code: def test_dropout_random_mask_is_recomputed_on_forward_pass():
      from cntk import dropout, input
  
      shape = (100, 100)
      dtype = np.float32
      value = np.ones(shape=shape, dtype=dtype)
  
      a = input(shape=shape, needs_gradient=True, dtype=dtype)
      dropout_node = dropout(a, dropout_rate=0.1)
      network = dropout_node + constant(0)
  
      value.shape = (1,) + value.shape
  
      _, forward = network.forward(
          {a: value}, network.outputs, network.outputs
      )
      non_zeros_1 = forward[network.output] > 0.0
  
      _, forward = network.forward(
          {a: value}, network.outputs, network.outputs
      )
      non_zeros_2 = forward[network.output] > 0.0
  
      assert not (non_zeros_1 == non_zeros_2).all()
  
imports: from __future__ import division
  import numpy
  import cntk
  import pytest
  from .ops_test_utils import unittest_helper, _test_unary_op, _test_binary_op, AA, precision, PRECISION_TO_TYPE, cntk_device
  from cntk.tests.test_utils import TOLERANCE_ABSOLUTE
  from cntk.internal.utils import eval
  from cntk.internal import sanitize_dtype_cntk
  from ..None import constant
  from cntk.variables import Parameter, Constant
label_desc: Use image node_id 9 for calling a global function with example usage: test_dropout_random_mask_is_recomputed_on_forward_pass() without return types