code: def testLargeDynamicRange3(self):
      random_seed.set_random_seed(10)
      counts_by_indices = {}
      # here the cpu undersamples and won't pass this test either
      with self.test_session():
          samples = random_ops.multinomial(
              constant_op.constant([[0, -17]], dtype=dtypes.float32),
              num_samples=1000000,
              seed=22,
          )
  
          # we'll run out of memory if we try to draw 1e9 samples directly
          # really should fit in 12GB of memory...
          for _ in range(100):
              x = self.evaluate(samples)
              indices, counts = np.unique(
                  x, return_counts=True
              )  # pylint: disable=unexpected-keyword-arg
              for index, count in zip(indices, counts):
                  if index in counts_by_indices.keys():
                      counts_by_indices[index] += count
                  else:
                      counts_by_indices[index] = count
      self.assertGreater(counts_by_indices[1], 0)
  
file_path: tensorflow-upstream/tensorflow/python/kernel_tests/random/multinomial_op_big_test.py
imports: import numpy
  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 test_util
  from tensorflow.python.ops import random_ops
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the MultinomialTest obj's underlying member method code with example usage: obj.testLargeDynamicRange3() without return types