code: def testSmallEntropy(self):
      random_seed.set_random_seed(1618)
      for output_dtype in [np.int32, np.int64]:
          with test_util.device(use_gpu=True):
              # A logit value of -10 corresponds to a probability of ~5e-5.
              logits = constant_op.constant(
                  [[-10.0, 10.0, -10.0], [-10.0, -10.0, 10.0]]
              )
              num_samples = 1000
              samples = self.evaluate(
                  random_ops.multinomial(
                      logits, num_samples, output_dtype=output_dtype
                  )
              )
              self.assertAllEqual(
                  [[1] * num_samples, [2] * num_samples], samples
              )
  
imports: import collections
  import timeit
  import numpy
  from tensorflow.core.protobuf import config_pb2
  from tensorflow.python.client import session
  from tensorflow.python.eager import context
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import random_seed
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import test_util
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import control_flow_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 1 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testSmallEntropy() without return types