code: def test_cudnn_dropout_reproducibility():
      d = nn.Dropout(0.5)
      d.initialize()
      a = mx.np.random.uniform(size=(100, 100))
      b = a.copy()
      a.attach_grad()
      b.attach_grad()
      seed = mx.np.random.randint(0, 100000).item()
      N = 10
      mx.np.random.seed(seed)
      out1 = []
      for _ in range(N):
          with autograd.record():
              out1.append(d(a))
      out1[0].backward()
      mx.np.random.seed(seed)
      out2 = []
      for _ in range(N):
          with autograd.record():
              out2.append(d(b))
      out2[0].backward()
  
      for first, second in zip(out1, out2):
          assert_almost_equal(first, second)
  
      assert_almost_equal(a.grad, b.grad)
  
imports: import sys
  import os
  import time
  import random
  import mxnet
  import multiprocessing
  from mxnet.test_utils import check_consistency, set_default_device, assert_almost_equal, rand_ndarray, environment
  import numpy
  import math
  from mxnet import autograd
  import pytest
  from common import assert_raises_cudnn_not_satisfied, run_in_spawned_process, random_seed
  from test_gluon import *
  from test_loss import *
  from test_numpy_loss import *
  from test_gluon_rnn import *
label_desc: Use image node_id 20 for calling a global function with example usage: test_cudnn_dropout_reproducibility() without return types