sum() == 1000)
  
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 6 for calling the CategoricalTest obj's underlying member method code with example usage: obj.testCategoricalIsInRange() without return types