code: def test_unique_zipfian_generator():
      ctx = mx.context.current_context()
      if ctx.device_type == "cpu":
          num_sampled = 8192
          range_max = 793472
          batch_size = 4
          op = mx.nd._internal._sample_unique_zipfian
          classes, num_trials = op(
              range_max, shape=(batch_size, num_sampled)
          )
          for i in range(batch_size):
              num_trial = num_trials[i].asscalar()
              # test uniqueness
              assert np.unique(classes[i].asnumpy()).size == num_sampled
              # test num trials. reference count obtained from pytorch implementation
              assert num_trial > 14500
              assert num_trial < 17000
  
imports: import os
  import math
  import itertools
  import mxnet
  from mxnet.test_utils import verify_generator, gen_buckets_probs_with_ppf, assert_almost_equal
  import numpy
  import random
  from common import retry, random_seed
  import scipy.stats
  import unittest
  import pytest
  from mxnet.test_utils import *
  from mxnet.base import MXNetError
  from common import assertRaises
label_desc: Use image node_id 23 for calling a global function with example usage: test_unique_zipfian_generator() without return types