code: def test_binomial_generator():
      ctx = mx.context.current_context()
      for dtype in ["float16", "float32", "float64"]:
          trials_num = 10000
          success_prob = 0.25
  
          buckets, probs = gen_buckets_probs_with_ppf(
              lambda x: ss.binom.ppf(x, trials_num, success_prob), 10
          )
          generator_mx = lambda x: mx.nd.random.binomial(
              trials_num, success_prob, shape=x, ctx=ctx, dtype=dtype
          ).asnumpy()
          nsamples = 1000
          verify_generator(
              generator=generator_mx,
              buckets=buckets,
              probs=probs,
              nsamples=nsamples,
          )
          generator_mx_same_seed = lambda x: np.concatenate(
              [
                  mx.nd.random.binomial(
                      trials_num,
                      success_prob,
                      shape=x // 10,
                      ctx=ctx,
                      dtype=dtype,
                  ).asnumpy()
                  for _ in range(10)
              ]
          )
          verify_generator(
              generator=generator_mx_same_seed,
              buckets=buckets,
              probs=probs,
              nsamples=nsamples,
          )
  
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 17 for calling a global function with example usage: test_binomial_generator() without return types