code: def testLargeLogits(self):
      for neg in [True, False]:
          with test_util.use_gpu():
              logits = np.array([[1000.0] * 5])
              if neg:
                  logits *= -1
              samples = self.evaluate(
                  random_ops.multinomial(logits, 10)
              )
          # Sampled classes should be in-range.
          self.assertTrue((samples >= 0).all())
          self.assertTrue((samples < 5).all())
  
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 8 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testLargeLogits() without return types