code: def test_gamma_generator():
      success_rate = 0.05
      ctx = mx.context.current_context()
      for dtype in ["float16", "float32", "float64"]:
          for kappa, theta in [(0.5, 1.0), (1.0, 5.0)]:
              buckets, probs = gen_buckets_probs_with_ppf(
                  lambda x: ss.gamma.ppf(
                      x, a=kappa, loc=0, scale=theta
                  ),
                  5,
              )
              generator_mx = lambda x: mx.nd.random.gamma(
                  kappa, theta, shape=x, ctx=ctx, dtype=dtype
              ).asnumpy()
              verify_generator(
                  generator=generator_mx,
                  buckets=buckets,
                  probs=probs,
                  success_rate=success_rate,
              )
              generator_mx_same_seed = lambda x: np.concatenate(
                  [
                      mx.nd.random.gamma(
                          kappa,
                          theta,
                          shape=x // 10,
                          ctx=ctx,
                          dtype=dtype,
                      ).asnumpy()
                      for _ in range(10)
                  ]
              )
              verify_generator(
                  generator=generator_mx_same_seed,
                  buckets=buckets,
                  probs=probs,
                  success_rate=success_rate,
              )
  
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 14 for calling a global function with example usage: test_gamma_generator() without return types